Reviews

W. F. Maier et al.

DOI: 10.1002/anie.200603675

Materials Research

Combinatorial and High-Throughput Materials Science
Wilhelm F. Maier,* Klaus Stwe, and Simone Sieg

Keywords:
catalysts · combinatorial chemistry ·high-throughput analysis ·materials libraries ·materials science

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There is increasing acceptance of high-throughput technologies for the
discovery, development, and optimization of materials and catalysts inindustry. Over the years, the relative synchronous development oftechnologies for parallel synthesis and characterization has beenaccompanied by developments in associated software and information
technologies. This Review aims to provide a comprehensive overview
on the state of the art of the field by selected examples. Technologies
developed to aid research on complex materials are covered as well as
databases, design of experiment, data-mining technologies, modelingapproaches, and evolutionary strategies for development. Different
methods for parallel synthesis provide single sample libraries, gradientlibraries for electronic or optical materials, similar to polymers andcatalysts, and products produced through formulation strategies. Many
examples illustrate the variety of isolated solutions and document thebarely recognized variety of new methods for the synthesis and analysis of almost any material. The Review ends with a summary of
success stories and statements on still-present problems and futuretasks.

1. Introduction
Our standard of living is closely associated with industrial
products based on functional materials (hard and soft matterwith a function). The worldwide demand for new or improved
materials is unlimited. The development and improvement ofmaterials have always been demanding, time-consuming, andcostly processes. High-throughput (HT) technologies, which
promise to speed up the discovery and development processes, have evolved rapidly during the last decade. The aim of
this Review is to present an overview of the current state ofthis field. Combinatorial and HT materials science is anapproach to the rapid discovery, study, and optimization of
new and known materials that combines rapid synthesis, highthroughput testing, and high-capacity information processing
to prepare, analyze, and interpret large numbers of diverse
material compositions.
The use of the terms “combinatorial” and “high-throughput” in the literature is still confusing. In an early approach,
IUPAC defined the terms used in combinatorial chemistry;[1]these definitions were guided by drug research and do notalways consider the problems associated with combinatorial
materials research. Sch-th has paid particular attention tothese two terms in a review article,[2] but we feel a need forfurther clarification. The term “combinatorial” should referto experiments in which groups or elements of different
materials or components of a recipe, such as solvents,
additives, or other components, are combined. Combinatorial
thus refers to a change in the nature of the parameters, not tothe change in the value of the parameters. The systematic
variation of given compositions, temperatures, pressures, orother single parameters to explore a wide parameter space is
not a combinatorial, but a high-throughput experiment.
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From the Contents
1. Introduction

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2. Computational Tools

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3. High-Throughput Syntheses

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4. High-Throughput Analysis andCharacterization
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5. HT Applications and Discoveries 6042
6. Promises, Problems, andSuccesses

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7. Conclusions

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Although “high-throughput” as a term only refers to thenumber of experiments and not to any intelligence associatedwith the experimental design and combinatorial strategies fordiscoveries, it also does not exclude those, and in thefollowing the term high-throughput will be used to describe
both combinatorial approaches and numeric variations. In
this Review we will frequently use the abbreviations: HT(high-throughput), HTT (high-throughput technology), HTE(high-throughput experimentation), and HTS (high-throughput screening).
High-throughput experiments have a long history; early
activities were exclusively manual operations, while the latest
developments have been technology driven. Some earlyexamples of high-throughput experimentation can be traced
back to Edison (1878) and Ciamician (1912; as outlined in areview by Schubert and co-workers)[3] as well as to thedevelopment of the catalyst for ammonia synthesis by
Mitasch at BASF in 1909. Despite these early activities,
HTE did not become a research subject for a long time. In
1970, Hanak successfully prepared and applied what we now
call composition spread or gradient libraries for research anddevelopment purposes at the laboratories of the firm RCA.
His work led to several new products, which successfully
entered the market. It also resulted in 28 publications and 12[*] Prof. Dr. W. F. Maier, Prof. Dr. K. St,we, Dipl.-Math. S. Sieg
Technische Chemie, Universit2t des Saarlandes
Geb2ude C4.2, 66123 Saarbr6cken (Germany)
Fax: (+ 49) 681–302–2343
E-mail: w.f.maier@mx.uni-saarland.de
Homepage: http://www.uni-saarland.de/fak8/maier
Supporting information for this article is available on the WWW
under http://www.angewandte.org or from the authors.

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patents, which were reviewed in detail recently.[4, 5] In one ofhis publications Hanak stated: “… the present approach to thesearch for new materials suffers from a chronic ailment, that ofhandling one sample at a time in the processes of synthesis,
analysis and testing of properties. It is an expensive and time
consuming approach, which prevents highly-trained personnel
from taking full advantage of its talents and keeps the tempo of
discovery of new materials at a low level.”[6] Despite thepotential importance and validity of this statement, the workof Hanak went unnoticed; his message was not appreciated at
the time. In the following years there was very little HTactivity of note. In 1980 the first article on parallel reactors forapplications in heterogeneous catalysis was published by the
Moulijn research group,[7] which was followed in 1986 by adetailed report on six parallel reactors for the testing ofheterogeneous catalysts.[8]In the early 1990s the bioorganic chemist Schultz assembled a team of physicists and materials scientists at theLawrence Berkely National Laboratory of UC Berkeley toapply combinatorial principles from drug development tomaterials research. The famous publication from 1995 concerning a search for superconductors from a materials librarymarked the actual start of combinatorial materials science asa discipline.[9] At that time scepticism was high and criticalvoices were common. There were those who were impressedand believed that this technology would rapidly solve many ofthe materials problems versus a critical majority afraid of thereplacement of intelligent science by sheer number crunching
and automation. However, the idea continued to spread andhigh-throughput experiments were started in many laboratories. In 1997 the newly formed company Symyx Technologies
published a library of over 25 000 distinct compounds, thereby
documenting the state of the art of this technique.[10] The firstextensive review appeared in 1999.[11] It covered 207 publications on a large variety of technological developments andprovided a critical, but positive view on a rapidly developing
field.
Today the initial euphoria has abated and combinatorial
materials science has matured. HTTs have been developed
for and applied to an ever increasing number of materials,
such as catalysts, electronic and magnetic materials, polymerbased materials, optical materials, biomaterials, paints, drug
formulations, detergents, cosmetics, glues, and others. Often,

the use of HTTs in the development or discovery of newmaterials is not even mentioned in the title of publications,abstract, or key words and is only found in the detailed
description or is completely omitted. It has become impossible to accurately identify all HTT activities. About 10 000
publications in which such methods have been applied canalready be found, which clearly exceeds the coverage of acomprehensive review. We have therefore restricted thisReview to selected publications and attempt to provide an
overview on the state of the art, the areas in which HTTs havealready made an impact, and the problems HTTs are stillfacing. Thus, HTTs related to drug discovery and homogeneous catalysis are largely excluded, because the two fields
have little in common with materials research. Combinatorial
drug discovery and development is based on molecular
structures and their variation, while in materials researchaccess to composition, processing parameters, and a large
variation of HT characterization methods have dominated thedevelopments in the field. Nevertheless, there are someoverlapping areas, such as the development of polymers for
drug transport and release, the acceleration of the formulations of drugs (galenics), and development of compatible
biomaterials, such as bone substitutes, which are associatedwith HTTs and combinatorial chemistry but these are also notcovered in this Review. Another rapidly developing field, theuse of HTTs in formulation developments, such as detergents,
paints, adhesives, and others, is confined to industrial
laboratories and rarely the subject of scientific reports.
High-throughput experiments in materials research aredefined by the types of materials of interest, and typicallyrequires the preparation of an array of materials (libraries), a
fast method to screen for properties (characterization andtesting), and suitable software for experimental control, data
storage, data analysis, and experimental design (computational tools).
A high-throughput experiment often starts with a first setof experiments that cover the parameter space selected. The
hits detected during the early stage of the study will usually
dominate the later experiments, that is, the search focuseswith time. There are two principally different scenarios forhigh-throughput experiments: discovery and optimization.
The discovery strategy (often termed primary screening) isapplied when totally new (alternative) materials are the target

Wilhelm F. Maier, born in 1949 in Kaufbeuren, is professor of Technical Chemistry at
Saarland University. After studying chemicalengineering at the Ohm-Polytechnic in
N.rnberg, he studied chemistry at the Philipps University in Marburg and received his
PhD with M. T. Reetz. After postdoctoral
research with P. von R. Schleyer at the University of Erlangen, he joined the Universityof California as Assistant Professor, and in1988 he became Professor for Technical
Chemistry at the University of Essen. In
1992 he joined the Max Planck Institut f.r
Kohlenforschung as head of a research group for heterogeneous catalysis
before taking up his current position in 2000.

Klaus St8we, born in 1962 in N.rnberg,
completed his PhD in chemistry in 1990
under the direction of H. P. Beck at theFriedrich-Alexander University in Erlangen.
After sabbaticals at the Max-Planck-Institut
f.r Festk8rperforschung in Stuttgart and thegroup of D. C. Johnson in Eugene, Oregon,in 1997 he completed his habilitation in
Saarbr.cken at the Institute for Inorganicand Analytical Chemistry, where he focusedon homonuclear interactions in selected lanthanide and actinide chalcogenides. In 2004
he joined the Technical Chemistry at Saarland University, where he is involved in high-throughput synthesis andcharacterization techniques. At the beginning of 2007 he was appointed
extraordinary professor.

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ChemieCombinatorial Materials Researchof the search (motivations may be: scientific curiosity, existingmaterials have little potential for further improvements, andno suitable materials are known). Discovery strategies aim at
sampling broad and highly diverse parameter spaces. Experimental conditions are compromised for throughput. The
disadvantage of this approach is that the number of mistakes
often increases (false positives and false negatives). Additional problems in the search for new or alternative materials
are search conditions, which are oriented at the conditions forthe best performance of existing materials, which give thelatter an advantage and contribute to false negatives and asignificant reduction in the number of hits. Inherent deviations between primary screening conditions and those of realapplications means that it is imperative to reproduce effective
materials (hits) resulting from primary screening data by
conventional synthesis and confirm the expected function by
conventional measurements. Hits, which are usually amplified
during a study, should always be validated under conventionalor realistic conditions. Optimization aims to accelerate thedevelopment of materials (often termed secondary screening). Here, relatively narrow, well-defined parameter spaces
around known materials are sampled at high speed underconditions as close to conventional experimentation as
possible. The known material to be optimized may be a hit
discovered by primary screening or it may be any known
material. Secondary screening describes experimental set-ups,
where the conditions used to measure the functional behaviorof materials is as close as possible to traditional measurement
procedures. Here, the compromise calls for high accuracy ofthe data, which is often paid for by a slowing down of theexperiment and a reduction in the number of samples studied
in the HT experiment. The goals are reliable trends andoptimized materials rather than hits and local optima.
There have been an impressive number of reviews on thissubject, which is typical for a rapidly developing new field.
Since many of these reviews are relevant for the HT topic aswell as related areas, a summary of selected review articles,
books, and special issues has been assembled. Their large
number and space limitations has necessitated the reviews
being summarized in the Supporting Information, which canbe accessed by the interested reader.

Simone Sieg, born in 1978 in Zweibr.cken,
completed her studies of mathematics witha minor in chemistry in 2003 at the University of Technology in Kaiserslautern, working
in the field of optimization and traffic planning (thesis title: “Algorithms for Multicovering Models with Application to Line Planning”). She then joined the team of W. F.
Maier to start her PhD thesis in the field ofheterogeneous catalysis and combinatorial
chemistry. Her current work focuses on themodeling of quantitative structure–activity
relationships for heterogeneous catalysts by
Kriging and multilevel B-Spline approaches.

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2. Computational Tools
A major bottleneck in high-throughput techniques is nolonger the development of experimental procedures for the
preparation and testing of materials, it is often data management and data analysis. Although the development of thecomputational methods has progressed rapidly in recent
years, many laboratories are hesitant to use these methods
because of a lack of manpower, complexity, and lack of accessto established software.

2.1. Design of Experiments (DoE)
The number of factors to consider increases dramaticallywith the desire to discover or develop new or better materials.
Elements of the periodic table, suitable precursors and theirconcentrations, functional group variations, sequence order of
the addition of reagents during the preparation, solvents,
additives, modifiers, treatment and reaction times, pretreatment, activation procedures, and microstructures are allparameters which affect the function of solids. Clearly,
systematic variation of all the potential parameters rapidly
approaches infinity. Although present high-throughput
experiments allow the acceleration of investigations by afactor of 10–100, this is by no means sufficient to support
mindless systematic screening. While DoE is still often
ignored in conventional research, it is essential for theplanning of high-thoughput experiments. Since high-throughput experiments are significantly more cost intensive thanconventional research, it is only successful if they deliver thepromised progress in a shorter time, which requires carefulplanning of the experimental parameter space. DoE can be
described as techniques that minimize experimental effort at
maximal information output. DoE has developed rapidly withthe onset of high-throughput experiments and a large variety
of methods have become available to serve the needs of HTE.
Since experiments are costly and time-consuming, intelligent selection of experiments has a long tradition. Statistical
DoE allows the effective determination of those parameters
as well as parameter interactions which have a main effect on
the property of interest. Systematic variations of up to fourparameters (so-called complete factorials or fractional factorials) can be carried out manually and have long become partof the education of experimental scientists (factorial design).
Ramos et al.[12] compared the performance of an inert
membrane reactor (IMR) for the oxidative dehydrogenationof propane to that of a conventional fixed-bed reactor withidentical catalysts and operating conditions. A factorial DoE
led to the maximum yield of propene. The statistical design ofexperiments has been used by Salim and co-workers[13] foranalyzing the precipitation and aging steps used during the
preparation of silica-supported nickel catalysts. A model
could be developed which describes the specific surface areaof the catalyst as a function of the rate of formation of thenickel silicate. With the help of this model, the preparative
conditions could be optimized to maximize the catalytic
activity. The effective application of such a systematic DoE tolarge sample numbers or parameter spaces has been the 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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objective of recent studies. A legitimate approach is the socalled full-grid search to sample the whole parameter space
defining individual step sizes for each of the parametersconsidered. In this approach, all the samples have to bescreened for their functional performance to obtain insight
into the impact each factor has on the property of interest. A
clear drawback is the large number of experiments to be
carried out, which rapidly increases with the number of
selected factors. Castillo et al.[14] presented the use of a splitplot experimental design, developed for high-throughput
studies of catalysts (see Figure 2 in Ref. [14]), but demonstrated this with only two catalysts. Here two levels of theparameters temperature (T) and pressure (p) were combinedwith the variation of two catalysts at two concentrations. With
each experiment carried out twice for statistical reasons, thisresulted in 32 parallel experiments. Four modules out of eightallow variation of temperature and pressure. This design canbe increased to cover any number of catalysts. Furthermore,
the study focused on the unique error structure of these
designs. The approach has been elaborated upon during a casestudy at Dow Chemical Company.[15] A good overview on
experimental design approaches for HTE can also be found in
Ref. [16], while examples of split-plot designs realized inindustry can be found in Refs. [17–19]. A factorial design was
selected by Corma et al. to study experimental variations inzeolite synthesis (Figure 1). A Pareto analysis was applied tointerpret and quantify the factor effects. The new zeolite ITQ30 was discovered by this technique.[20]Figure 1. Evolution of zeolite ITQ-30; crystallinity is shown as afunction of synthesis conditions on varying the molar ratios of Si/Ge
and H2O/(Si+Ge) (see Figure 5 in Ref. [20]).

With the development of computation, complex DoEs
became common, and now standard software can be used toplan and evaluate effective and statistically meaningful
optimizations. Unfortunately, in most cases the use offactorial design for simultaneous optimization is limited to a
maximum of five parameters at two levels. One approach to
reduce the parameter space is by intuition or knowledge
available from prior experimentation and research. Anotheris the use of a “primary screening” strategy, in which hundreds
or thousands of potential samples are prescreened for the

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property of interest. Primary screening is therefore a means to
reduce the parameter space for a final optimization.
Another way to limit the parameter space is by the use ofstructure–activity relationships, which turn random searches
into well-structured searches. Quantitative structure–activity
relationships (QSARs) are important aspects of modern drug
development, which provide descriptors that link molecular
structure with pharmacological effects. Structural diversity isan essential question of concern in the search for new drugs.
Much effort has been devoted to the question of how todesign a structurally very diverse library for general purpose
screening,[21–25] and many methods have been proposed to
optimize experimental designs.[26, 27] For example, scientists
rely on the “similar property principle”, which means thatmolecules with similar structures or with similar functionalgroups will show similar physicochemical and biologicalproperties.[28, 29] This approach is reasonable for drug development, and very effective codes or algorithms have beendeveloped to represent molecular structures for rapid computation. “Descriptors” (for example, dipole moment, distance between selected functional groups, etc.) are identified
which correlate molecular structure with specific drug function. Algorithms can then be applied to sort molecules into
different classes depending on the chosen similarity measure(for example, Euclidian distance, Tanimoto coefficient, etc.).
The design of a screening library for primary screening
usually selects only a few representatives from each class toachieve the largest diversity with the least possible effort.
Unfortunately, most materials cannot be represented byexact structures, and functional solids do not lend themselves
easily to simple representation by a computer. The muchhigher complexity of materials and the diverse preparation
methods of such functional solids do not allow such developments to be directly transferred from drug research tomaterials research. Nevertheless, the mathematical techniques used can still be applied. In materials research,quantitative structure–property relationships (QSPRs)[30]
andquantitative
composition–activity
relationships(QCARs)[31] have been developed, which attempt to link
the materials function with structure or chemical composition.
Reynolds reported that the concepts of molecular diversity and similarity that have shown to be useful in the field of
biologically active molecules can also be applied successfully
to the design of synthetic polymers.[32] A first serious effort toextend the descriptor approach to heterogeneous catalysts
was recently published by the research groups of Sch-th andMirodatos.[33–35] They described a search for descriptors basedon data obtained by testing a library of 467 catalysts for theoxidation of propene. Experimental data were supplemented
by physical data of the elements and phases. Principal
component analysis (PCA) and clustering methods wereapplied to identify characteristic features correlating withcatalysis (Figure 2). The clusters allowed the catalysts to begrouped into classes, but descriptor identification turned out
to be difficult.
The lack of correlation between catalytic performanceand composition is understandable since catalyst preparation
varied greatly. The best descriptors identified were atomic

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ChemieCombinatorial Materials Researchto establish a straight-forward correspondence between the
optimization paths followed by the algorithm and thechannels of a high-throughput reactor in which the proposed
new materials are to be tested and validated. 2) Constructionof an analytically expressible function using the available datasuch that the gradient and second-order derivatives can be
estimated with sufficient precision. Standard optimization
methods can then be applied. Thus, methods to approximate
very general functions are needed. Various classes of neuralnetworks seem to yield the most promising results for thisapproach. Applications in materials research are nearly all
based on a particular kind of neural network, the so-called
multiplayer perception (see for example, Ref. [37] andreferences therein).
Figure 2. Number of catalysts n in each class for k-means analysis
based on eight principal components that characterize the catalytic
performance of 467 very different materials for propene oxidation(from Ref. [35]). Class 1: low conversion, high selectivity for CO2 ;class 2: medium conversion, high selectivity for CO2 ; class 3: lowconversion, high selectivity for CO, partial oxidation products; class 4:
low selectivity for CO2, CO, and hydrocarbons; class 5: high conversion, high selectivity for CO2.

radius, electron affinity, and free enthalpy of the most stable
oxides. The authors concluded that a broader database andmore comparable data were required for this type of analysis.
Corma et al. reported the successful unsupervised construction of QSPR models from spectra characterization descriptors and synthesis descriptors for epoxidation catalysts basedon Ti silicates.[36]Searching for an optimal composition or a synthesis routeto a material is a multidimensional optimization problem.
Since many factors influence the properties of materials (forexample, chemical composition, synthesis route, pore structure, surface properties, etc.), 20–30 descriptors are notexceptional. At the start, the functions to be optimized(objective functions) that describe the relationship between aperformance measure (for example, activity, durability, hardness, flexibility, conductivity, etc.) of a material and its
composition or certain other descriptors are unknown. To
date, no theory exists that helps this relationship to be
described in an analytical way. Only discrete values of theseunderlying functions are available from experimental measurements, and therefore standard mathematical optimization
approaches cannot be used directly. In most cases, analytic
expressibility is an important prerequisite for the applicationof efficient optimization methods such as gradient methods,
conjugate gradient methods, or methods that also needsecond-order derivatives (for example, Gauss–Newton, Levenberg–Marquardt).
To solve this problem for applications in materials
research, Holena[37] proposed two possible solutions:
1) Employing optimization methods that do not require
gradient or second-order derivatives of the optimized function. These can be deterministic, such as the simplex
method,[38] stochastic, such as simulated annealing,[39–41] orgenetic algorithms (GAs). Holena remarked that GAs havebecome very attractive for catalysis research, since they seem
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2.2. Genetic Algorithms and Evolutionary Strategies
GAs are ideally suited for high-throughput experiments
since they require a population of individual samples and thus
rely on high-throughput. GAs have been applied to materials
research for nearly ten years. The history of GAs goes back to
the 1960s when Holland started his work in this field and thefundamental concepts and ideas were published in 1975.[42]De Jong published the first application (parameter optimization) in the same year.[43] It was not until 10 years later that
this new approach to solve complex practical problems
became more and more accepted within the community. In
1989, Goldbergs book Genetic Algorithms in Search, Optimization and Machine Learning[44] introduced the theory andapplication of genetic algorithms to a wide audience. In
general, GAs are a class of nonlinear, adaptive, and often
heuristic methods for solving optimization and search problems. As in nature, genetic algorithms are often used as socalled “black-box” functions. In nature, populations evolve
over many generations following the principles of natural
selection and the “survival of the fittest”. By copying andimitating these principles from nature, genetic algorithms cangenerate artificial populations to undergo an evolution thatapproaches an optimal solution of a predefined problem. In
contrast to other methods, a GA need not to be trained anddoes not need nor collect information about gradients orother specific information on the problem to be solved, andtheoretically there is no limit to the number of parameters or
algorithms that can be applied. This may be the reason why
GAs are often applied to fields that are not well understoodor where a complete modeling is not possible because ofmathematical or computational restrictions or efforts.
A good overview on genetic algorithms and neuralnetworks and their use in heterogeneous catalysis has been
given by Holena.[37] The author lists the most relevant
practical applications of both techniques and the reader isalso referred to references in that review. Figure 3 illustrates
the idea and procedure of a genetic algorithm.
The aim of applying a GA is to improve a starting solution(library of individuals) for a given problem within each
iteration. The individuals are evaluated by the fitness function(desired property). The best individuals are used to produce
an offspring generation with the help of selected algorithms,

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software called OptiCat that enables the user to constructcustom-made workflows. They tested their approaches on a
virtual benchmark test and on experimental response surfaces
obtained from HT screening. The research group also studied
the effects of genetic algorithm parameters on the optimization of heterogeneous catalysts, especially the influence of
population sizes on the robustness and convergence speed.[54]Corma et al.[55] used a GA to optimize isomerization catalysts
for light paraffins. The successful combination of GA andDoE led to the discovery of new paraffin isomerization
catalysts (Figure 4).[56]Figure 3. Flow scheme of a genetic algorithm.

such as mutation, cross-over, or recombination operations.
The offspring generation is then evaluated and the process
starts again. Genetic algorithms for materials research can be
simply described as follows: the best members of the starting
library with respect to the fitness function are selected as hits.
From these hits (parents), the next library (offspring generation) is formed. It is up to the researcher to develop suitablealgorithms that form an offspring generation which improves
upon the parents. Such algorithms may exchange the elementsof the parents, exchange their molar contents, or introduce
random dopant elements. As long as there is an improvementin the offspring generations, the evolution towards the desired
function is working. If there is no improvement in early
offspring generations, the algorithms chosen may be poor. If
this happens in later generations, an optimum may have beenreached. Contrary to most other optimization procedures,
GAs are not limited by the boundaries of the starting libraryor starting set, and can thus escape local maxima or minima
and enter new parameter spaces by itself. It is interesting thatin the application of a GA, randomness of mutations plays animportant role in obtaining a new solution. Furthermore,genetic algorithms are nondeterministic methods. It is neither
possible to predict the number of generations the algorithm
will produce until a “best” solution is reached, nor cananything be said about the solution itself.
Although there have already been many reports on theuse of GAs in materials research, there are as many different
algorithms. The choice of algorithms and the strategy applied
to generate the offspring generations characterize each GA
and are also responsible for success or failure. One application of genetic algorithms is for the design of diverse
combinatorial libraries for high-throughput screening.[45–47]
The first use of an evolutionary strategy for searching the
optimal composition of catalytic materials was described by
Baerns and co-workers.[37, 48–51] Another evolutionary optimization approach combined with high-throughput synthesis
and screening has been applied to the discovery of new
catalysts for the oxidative dehydrogenation of ethane toethylene.[52] Mirodatos and co-workers[53, 54] used genetic
algorithms in several ways: they developed a GA platform

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Figure 4. Catalyst development for pentane isomerization with the ten
best ranked materials from three generations through the combinationof GA with DoE (from Ref. [56]). Y = n-pentane conversion.

In a theoretical study, a combination of density functional
theory (DFT) and genetic algorithms has been applied by
Nørskov and co-workers to search for new stable alloys
consisting of four components.[57] The research group identified several new alloys among the 192 016 possible facecentered cubic (fcc) and body-centered cubic (bcc) alloys thatcan be constructed out of 32 different metals. The method has
now been extended to the discovery of electrocatalytic
materials for hydrogen evolution. Not only is the theoretical
approach remarkable, but the authors also did not stop withthe prediction but verified the validity of their study withexperimental data. Starting with a screening for catalyst
activity, the selection was refined by testing (theoretically) forsegregation, island formation, and dissolution of the potential
alloys. From a starting set of over 700 binary transition-metalalloys BiPt was identified as the most promising. It was
synthesized and tested experimentally and, in agreement withthe theoretical prediction, its hydrogen evolution activity wasbetter than that of pure Pt.[58] The application of genetic
algorithms to polymer design is illustrated in Ref. [59]. Giroet al. demonstrated how the application of a genetic algorithm
can help to accelerate the development of new conducting
polymer materials (binary up to quinternary disorderedpolymeric alloys).[60–62]
The evolutionary strategies (ESs) developed by Rechenberg are related to GAs.[63] Evolutionary strategies allow theuse of continuously variable parameters, such as elemental
composition, and have been applied to a large variety ofproblems, such as the design of an optimal cross-section for a 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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hypersound nozzle.[64] Evolutionary strategies, combined with
GAs were used by Kirsten and Maier in a search for newoxidation catalysts.[65]2.3. Artifical Neural Networks
Artificial neural networks (ANNs) are computing systems
that are based on the concepts of neurons in biology. A
neuron can be seen as an elementary signal processing unitthat is either connected to other neurons or to the environment such that the transmission of signals can be realized.
Input neurons receive signals from the environment, while
output neurons can send signals to the environment. The
neurons in between are called hidden neurons. The architecture of the networks gives the structure of the connections
between input, output, and hidden neurons. The mostimportant class of networks for applications are so-called
feed-forward networks. Here, the set of neurons is partitioned
into several layers such that signal transmission between
neurons is only possible from a lower layer to a higher layer.
So-called multilayer perceptrons are the most common
networks of the feed-forward kind and, according toRef. [37], all neural networks applied so far in materials
research are of this type.[66–71] Figure 5 illustrates an example
of a multilayer perceptron.

Figure 5. Example of a multilayer perceptron.

Multilayer perceptrons with applications in catalysis aredescribed in detail in Ref. [66]. The approximation ofcomplicated and general dependencies is one of the mostremarkable features of feed-forward networks. These networks have been used to approximate relationships between
catalytic performance and chemical composition, physicalproperties, and reaction conditions.[66–72]
Neural networks need to be trained first on a selected setof training data. Theoretically, there is no limitation to thenumber of parameters or connectivities. A main problem withneural networks is that the information used for learning does
not extrapolate reliably to trained dependencies outside of
the training data. It might happen that the approximation
perfectly fits the training data and also the noise included. In
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this case, points outside the training set are quite irrelevant tothe approximated dependence. This phenomenon is called“overfitting” and can be recognized by using a new data set(test data) that also possesses the approximated dependence
but has not been used for the learning process. A detailed
treatment of artificial neural networks can be found in
Ref. [73, 74] and a detailed overview on the application ofneural networks in chemistry can be found in the citedbooks.[75, 76] Within the last decade a review[77] and a book[78]have been published that cover the applications of neuralnetworks in chemistry and science. Additional applications ofANNs to catalytic problems are described in Section 2.4.

2.4. Combination of GAs and ANNs
The search for the best material within a predefinedparameter space is approached from different directions by
GAs and ANNs. The combination of both methods has led topositive effects being noted, such as remarkable acceleration.
A GA has been used to train an ANN in catalysis forparameter tuning of a three-way catalytic converter.[79] This
strategy of integrating neural networks in GAs has been used
to find the optimal composition of a catalyst for theammoxidation of propane.[80] In this case, no experiments
were performed and the network was trained with literaturedata. The same strategy has been used to find the optimal
Cu:Zn:Al ratio in mixed oxide catalysts for the synthesis ofmethanol from syngas.[81] The process variables of the TS-1catalyzed hydroxylation of benzene have been optimized by asimilar strategy, and the predicted process variables wereexperimentally verified.[82]Another approach is to use ANNs to simulate experimental feedback concerning the performance of proposed
catalysts selected by a GA. The GA is run several times using
different population sizes to study the influence of population
size on the convergence behavior and decrease of population
diversity. This approach allows an intensive study of theadjustable parameters in the GA and their influence on
convergence speed and decrease in diversification. Parameterstudies for GA have been described by Mirodatos and coworkers[54] as well as by Sundaram and Venkatasubramanian.[59] Corma et al. described several applications of ANNsand GAs for modeling the kinetics of catalytic reactions.[83, 84]
ANNs have been used to study the behavior of catalysts under
different reaction conditions for the isomerization of noctane. Based on the reactor conditions, the networks havebeen trained to predict the composition of new catalysts forthe oxidative dehydrogenation of ethane.[85] Larachi[86] usedmodeling with ANNs to describe the coke burn-off on MnO2/
CeO2 oxidation catalysts under wet conditions. Huang et al.[87]proposed another method for catalyst design based on the
combination of artificial neural networks and genetic algorithms. They trained an ANN to model the relationshipbetween catalyst components and catalytic performance. To
enhance the efficiency of the designing process, a new hybrid
genetic algorithm was developed to solve the global optimization problem. With this method, a multicomponent catalyst
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exceeded the results previously reported for other catalysts.
Mirodatos and co-workers[88] used ANNs to predict theperformances of catalysts for the water-gas-shift reaction
and also as a classification tool within an evolutionary
approach (Figure 6). Roy et al. presented an approach ofcombining neural networks, genetic algorithms, and Markov
chains to simulate polymer blends and predict the miscibilityof unknown polymer systems.[89] Other applications also
include the modeling of chemical reactors,[90] studies on sootformation in hydrocarbon flames,[91] and predictions ofcatalyst deactivation.[92]Figure 6. Scheme of the methodology proposed by Mirodatos and coworkers for boosting primary screening in heterogeneous catalysis.[88] .

Another approach to multiparameter modeling andoptimization is the holographic research strategy (HRS)
developed by Margitfalvi and co-workers. The authors[93]compared the performance of a genetic algorithm approachto the HRS to find an optimal material composition in a
multidimensional search space. Similar to GAs, HRSs can beused for library design, predictions in materials synthesis, andfunctional optimization. In elaborate studies, an HRS wascombined with an ANN and compared to a GA in catalyst
optimization for methane combustion at 350 8C, propane
combustion at 150 8C, and oxidative coupling of methane at
800 8C. Catalysts composed of Pt, Pd, and Au on mixed oxide
supports of Ce, Co, Zr, Cr, La, and Cu were used for the firsttwo reactions and Na, S, W, P, Zr, and Mn on SiO2 for the
coupling reaction.[93–95] In all cases, very similar optimal
catalysts were obtained, while the HRS is claimed to require
only half the samples to converge to an optimum. HRS has so
far only been used by the Margitfalvi research group. Support
vector machines (SVMs) have been used by Baumes et al.[96]for the predictive modeling of heterogeneous catalysts for theisomerization of hydrocarbons and the epoxidation of olefins.
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identify the correct model structure from the data available.
Data sets therefore include a training data set and test
samples to evaluate the accuracy of the derived models. SVMs
have been applied to olefin epoxidation and isomerization
catalysts.

2.5. Data Mining/Knowledge Discovery/Data Bases
The use of high-throughput experimentation generates
lots of data and information within short time periods. These
data are just information and only proper data analysis canturn the data into knowledge. The extraction of knowledge(knowledge discovery, KD) out of large data sets is not atrivial task and misleading conclusions readily result if datainterpretation is not accompanied by proper statisticalanalysis.
A large variety of mathematical tools are available fordata analysis. Important data-mining techniques used forknowledge discovery in large data sets are principal component analysis (PCA), clustering techniques (for example,
hierarchical clustering, k-means clustering, etc.), ANNs, GAs,
classification methods, regression methods, kernel methods(for example, SVM), decision trees, and self-organizing maps.
Nearly all of these techniques require profound statistical andmathematical knowledge for proper application. For adetailed description of these data-mining tools we refer toadequate handbooks of multivariate statistics,[97] machinelearning,[98] and data mining itself.[99]Many new approaches have been published which combine HTE and mathematical data-mining techniques to speed
up the development of new materials. Caruthers et al.[100]presented a new framework for designing catalysts that
integrates HTE with computer-aided extraction of knowl
edge. The current state of HTE is described and its speed andaccuracy was illustrated using a FTIR imaging system for CO
oxidation over metals. Furthermore, the authors show theperformance of a “knowledge extraction (KE) engine” (withrespect to robustness, automated model refinement, etc.) andits possibility to predict optimal catalyst composition using aforward and inverse model (Figure 7).
A hybrid evolutionary framework was also used thatcombines ANNs and GAs to solve the forward and inverse
problem for the development of industrial products and which
benefits from this synergistic approach.[101] BMcker et al.[102]Figure 7. Schematic representation of the forward and inverse problem
in materials design (from Ref. [100]).

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published a review on data-mining approaches in HTS. The
most frequently applied techniques are described, including
kernel-based machine-learning tools. This review also provides a large bibliography for data mining in HTE, including
textbooks that provide theoretical background. Ohrenberg
et al.[103] have reported how data mining and evolutionary
optimization can be used to increase the efficiency of material
searches in high-dimensional parameter spaces. The authors
used different data-mining techniques, such as clustering,correlation analysis, and decision trees, in combination withevolutionary strategies for materials optimization. As themost important result, the authors stress the importance ofcombining different techniques to gain significant advances inknowledge. The application of data-mining techniques inpolymer science has been reported by Adams and Schubert.[104, 105] The authors give an overview on the developmentof a detailed data-management system to handle highthroughput screening data and to derive knowledge out ofthese experiments. As a main focus of their work, they refer toan informatics infrastructure that was developed to support
the experimental work and especially the analysis of screening data. Another application of a clustering method(sequential superparamagnetic clustering) has been appliedby Ott et al.[106] to cluster chemical structures. The authors
conclude that sequential clustering can also be of particularinterest to chemical applications, such as combinatorial
library design and hits analysis in HTS data. Saupe
et al.[107, 108] illustrated how the use of appropriate softwaretools in every single step of the HTE process helps to increase
the speed of knowledge discovery. A modular approach to an
HTE platform was presented which satisfies the required
flexibility for the changing requirements of research. Farrusseng et al.[109] pointed out the main issues involved in data
management for the discovery and development in heterogeneous catalysis, that is, for example, automated dataacquisition, data storage, and data analysis together with theapplication of data-mining techniques. They also provide amethodology for facilitating data management for heterogeneous catalysis. The authors also presented a database linked
to a powerful algorithm for the iterative discovery andoptimization of catalytic samples. A more theoretical
approach to data mining has been published by Clercet al.[110] The authors show how optimization problems canbe solved by hybridizing a classical GA with a KD system (forexample, a learning process using k nearest neighbors) thatextracts information from a database. A schematic flow chart
is shown in Figure 8. This approach has been applied to a
problem in the field of heterogeneous catalysis in which
different possibilities for the hybridization of the GA with the
KD according to robustness and optimization speed werecompared.
Rajan and co-workers[111–114] applied data-mining methods, such as PCA, and predictive methods, such as partial leastsquares (PLS) to certain fields of materials science (zeolites,
semiconductors, etc.). They connected conventional materials
databases with experimental data sets in searches forcorrelations and patterns. One further possibility to design
combinatorial libraries is by integrating data-mining techniques with physically robust multivariate data. In doing so,
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Figure 8. Hybrid GA with a KD System. The hatched blocks are theelements of the KD engine, the remainder are traditional elements of
the GA (from Ref. [110]).

large data sets can be generated from relatively small
amounts of experimentally and theoretically based information. During this process a strategical selection of appropriate
physical parameters is necessary that can be analyzed in a
multivariate manner. This “virtual” approach to combinatorial experimentation has been applied by several researchgroups. For example, Suh and Rajan[115] predicted the bandgaps and lattice parameters of nearly 200 stoichiometries of
new and yet to be synthesized semiconductors with chalcopyrite structure and tested the robustness of this approach bycomparison with predictions of band gaps from theoreticalstudies on selected quaternary semiconductors covering a
range of compositions. They applied the multivariate PLS
technique to a training set of selected data from the literature.
PLS has distinct advantages over classical multiple regression
and principal component regression approaches. By using the
PLS coefficients they completed their analysis of property
prediction for over 200 compounds based on their initial
combinatorial data input for training. In this way theypresented an approach to develop combinatorial libraries,
which can serve as an effective screening tool to guidecombinatorial experimentation. Kubo, Miyamoto et al.[116]applied a combinatorial, computational-chemistry approach
mainly based on static first-principles calculations to various
catalyst and material systems. By determination of theformation energies of intermediates for a number of metal
catalysts, such as Cu, Ru, Rh, Pd, Ag, Re, Os, Pt, and Au—in
neutral as well as cationic form—by DFT calculations, they
investigated the design of catalysts for the synthesis ofmethanol. Their calculations confirmed the Cu+ ion as theactive center in industrial Cu/ZnO/Al2O3 catalysts andpredicted Ag+ and Au+ to be potential candidates for highly
active catalysts for methanol synthesis. In an analogous way,
they studied precious-metal catalysts for the deNOx process
by investigating the adsorption properties of small metalclusters for NO. It was demonstrated that the energeticallymost stable adsorption state of NO is on an Ir cluster,
independent of both the structure and number of atoms

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within the metal atom cluster.[117] Combinatorial computational chemistry (CCC) has also been used to find materials
with novel properties in lithium battery applications. DFT
calculations were performed on periodic models of LiMO2(M = 3d transition metal) with layered rocksalt superstructures to investigate the structural properties of LiCoO2,
LiNiO2, and doped LiNiO2. This study revealed that the poor
cyclic charge-discharge reversibility of LiNiO2 resulted fromthe large change in the structure because of the difference in
the ionic radii of Ni3+ and Ni4+.[118] Since Co3+ and Co4+ ionsgive almost the same metal–oxygen distances, the use of Co asa dopant reduces the structural changes of LiNiO2 andimproves the cycling stability of the material. This approach
was recently extended from static first-principles calculations
to high-speed simulations of chemical reaction dynamics
based on quantum-chemical molecular dynamics (MD)calculations to realize an even more effective and efficient
CCC screening. Improving the conventional performance
speed by a factor of 5000 resulted in sufficient computational
capacity to perform a high-throughput screening. The applicability and effectiveness of the method was demonstrated byinvestigating the atomistic mechanism of the methanol synthesis with the Cu/ZnO catalyst system at reaction temperatures and comparing it with the results of regular firstprinciples MD calculations; the HT screening potential of themethod has still to be demonstrated by the authors.[119]A critical issue remaining in high-throughput technology
is the actual databases. Only limited information is available
about software or database solutions in industry, academia,
and research institutes. The lack of simple and versatile databases for materials research means that Microsoft Excel
sheets are still used for data collection in many laboratories.
There have been several reports on the development of
databases for combinatorial and high-throughput materials
science. One example is the work by Frantzen, Sander
et al.,[120] who developed a project-oriented Microsoft
Access based database for data storage, visualization, anddata mining in the search for new sensor materials. The
concept satisfies the essential needs of high data compatibility
and versatility together with convenient data import andexport. Potyrailo and co-workers[121–123] presented a centralized data-management and storage system for their work onorganic polymer and hybrid coatings. One important fact of
their approach is the sharing of information from synthesis,
testing, and evaluation by the database. Another example of adata-management system developed in a research institute is
the StoCat database of Mirodatos and co-workers[109] for theacquisition of laboratory and experimental data for HTE.
Commercial data bases are provided by high-throughput
companies, such as Symyx Technologies, hte-AG, and Avantium.
A rather simple aspect of knowledge discovery is the
mapping of any function against chemical composition, which
was often studied in the early high-throughput experiments.
This approach can be considered as a form of QCAR. Basic
research in materials science and heterogeneous catalysis
currently focuses on microstructure, oxidation states, surface
polarity, pore size, porosity, or phases, but rarely on chemicalcomposition. Through the search for defined phases respon-

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sible for performance, composition has been dominated bystoichiometry. It is not clear, whether there is a correlation
between composition and catalytic performance. There is a
wealth of catalytic literature based on amorphous systems,
especially mixed oxides as well as all the mesoporous
materials, whose pore walls are consistently amorphous. The
search for defined phases still continues, but few studies arebeing carried out by the catalytic community in regard to theidentification of active sites in amorphous catalysts. The
reason is clear—there are few tools to solve such a task.
Therefore, amorphous materials are accepted as catalysts, but
not understood. However, such amorphous materials, to afirst approximation, are free of stoichiometric restrictions andallow the sampling of continuous composition spaces. This isof fundamental importance for our desire to understandcatalysis, since the chemical composition of catalysts can now
be treated by continuous variables, and the catalytic performance can be mapped against chemical composition.
The first direct mapping of catalytic performance against
chemical composition to our knowledge was reported in 1999
by the scientists at Symyx in their search for new catalysts forthe oxidative dehydrogenation of ethane.[124] The map of thephase space (Figure 9 a), which consists as a test on the
reproducibility of two in the compositional range identicaltriangles, shows that the catalytic activity of these mixed
oxides varies smoothly with composition and that there is adistinct maximum in the catalytic performance.
Paul et al. found in a study on the direct oxidation of
isobutane with air on mixed oxide catalysts[125] that theformation of methacrolein is highest at a low V content (2 %)and with about 10 % Mo in Sb oxide (Figure 9 b), while theparallel formation of isobutene is favored by the Mo-poorcompositions with higher levels of V in the Sb oxide(Figure 9 c). The undesired combustion to CO2 is strongly
favored by compositions with low levels of Sb and high levelsof V relative to Mo (Figure 9 d). This is an ideal example ofcatalytic performance, since here the selectivity can be tuned
directly by the chemical composition of the catalyst.
Such a significant correlation of the catalytic selectivity
with chemical composition is by no means general. In a
related study with mixed oxides of V, Bi, and Sb, the activity
for the formation of methacroleine, isobutene, and CO2 were
found to be located in the same range of composition.[126]The mapping of the function of a material against
composition has not yet become routine, but it has become
increasingly common. In a study on a range of compositions
prepared by co-deposition of thin films, the dielectric constantand stored charge density (Figure 10), for example, showed asmooth dependence on chemical composition.[127] The mapping of the catalytic activity–composition relationships for thedehydrogenation of ethane with Mo-Nb-V mixed oxides
obtained by wafer technology compares very well withliterature data obtained by traditional methods.[128]The mapping of functions against chemical composition isby no means trivial. Materials functions such as catalytic
selectivity or piezoelectric performance are critically dependent on the exact preparation conditions. To map a function
against composition, therefore requires that all the materials
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Figure 9. a) Mapping of the catalytic activity for the oxidative dehydrogenation of ethane against composition (from Ref. [124]); b–d): Dependenceof the relative activity of the oxidation of isobutane to methacrolein (b), isobutene (c), and CO2 (d) with air on the chemical composition of themixed oxide catalysts indicated (from Ref. [125]).

Figure 10. Stored charge densitiy of potential capacitors mapped
against chemical composition (from Ref. [127])

procedures or recipes. This is relatively trivial in the cases ofthin-film materials prepared by PVD, CVD, and related
methods. It is not trivial, however, if the materials areprepared by liquid-phase or solid-phase procedures.
In comparison to conventional preparation and testing ofindividual samples, the preparation and testing of whole
libraries has several advantages. All materials are tested at thesame time and under identical conditions. This allows for the
first time to reliably compare the performance of all thesamples in a library. The use of an internal reference sample
allows standardization of the relative performance data. The
use of synthesis robots and computer-controlled synthesis andtesting strongly increases the reproducibility of the data
accumulated. Furthermore, if suitable data bases are used fordata storage, and the mining and library preparation are
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automated, libraries can be reproduced easily. Outliers areeasily recognized if their immediate neighbors show significantly different functional activity. If the materials of acomposition library are statistically and randomly distributed
over the library or array and subsequently ordered according
to composition, a continuous smooth activity map is evident
for comparable performance across the library.
Data sets obtained experimentally by the mapping ofparameter spaces also provide the basis for the directmodeling of such QCARs.[129] Sieg et al. showed withquaternary composition spaces that the proper mathematicalmodeling of such relationships can be accomplished readily
with the help of SVMs, multilevel B-splines, or Kriging(Figure 11).[130]There have been significant developments in the use of IT
tools for HTE. It has also been widely demonstrated that thehuge data sets produced by HTE can be handled properly andbeneficially by the IT tools already available. Unfortunately,
the field has turned into a maze of individual solutions, andmany laboratories are hesitant to implement the necessary
information technology. Compatible data bases, the mostessential prerequisites for a future data sharing and moreadvanced discovery of knowledge, have not yet entered manylaboratories.

3. High-Throughput Syntheses
An ever increasing number of synthesis and screening
methods have been developed in the field of HT materials
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Figure 11. Tetrahedral visualization of the dependence of the relative
activity for the oxidation of propene at 350 8C on the composition ofquarternary mixed oxide catalysts (from Ref. [130]).

believed to be limited to the most simple materials, library
preparation with complex materials, such as block copolymers, zeolites, supported catalysts, detergent or adhesive
formulations, magnetic resists, and other complex materials,
now dominates the field. Mapping, screening, and optimization experiments have different primary goals and therefore
make different requirements in the planning of an experiment.[131] There is a large variety of preparation methods formaterials. Many synthesis methods are not suitable for HTE,
and alternative, HTE-suitable synthesis procedures need to
be developed.

3.1. Thin-Film and Related Techniques
The so-called “diffusion-multiple approach” enables thegeneration of a large number of phases and compositions forthe efficient mapping of phase diagrams, phase properties,
and kinetics by the creation of composition gradients andintermetallic phases through the long-term annealing ofjunctions of three or more phases/alloys.[132] Not only phase
diagrams, but also diffusion coefficients, precipitation kinetics, as well as solution-strengthening and precipitationstrengthening effects can be evaluated by this method. The
method is based on the fundamental solid-state principle ofcounterdiffusion of the constitutional elements in diffusion
couples made by placing two blocks of dissimilar materials in
intimate contact with each other to give a well-defined andplanar interface. The length scale of the product layers usuallyinvestigated by bulk diffusion couples is on the order ofmicrometers. According to the rules of Walser and BenP, thefirst compound nucleated in planar binary reaction couples is
the most stable congruently melting compound adjacent to
the lowest temperature eutectic on the bulk equilibriumphase diagram.[133] After nucleation, this first phase grows andthus two new diffusion couples (that of the crystallizing binary
compound with either of the two constitutional elements) are
generated. Consequently, as products of long reaction times,
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phase diagram will nucleate and grow. Zhao et al.[132, 134, 135]
extended this approach to more than two elements by using
an assembly of three or more different metal blocks inintimate interfacial contact and subjecting this to hightemperature to allow thermal interdiffusion to create solidsolution compositions and intermetallic compounds. In theirinvestigations, the resulting library of intermetallic compounds was mapped for thermal conductivity with micrometer-scale resolution by time-domain thermoreflectancewith a femtosecond pulsed laser (a method developed
recently)[136] and also for YoungRs modulus by nanoindentation techniques. An example of the diffusion multiple
mapping of the phase diagrams in the Pd-Pt-Rh-Ru-Cr
system is shown in Figure 12.
The idea of synthesizing samples that show continuous
phase diagrams (CPDs) or continuous composition spreads(CCSs) is rather widespread within the “thin-film community”, where initial work using composition-spread thin films
dates back to the mid-1960s. A detailed historical introduction to composition-spread approaches has been given by
van Dover and Schneemeyer.[127] Here, we only mention theearly work of Hanak, who in 1970 published a prescientdeclaration of the general potential of these high-throughput
synthesis and evaluation techniques for materials investigations (entitled as “multisample concept”) and provided
details and examples for the particular case of multitarget
sputtering.[6] The unique feature of these approaches is asynthetic technique in which material is deposited on asubstrate simultaneously from two or more sources that are
spatially separated and chemically different. In this way thinfilms are produced with an inherent composition gradient andintimate mixing of the constituents. As with the diffusion
multiple approach mentioned above, complete multinary
phase diagrams can be prepared in a single experiment.
Hanak[6] already recognized the persistent problem of determining the film compositions efficiently, and identified theneed for rapid automated testing to complement the parallel
synthesis technique.
Two possibilities in principle exist for preparing continuous composition spreads: cosputtering and coevaporation.
The critical challenge with both techniques is the ability tocreate a set of samples with the same properties when
prepared under identical conditions, that is, the reproducibility of the synthesis, in situations where variations between
runs could confound systematic trends. Even the smallest
composition deviations arising from flux variations between
different runs may alter the physical properties of materials
significantly, as reported by Hanak.[6] Coevaporation is amuch more challenging technique to implement successfully
than cosputtering, since the evaporation rates of conventional
evaporation sources are sensitive to the conditions of theevaporant source and depend exponentially on the input
power, thus making it very difficult to maintain constantdeposition rates during a number of experiments. For
materials with low evaporation temperatures which can bedeposited by effusion cells, as in molecular beam epitaxy(MBE), a careful control and stabilization of the source
temperature is necessary. In contrast, for materials with highevaporation temperatures, for example, refractory materials,

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Figure 12. Diffusion multiple approach to high-throughput materials research (from Ref. [134]).

which have to be deposited by electron beam evaporation,
control of the evaporation rate can only be achieved by
feedback loops, for example, by employing ion gauge ratemonitors and feedback algorithms. Only in this case can eachconstituent be controlled routinely to less than 1 mol %.
The co-deposition technique to obtain continuous compositions spreads has been used for the systematic explorationof known systems and also for the discovery of new materials
in unknown phase systems. An example of the first case wasreported by van Dover and Schneemeyer who described thesystematic trends of crystallization in amorphous Zr-Si-O
dielectrics.[127] Transition-metal oxides such as ZrO2 and HfO2
show a distinct tendency to crystallize at standard processing
temperatures (1000 8C for 20 s to activate dopants). By adding
a component with a much higher crystallization temperature,for example, Al2O3 or SiO2, this tendency can be reduced tothe detriment of the dielectric constant (eR : 9.0 and 3.9,
respectively). By using this technique, the authors prepared asample with a length of 5 cm and a composition of Zr1xSixO2(0.1 < x < 0.8), that is, the deposition gradient was roughly
1 mol % per mm. To simulate the effect of temperature during
a standard processing procedure the sample was subjected tohigh-temperature annealing and X-ray data were collected at
5 mm intervals along the composition spread. Only when x >0.8 was the film found to remain amorphous with a dielectric
constant of eR  6.9, a value that is only marginally larger thanthat of the industrial standard, amorphous silica. As the Zr-SiO system does not satisfy the requirement of a high eR value
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together with an amorphous state, the authors decided to starta systematic research for new solid-state materials in higherdimensional phase space, for example, the Zr-Ti-Sn-O system,
to find superior dielectric compounds that could be processed
below 400 8C, a requirement that largely excludes theextensively investigated crystalline dielectric materials. For
this they used a deposition chamber with three magnetron
sputtering units, and deposited the CCS materials on Si
substrates covered with metal base electrodes at slightly
elevated temperatures of 200 8C. Traveling Hg probes orcontacts of 0.2 mm radius made by deposition through ashadow mask were used as counterelectrodes for the capacitance mapping measurements. These measurements revealed
that the optimum amorphous material has a composition in
the vicinity of Zr0.2Sn0.2Ti0.6O2, whereas the commercially used
crystalline microwave dielectric material has a composition
close to Zr0.45Sn0.1Ti0.45O2 (see also Figure 10). It is extremely
unlikely that this optimum amorphous composition would
have been found by single-sample studies, which would
certainly have concentrated on compositions closer to theimportant crystalline composition.
Besides the magnetron sputtering technique, pulsed-laser
deposition (PLD) is also used for rapid, sequential submonolayer deposition of the constituents of the phase spread,with an intermixing of the constituents on the atomic scale
during the growth process. Therefore, as for co-deposition, a
pseudobinary or pseudoternary phase diagram can be generated without the requirement of a postannealing stage, thus

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making this approach applicable to the non-equilibriumsynthesis of metastable phases. Prerequisites for the perfection of CCS approaches are the submonolayer deposition of
the constituents and intermixing without postannealing, as
mentioned above, as well as an automation (very similar tothat used in discrete composition spread approaches) that cancontinuously move masks. As with all moving-shield applications, CCS deposition also relies critically on the uniformity ofthe deposition zone across the entire substrate area, thus
limiting the compositional spread in most cases to an area ofless than 2 cm. Again the synthesis and analysis methods are
intimately interwoven, as only sophisticated analysis techniques such as scanning probes (scanning microwave or SQUID
microscopy) or simultaneous imaging by concurrent X-ray
and optical methods are suitable. By applying a number ofdifferent “firing schemes” with synchronization between thelaser firing and substrate translation behind a fixed-slit
aperture, Christen et al.[137] were able to show that thismethod can be used to obtain controlled lateral variations
in film thickness, film composition, and deposition temperature. In all cases, the resulting samples are sufficiently large
for conventional characterization and measurement techniques, including ellipsometry, SQUID magnetometry, andtemperature-dependent resistance measurements. The PLD
technique has been applied in several studies, for example, tothe investigation of electrooptic (SrxBa1xNb2O6) and magnetic materials (Sr1xCaxRuO3) as well as epitaxial heterostructures in the form of superlattices with alternating stacks
of SrTiO3 and SrxBa1xZrO3, where the parameter x varies
continuously across the sample.[137–139] Similar approaches
were also used by other authors, for example, in Ref. [140],
for the growth of combinatorial libraries of thin films. Guerin
and Hayden[141] reported a novel co-deposition method inwhich fixed shutters were combined with electron beam andKnudsen PVD sources to produce controlled libraries with awide composition range. The insertion of fixed shutters topartially shadow the source can be optimized to produce
fluxes which vary across the substrate, and this shadowing
effect can be used to control the deposition profile. Bymodeling the finite PVD source, deposition has been
simulated for a number of geometries for a single finite
source site to establish the conditions required for optimal
wedge growth. The modeled PVD profiles were subsequently
compared with experiments and revealed good correlation
between the simulated and experimental data. The combination of three sources with individual shutters enables codeposition of metals at room temperature to provide large
compositional ranges of alloy materials in a non-equilibrium
state, thus allowing amorphous or microcrystalline mixed
crystal systems to be obtained. Annealing the sample either
during deposition or postdeposition induces the formation ofthermodynamic phases and surface segregation. To demonstrate the methodology, ternary CCSs of Pd, Pt, and Au as
well as Ge, Sb, and Te, each arranged in a threefold symmetry,were co-deposited, and the relative atomic percentage of thedeposited elements determined by energy-dispersive spectroscopy (EDS).
A similar approach, but with different terminology, wasapplied by Xiang.[142–144] The difference between his “contin-

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uous phase diagram” (CPD) approach and the former ones isthat in the ternary phase diagrams, three different precursors
are deposited sequentially in the form of wedges, one on topof the other in opposite directions. Homogeneous mixing of
the precursors is achieved by an appropriate postannealing
process, the temperatures of which are highly dependent on
the thickness of the individual elemental layer. It has been
known since 1983 from experiments by Schwarz and Johnson[145] that in the case of very thin layer thicknesses, so-called
ultrathin layers with thicknesses up to several hundred T,
multilayer composites interdiffuse at low temperatures toform a homogeneous, amorphous alloy. Interesting aspects ofthese solid-state reactions to generate an amorphous sample
are the surprising stability of the amorphous alloy withrespect to the crystalline, elemental components and theinability of the system to nucleate a compound from theamorphous intermediate. The stability of the amorphous alloy
with respect to the elements has been attributed to the large
negative heat of mixing of the elements, which originates fromthe observation that in many of the solid-state reactions
investigated, the formation of an amorphous alloy produces
the majority of the heat of formation of the final crystalline
compound. Although the crystalline product is more stable
than the amorphous alloy, it is thought not to form because of
kinetic limitations resulting from the existence of a nucleation
barrier. The formation of an amorphous intermediate therefore results from a competition between diffusion andnucleation. Xiang used this approach to discuss, as examples,
the results of mapping optical, electrical, and magnetic
properties of manganese oxides as a function of doping
concentrations, ionic radii, etc. Surprisingly, evidence wasfound for various electronic phase transitions, such as spin–
orbit orderings and smectic phase formation, in highly
correlated electronic systems such as the CPDs of perovskite
manganites of formula RE1xAExMnO3 (with RE = rare earthand AE = alkaline-earth element).[144] The systematic experimental data presented in this study should help to identify
new phenomena and elucidate the underlying physics of thesecomplex systems. Continuously mapping the doping dependence of complex materials has distinct advantages compared
to extrapolating over discrete doping points. A similar CPD
approach has been used by Yoo and Tsui, but with thedifference that the perovskite manganites were deposited
epitaxially in the form of monolayers or submonolayers ofindividual precursors at elevated temperatures on an appropriate substrate.[146] The real-time epitaxial processes weremonitored and controlled by using in situ MBE techniques,
such as scanning reflection high-energy electron diffraction(RHEED). Control over the composition is achieved by thesequence in which different precursors are deposited as well
as by the use of well-characterized flux gradients that are
strategically positioned to produce the desired continuouscomposition spread across the substrate. Besides perovskites,
magnetic alloys in the Co-Mn-Ge system have also beengrown and the magnetic properties of these thin films
investigated by the magnetooptic Kerr effect (MOKE) as
well as scanning Hall probes.[147]The multilayer technique has also been applied toisothermal sections of the Cr-Fe-Ni system grown on Al2O3-

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ChemieCombinatorial Materials Research(0001)-sapphire substrates by sequential deposition of layersof graded thickness followed by annealing to interdiffuse theelements. Maps of phase composition and lattice parameters
as a function of composition for several annealing treatments
were generated by rastering the film covering the Cr-Fe-Ni
ternary system under a focused beam of synchrotron radiation
while simultaneously measuring the diffraction pattern with acharge-coupled device (CCD) detector to determine crystallographic phases, texture, and lattice parameters and alsomeasuring the X-ray fluorescence (XRF) with an energydispersive detector to determine the elemental composition.[148] A versatile ion beam sputtering technique has been
described by Chikyow and co-workers to speed up thedevelopment of electronic components. Through depositionof binary and ternary metal films in a composition spread on adielectric film and characterization by capacitance–voltage
measurements, XRF, and XRD mapping, new multicomponent metal gate materials for CMOS transistor development
were investigated.[149] Similarly, effects of composition andannealing temperature on the achievable coercive field to
identify its maximum at low processing temperatures werestudied by Ludwig et al. in the Fe-Pt system on multilayer thinfilms with a broad composition range.[150] Two types ofmultilayer systems were deposited, the first type was comprised of alternating opposing wedges, whereas the second
type consisted of repeated uniform Fe and Pt layers interspersed periodically with wedge layers. It was found thatcoercive fields with m0Hc > 0.7 T can be achieved at annealing
temperatures of 300 8C for both types of multilayers close to
the composition FePt. Multilayers with additional Fe layers
showed increased remanence but reduced coercive fields. An
additional advantage in the deposition of thin films is thepossibility to apply external fields during deposition to
influence specific properties of the synthesized materials
systematically. For example, films and multilayers with adefined magnetic anisotropy can be achieved by applicationof magnetic fields. This was shown for nanoscale-fabricated
Fe50Co50/Co80B20 multilayers (m0Hext = 10 mT) produced bymagnetron sputtering, which resulted in a transition in thedependency of the anisotropic field HK, and thus theferromagnetic resonance frequency fR, which was notobserved before.[151] Even more promising, in view of
unexpected properties of designed new materials, are specificfeatures of multilayer stacks that differ from bulk materials of
the same composition. It is known that Ti-BN multilayers
generate ultrahard coatings with hardness values up to6000 HV, which exceeds the hardness of TiB2 with 3480 HV,
at a concentration ratio Ti/B/N of 1:0.5:0.4 after a subsequent
thermal treatment to induce a diffusion-activated mixing
process between the Ti and BN layers and subsequent phasetransformations.[152] The coating with this compositional ratio
is assumed to comprise a mixture of two solid solutions of type
Ti(Bx,Ny) and TiB1xNy. Another example is the first observation of a dramatic increase in hydrogen solubility in Nb-Ta
superlattices, compared to what would be expected for bulk
Ta or Nb, as a result of strain modulation in the multilayer
induced by interstitially dissolved atomic hydrogen.[153] Multilayer thin films with compositional gradients can be synthesized to systematically investigate unexplored regions inAngew. Chem. Int. Ed. 2007, 46, 6016 – 6067

phase space to discover new materials that reveal phenomenaof this type. For example, by using HTE on thermoplastic
shape memory alloys (SMA), a new composition region of Tirich SMA was identified by the research groups of Takeuchi
and Ludwig.[154] From the relationship between the magnetic
hysteresis and the transformation stretch tensor, the geometric nonlinear theory of the formation of martensite based
solely on crystal symmetry and geometric compatibilities
between the corresponding phases which predict a reversibility of structural phase transitions could be verified. Amongthese new materials, giant magnetorestriction and magnetic
SMA are currently being studied for high-speed actuation in
adaptive systems. A limitation in the application of thesematerials in actuators is the requirement large switching fields
for actuation. In exchange-coupled geometries such as multilayers, the switching field might be reduced because of the socalled KnellerRs exchange spring mechanism,[155] in which theaverage magnetization is increased and the average anisotropy of the multilayers decreased. This is achieved bysandwiching actuator thin films with high switching fields
between high magnetization soft magnets such as Fe or
Fe50Co50. Prerequisite for this is that the individual layer
thickness is kept below the wall thickness of the domain toprevent formation of domain walls parallel to the interfaces,
whose presence would otherwise lead to a substantial
reduction in the observed magnetostriction and a more
complex behavior. The microscopic nature of the Kneller
exchange spring mechanism was investigated using TbFe/
FeCo and FePd/Fe multilayers deposited by magnetron
sputtering on Si(001) substrates.[156] In this approach thecomposition of the FePd films was varied either by sputteringa Fe70Pd30 target under varying powers and pressures, or bycosputtering Fe50Pd50 or Fe70Pd30 targets with a pure Fe target.
A disadvantage of the CCS approaches is the need foranalytical methods with high lateral resolution to avoid
information averaged over the spatial region analyzed. For
example, only microfocused beams of synchrotron radiation
scanning the surface of the composition spread are appropriate when using X-ray diffraction for characterization.
When these analytical tools are not available, combinatorialmasked deposition (CMD) has to be applied for the
production of thin films with individual spots of homogeneouscomposition. Masking can be obtained either by physicalshadow masks[157] or photolithographic lift-off systems.[151] In
this context the study by Weinberg and co-workers has
attracted a great deal of attention, in which they describe an
automated combinatorial method for synthesizing and characterizing thin-film libraries of up to 25 000 different materials
on a substrate with a diameter of three inches as candidates
for new phosphors.[10] These libraries were deposited as thinfilms by electron-beam evaporation from multiple graphite
crucible target pockets using a stainless-steel primary mask
consisting of 230 mm square elements spaced 420 mm apart.
This enabled the authors to identify a new red phosphor
Y0.845Al0.070La0.060Eu0.025VO4 with superior quantum efficiency.
The use of this combinatorial concept in conjunction withlaser MBE is widespread, and is named combinatorial laser
MBE (CLMBE). The research group of Koinuma hasdeveloped a CLMBE system which features a multitarget 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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holder and a disk plate consisting of eight distinctly patternedmasking plates.[158] This approach, documented in a large
number of manuscripts, was used, for example, for thesynthesis of high-quality c-axis-oriented Mg-doped ZnO
thin films on sapphire (0001) substrates,[158] 3d transition
metal ion doped epitaxial ZnO films,[159, 160] libraries of thin
(Ca1xBax)3Co4O9 films on TiO2 rutile (001) substrates,[160] andSrTiO3/BaTiO3 superlattices with equimolar ratios and different periodicities.[161] Epitaxial composition spreads of Sr-VCr-Ti oxides on two different single-crystal substrates,
LaAlO3 and Nb-doped SrTiO3, have been evaluated for thephotoreduction of Ag+ to Ag. Photodeposition of Ag wasenhanced in the region of SrV0.05Ti0.95O3 only on the Nbdoped SrTiO3.[162] However, the CMD method can only beeffective when three conditions are satisfied: the mask-source
distance has to be much larger than the mean free path of thedeposition species, the mask–substrate distance much lower
than the mean free path of the deposition species, and last but
not least the sticking probability near 1. Under these
conditions, the flying direction of the deposition species is

randomized by sufficient gas-phase collisions in the space
between the source and the mask and, therefore, the species
passes through the hole at randomized angles. Deposition flux
is another important factor that determines the structures ofthe vapor-deposited materials. Noda et al. investigated theeffect of the deposition flux on the island structure, anddeveloped a simple method to control the deposition flux andits spatial distribution.[163] Photolithographic techniques incombination with the production of thin films by magnetron
sputtering were used by Whitacre et al., who developed amethodology for batch-fabricating hundreds of submillimeterthin-film solid-state batteries from LiMn2O4 and LiNiO2
sputter sources.[164] Their process flow for the microfabrication of a Li metal anode is depicted in Figure 13.
Many other different evaporation techniques have been
applied for the generation of thin-film libraries. For example,
hot-wire chemical vapor deposition (HWCVD) has been used
in a combinatorial approach to grow device-quality amorphous and microcrystalline thin Si films by decomposing SiH4
at a tungsten wire at 2000 8C.[165, 166] In this context, micro-

Figure 13. Process flow for the microfabrication of Li metal anodes (from Ref. [164]) which shows the processing steps involved in creating a
microdimensional Li anode on an existing thin-film microbattery structure. These include masking with photoresists, exposure to UV light,
removing excess photoresist, deposition of a lithium film, and removal of excess lithium (1–9). The last step is carried out by covering the entire
area with adhesive kapton and slowly peeling it away. The processing is done in a dry room environment with less than 1 % humidity.

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electromechanical systems (MEMS) are powerful tools forthe fabrication and processing of materials libraries. MEMS
can be used for the parallel processing of materials, either as
passive devices such as shadow-mask structures or as active
devices such as micro-hotplates. Ludwig, Takeuchi et al.
described the production of discrete arrays of micro-hotplates
and the concepts for micromachined gradient heaters.[167]
These are well suited as microdeposition substrates formaterials research using CVD. To illustrate this approach,
Taylor and Semancik deposited TiO2 from TiIV nitrate andisopropoxide as precursors using micro-hotplates for developing metal oxide thin film gas sensors.[168]Deposition of thin films by electrochemical methods has
also been used for HTS and the screening of materials.
Besides not needing an ultrahigh vacuum (UHV), electrochemical methods have the advantage that the synthesis canbe directed in a way that the resulting thin films have asufficient surface roughness to catalyze chemical reactions.
With electrochemical methods, there are many synthesis
variables under direct control, such as voltage, current
density, and electrolyte. These can be changed readily using
automated programmable systems, thereby resulting in adiverse range of structures and compositions. Baeck, McFarland, and co-workers developed an automated system for theelectrochemical synthesis and HT screening of catalytic
materials by using a well-plate-based assembly with up to 63
samples.[169, 170] The library plate is sealed in this systembeneath a perforated polypropylene block with an array of
independent O rings underneath. Electrodeposition is achieved either serially using an x-y-z translatable counter andreference wire electrodes or in a parallel mode using an arrayof counterelectrodes multiplexed to a potentiostat. The
authors characterized their system in a way that the parallelsystem had a higher throughput; however, the rapid serial
method offers better control for each deposition.[171] Thissystem was used to synthesize 2D arrays of gold nanoparticles
on a thermally oxidized titanium dioxide substrate for thephotoelectrochemical oxidation of water and electrooxidation of CO,[171] ZnO samples with varying concentration of thestructure-directing agent (SDA) poly(ethyleneoxide)-blockpoly(propylene oxide)-block-poly(ethylene oxide) EO20PO70EO20 ranging from 0–15 weight % for photocatalysis,[169]and WO3-MoO3 mixed-metal oxides on Ti foil with n-type
behavior for photocatalytic activity measurements.[172] The
activity screening was performed in the same device automatically by using a scanning photoelectrochemical cell thattraverses the library, thereby illuminating each sample with amodulated light source.
Besides the electrodeposition of samples with discrete
structure and composition, there is also a counterpart forcontinuous compositions spreads in electrochemistry: byusing homemade, modified Hull cells with nonparallel
electrodes that resulted in a current density gradient, Beattie
and Dahn[173] performed the deposition of a 2D composition
spread library of Sn-Zn alloys. A third element, Cu, wassubsequently introduced in the composition spread library bydripped immersion plating (DIP), that is, by continuously
increasing the amount of Cu sulfate solution in a beaker, inwhich the library was placed vertically, and with theAngew. Chem. Int. Ed. 2007, 46, 6016 – 6067

composition gradient running parallel to the solution surface.
As a result of the continuous dripping (by a Tsunami BlasterX water gun as a peristaltic pump!) of the Cu solution, thecontact time of the library with the solution during electrodeposition and thus the vertical Cu content varies. The choiceof the Sn-Zn system was not arbitrary, but it is well-known
that Sn as well as Zn undergo ion exchange with aqueous Cu
ions, as indicated by their relative standard hydrogenreference electrode (SHE) reduction potentials. Alloy systems such as Cu-Sn-Zn have been proposed as a replacement
for graphitic cathodes in commercial lithium-ion batteries as aconsequence of their high theoretical capacity and relatively
good cyclability. Several other methods have been reported
for the generation of composition gradients, including thenovel gradient fabrication technique based on solution
diffusion, followed by electrodeposition for the constructionof highly dense libraries of samples of electrooxidation
catalysts on indium tin oxide (ITO) substrates.[174] In thismethod, a surface gradient is created by controlled diffusionof precursor materials into a swollen polymer gel. In special
cases a binary composition gradient is produced by diffusionof a solution containing the salt of a second metal into a gel
containing a uniform concentration of a salt of the first metal
in its matrix under controlled humidity conditions to avoid
shrinkage of the gel. After diffusion, the metal ions areelectrochemically reduced onto the surface of a conductive
substrate. Removal of the gel leaves a composition gradient of
the binary catalyst system on the substrate. A binary PtxRuy
composition gradient was constructed as a model system andscreened for catalytic electrooxidation activity using a scanning electrochemical microscope (SECM). Instead of implantation into a gel, implantation into solid materials by nonelectrochemical methods has also been used to prepare
combinatorial libraries. Stritzker and co-workers have built
up an advanced apparatus for the combinatorial synthesis ofdensely packed, thin buried layers of semiconductor nanocrystals, such as CdSe, in thermally grown SiO2 on Si.[175–177] In
this approach, the combinatorial materials library was generated by sequential implantation of Cd+ and Se+ ions and thegradients generated by spatially moving selective shields
inserted into the particle beam. In practice, this is achieved
using a Freeman ion source loaded with CdSe material andselection of the isotope to be implanted by an electromagnetic
isotope separator. A lateral pattern of well-defined distinct
combinations of dose and isotope ratios of different sequentially implanted ion species is obtained by moving a precise
and automated stainless-steel shield stepwise. Analogously,
mixed cadmium sulfide selenides were ion-implanted andcharacterized by Rutherford backscattering analysis (RBSA),
XRD, and Raman spectroscopy, which indicated the formation of the solid solutions CdSxSe1x of the implanted ions insilica.[178] In a similar way, modifications of the structure andmagnetic properties of magnetron-sputtered Fe50Co50 films
induced by high dose Sm or Xe implantation have beenachieved by combinatorial ion implantation.[179]
Solid thin films are usually not suitable for the study ofcatalytic properties because of mass-transport problems. HTE
for catalytic applications therefore often relies on the synthesis of bulk materials by solution-based methods.

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3.2. Solution-Based Methods
The application of combinatorial methods to materials
synthesis in the field of solution chemistry generates a numberof new challenges to be faced, such as issues of scalability andreproducibility, poorly defined and understood active sites,
poorly understood links between activity and chemical
process conditions, as well as the formation of metastablestructures. Many new parameters, for example, particle
morphology, may play just as important a role as compositionin the performance of a catalyst. Compared to the depositionof thin films, especially electrodeposition and chemical vapor
deposition methods, solution methods are very complex andare labor-intensive processes which are sensitive to handlingprocedures, such as, for example, experimental conditions,high temperatures or pressures, pH value, and nature ofsolvents, preparative procedures, for example, milling,
mixing, and mixing order, as well as work-up procedures,for example, washing, filtering, and drying. The influence of
all these parameters on the catalytic performance of amaterial necessitates the extension of high-throughput concepts into the even more demanding process of catalyst
optimization. It is not only important to recognize all theparameters that affect catalytic performance, but also thecomplete documentation of these in a database in a reusable
and mineable form is crucial, especially if quantitative
structure–activity relationships (QSARs) need to be deduced.
Impregnation of porous support materials with active
components, such as noble metals, is a common technology
for catalyst preparation. It lends itself perfectly for HT
applications and has thus been applied in many studies.[180–184]
The automation of conventional precipitation reactions is lesstrivial. The parallel preparation of catalysts for libraries by
precipitation remains a challenging problem because of thehigh dilution, necessity of temperature, and the need for pH
control during precipitation, followed by filtration, washing,and calcination.[2] Hoffmann et al. used automated co-precipitation for the preparation of Au catalysts.[185] A typicalexample of the complexity of solution-based reactions andchallenges which have to be faced is hydrothermal synthesis.
A number of parallel hydrothermal crystallization configurations have been reported in the literature, one of the firstbeing that of Akporiaye et al.,[186, 187] Bein and co-workers,[188]and Klein et al.[189, 190] The main focus of this method has been
the parallel synthesis of meso- and microporous zeolites andaluminophosphates (AlPOs) by a multiclave concept, a term
derived from the condensation of “multiple autoclaves”.
Historically, parallel experimentation has been the norm in
the exploration of zeolite crystallization fields, but increasing
the number of parallel reactors, achievement of sufficient
control over physical parameters, and the development ofanalytical approaches that need much smaller productamounts still need to be addressed. Song et al. recently
presented a strategy toward the rational synthesis of microporous materials by the combination of a computational and a
combinatorial approach.[191] The templating abilities of various organic amines in the formation of the microporousaluminophosphate AlPO4-21 have been evaluated by considering the nonbonding host–guest interaction energies simu-

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lated by molecular dynamics (MD) calculations using the
Cerius package of MSI. On the basis of the predicted suitable
templates, the use of a rational selection of amines such as
ethanolamine, triethylamine, and N,N,N’,N’-tetramethylethylenediamine in the reaction system Al(iOPr)3/x H3PO4/y amine/255 H2O resulted in the successful synthesis of
AlPO4-21. Characterization of the products was achieved byinductively coupled plasma (ICP) analysis, thermogravimetry(TG), as well as powder and single-crystal X-ray diffraction(XRD). The framework of AlPO4-21 belongs to zeotype
AWO, with eight-membered ring-shaped channels along the[001] direction.
Special attention has also been paid to the rational DoE in
the synthesis of microporous materials. For this purpose,
Newsam and co-workers developed a Monte Carlo approachbased on the method of automated assembly of secondary
building units (AASBU).[192] This method generates virtual
libraries of viable inorganic structures by sampling the ways inwhich predefined secondary building units (SBUs) can bethree-dimensionally interlinked. Knight and Lewis reported
on a template-screening approach in which combinatorial
methods were applied to investigate the structure-directing
properties of the ethyltrimethylammonium (ETMA) template, both by itself and in combination with other structuredirecting agents (SDAs) in the range Si/Al = 2–48.[193] The
main topic addressed in this investigation was the decouplingof the role of the different components that strongly influencezeolite crystallization, that is, the silica, alumina, and hydroxide sources, from the sources of additional SDAs. This was
accomplished by using ETMA aluminosilicate solutions,
ETMAOH as the sole hydroxide source, and additional
SDAs as salts. These experiments yielded the new zeolite
species UZM-4, UZM-8, UZM-15, and UZM-17, and thus
demonstrated the broad potential of a single organic template
to synthesize materials with both small and large pores. The
application of porous aluminosilicates has also been of
considerable interest, for example, as matrices for theencapsulation of conducting organic polymers to stabilize
these highly degradable and labile species. Atienzar et al.
reported the first synthesis of oligo(p-phenylenevinylene)s(OPVs) encapsulated within zeolites by using a high-throughput system for the preparation and screening.[194] A 96-wellsample library based on a (2 V 32 V 5) factorial design was
obtained after consideration of the following preparation
factors (levels) in the synthesis of OPV@zeolite: different
monomer loadings (2), synthesis temperatures (3), zeolite
structures (3), as well as nature of the exchanged alkali-metal
ions (5). High-throughput characterization of the library wasachieved by operando photoluminescence spectroscopy,
which revealed that the synthesis temperature and thenature of the alkali-metal ion present in the zeolite were themost important experimental parameters to be controlled in
the synthesis.
A combinatorial hydrothermal synthesis methodology
with variation and optimization of the pH value has also been
applied for the characterization of 48 perovskite samples inthe (Pb,Ba,Sr)ZrO3 compositional field.[195] In a second seriesof 96 samples, the (Pb,Ba)(Ti,Zr)O3 compositional field was
also investigated combinatorially to control the crystallinity

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Angewandte

ChemieCombinatorial Materials Researchand particle size. Both series revealed that combinatorialhydrothermal synthesis and characterization techniques areapplicable to the perovskite family.
During the course of the continuous miniaturization of
HT devices in the discovery and screening of new materials, a
reduction of both the droplet size of the applied precursor
solution during the synthesis and the complete reactor
assembly to increase the sample density in combinatorial
libraries has been explored. In regard to the amount of liquid
applied, there is a continuous transition from micropipetting
methods to ink-jet printing techniques associated with acontinuous reduction in the droplet size. Whereas micropipetting is normally used to transfer liquids from stock
solutions to discrete wells, ink-jet printing offers the possibility of reducing the dosing volumes to several magnitudes
smaller than with micropipetting and thus offers the possibility of generating pseudocontinuous sample libraries. Inkjet printing (Figure 14) has been successfully used in the last

Wang et al. generated multiple compositions by combinatorial ink-jet printing of ceramics in the pseudoternary system
BaTiO3-Al2O3-ZrO2.[199] Two different approaches were used:discharging variable compositions by mixing liquids within
the printer with the help of pressurized reservoirs, electromagnetic valves, a micropump, and an associated mixing
chamber, tubing, and nozzle, or well-plate reformatting byaspiration–dispersion action for the application of individual
ceramic suspensions. Both approaches involve the mixing of
ceramic suspensions such that diffusion distances during
sintering are comparable to the particle or agglomeratedimensions, thereby achieving high compositional accuracy inboth cases. The main difference between the two methods isthat the mixing in front of the nozzle in the well-platetechniques enables mixtures with a large number of components to be made, which is limited only by the number of wells
and nozzle dimensions, whereas in direct mixing, the numberof components is limited by the number of printer lines
available. Well-plate reformatting of ceramic inks was also theprinciple of operation of the London University SearchInstrument (LUSI), which was commissioned to create andtest combinatorial libraries of ceramic compositions.[200]3.2.1. Microfluidics

Figure 14. Principle of ink-jet printing.

decade for a number of new applications, such as the
fabrication of organic light-emitting diodes (OLED), transistors and integrated circuits, ceramics, and a large number ofpolymer applications, which are not cited here in detail. For
an overview, we recommend a special issue of the journal“Macromolecular Rapid Communications”[196] as well as adetailed review by Wallace and Grove.[197]
The inks to be deposited on substrate surfaces by ink-jet
techniques have to meet very strict physicochemical properties, such as viscosity, surface tension, adhesion to a substrateetc., that is, parameters which are summarized in the ink
formulation. The materials to be printed are either soluble orinsoluble, so the ink is either a solution or a dispersion (solid
in liquid) or even a microemulsion (liquid in liquid). A
reduction of the particle or micelle size to 50 nm or less is
expected to improve the image quality, resolution, andreliability of the printhead. Ink-jet techniques have been
applied in combinatorial chemistry for the deposition of
metallic nanoparticles and microemulsions.[198] Kamyshny
et al. used aqueous dispersions of Ag nanoparticles stabilized
by polyelectrolytes and surfactants for printing conducting
patterns onto various substrates using standard ink cartridges.
Angew. Chem. Int. Ed. 2007, 46, 6016 – 6067

Another miniaturization approach, which has the advantage of being able to handle nanoliters of fluid and to provide
fast response times, is microfluidics. This is a rapidly developing technology that involves the handling of fluids indevices containing channels in the micrometer-size regime.
Microfluidic technology is used in many applications in thelife sciences and pharmaceutical industry as a quick andefficient method for performing biological assays on the
nanoliter scale and for rapid chemical analysis of aqueous
solutions. Beers and co-workers used rapid prototyping
photolithography of a thiolene-based resin to fabricate
microfluidic devices stable to aliphatic and aromatic organic
solvents.[201] For this purpose, the thiolene-based adhesive
NOA 81, which can be hardened with UV light, was spread
between two glass slides and two identical photomasksaligned and placed on the top of the thiolene device. Afterprecuring the sample under a UV lamp, the uncured resin was
flushed from the channels with air and solvents. Droplets ofhexane and toluene of uniform size were generated inside awater matrix containing SDS surfactant within the generated
channels. The possibility of performing reactions within theorganic phase were demonstrated by the bromination ofalkenes within the droplets. Alternatively, microcapillaries
with diameters as small as 0.5 mm have been drilled into
PDMS microfluidic devices by using femtosecond laser pulses
as a micromachining technique.[202] Laser-drilled microcapillaries were also used by the same research group to trap apolystyrene bead by suction and hold it against a shear flow.
Symyx Technologies used a massively parallel microfluidic
reactor system, which consisted of a microfluidic flow
distribution system, a 256-element catalyst array, and colorimetric detection methodology to allow parallel reaction andparallel detection, for the high-throughput screening of
catalysts for the gas-phase oxidation of ethane to acetic

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acid,[203] the oxidative dehydrogenation of ethane to ethylene,
the selective ammoxidation of propane to acrylonitrile,[204] aswell as other heterogeneous catalytic liquid and gas-phaseoxidation reactions.[205]3.2.2. Approaches To Increase the Sampling Space (vHT)
As a consequence of increasing parallelization and theintegration of reactor and analysis systems, the requirements
for new synthesis methodologies include ever smaller
amounts of samples, for example, different multicomponent
mixed oxides in the mg or even mg range have to be prepared
reproducibly and by a fully automated process. The need forautomation brings experts of different skills together to fuse
the challenges of robotics and automation with those of
inorganic or organic synthesis. So-called split&pool (S&P)
methods have been developed to achieve very high throughput (vHT) of highly diverse materials libraries in the range of
103–108 samples by a simple procedure to realize combinatorial chemistry in its intrinsic meaning, that is, the combinatorial permutation of element combinations or synthesis
parameters. Based on the pioneering work by Houghton[206] aswell as by Geysen et al.[207] on multiple peptide synthesis,
Furka et al. presented a novel concept at a conference[208] inwhich some characteristics of the former methods weremerged. Common synonyms for the S&P synthesis are“mix&split”, “split&combine”, “one bead—one compound”
and “selectide process”.[209] The process is depicted schematically in Figure 15: a batch of porous spherical beads, originallymade from resin in peptide chemistry, but in inorganic S&P
synthesis made from an inert support material such as Al2O3,
SiO2, etc., prepared with a homogeneous size and loading
capacity is divided (“split”) into a number of aliquots of equalsize. A different monomer (A, B, C) is coupled to eachportion, or a different metal precursor solution (A, B, C) is
impregnated in each portion.
After completion of the coupling, excess reagent isremoved by washing, the aliquots are combined again and

Figure 15. Schematic representation of the split&pool principle (fromRef. [209]).

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mixed (“pool”). As shown in Figure 15, a library with threeprecursors A, B, C consists after three cycles of 33 = 27
members, after four cycles of 34 = 81 members, and so on; ingeneral 3S library elements will result after S split cycles. If thenumber of precursors is denoted as M, the total number oflibrary elements N is calculated as N = MS. The S&P
technique can be used to evaluate a large number ofcompounds with very little effort. The practical limit of thelibrary size depends strongly on the number of beads which
can be handled and screened with a corresponding assay. The
problem with the S&P technique is that, due to the mixing
steps, the composition of each bead is unknown and has to be
determined in a separate step, for example, by m-XRF
techniques. Another solution to this problem is to arrange
the beads in a two-dimensional array so that each library
member is spatially addressable by its position in the array or
to tag the beads by labels for identification. Klein et al.[209]developed a powerful enhancement of this synthesis tool in
the form of a “single-bead reactor” (SBR), which allows
efficient testing of the libraries created by the split&pool
methodology.
Nanosphere lithography is an inexpensive alternativetechnique if not the composition but the size of the individuallibrary members has to be varied. This technique offers thepossibility of inherent parallelization, high throughput, andthe relatively unlimited preparation of accessible materials
for well-ordered 2D periodic arrays of nanoparticles.[210, 211] In
this technique, the self-assembly of spherical beads is used as
the shadow mask for the physical vapor deposition (PVD) of
materials, such as Ag nanoparticles. The nanosphere lithography masks were created by spin-coating suspensions ofpolystyrene nanospheres of different sizes (165, 264, 401,
542 nm) in water together with a surfactant to assist thesolutions in wetting onto the substrate of interest. Thin filmsof Ag were deposited whilst varying the in-plane diameter ofthe nanoparticles from 26 to 126 nm, and similarly the out-ofplane height by variation of the mass thickness of the Ag
overlayer. The experimental determination of these parameters after deposition was carried out by AFM measurements.
These studies revealed that the dimensions of the nanoparticles accurately correspond after correction for convolution of the AFM tip to predictions based on the mask
geometry of the nanospheres. Furthermore, the authors
established that nanosphere lithography can fabricate nanoparticles that contain only approximately 4 V 104 atoms (inplane diameter: 21 nm, out-of-plane diameter: 4  1 nm), thatis, in the size-range of surface-confined clusters. Additional
compositional variation may be achieved within this approachby sputtering gradients, multilayers, or codeposition of different elements, that is, topics, which have already beenaddressed in more detail above.
The two extreme cases in the broad field of sample
preparation for HT applications are: the combining of all thesamples in one pool and the synthesizing of a large number ofindividual samples with different properties in a parallelmanner. Between these two extremes there is a continuoustransition, which opens up the possibility of various intermediate approaches, such as, for example, the single-sample
concept (SSC) proposed by Hulliger and Awan.[212, 213] In this 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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approach, a single sample of approximately 1 cm3 is preparedby treating N randomly mixed starting materials by solid-state
reactions. Whereas in traditional ceramic synthesis only asmall number of components (usually 2–4) are reacted bythermal treatment, which results in one stable product atnearly any place within the sample—at least after a longreaction time—a large number of starting materials N eachrandomly constituted in a neighborhood of grains, which leads
to a so-called local configuration C of different elements andcorresponding masses, may lead in principle to a new
multicomponent compound. However, experience showsthat the thermodynamic stability of a multicomponent compound decreases with the number of constituents, and thatimportant material properties may be obtained even by alimited number q of constitutional elements (q  6) in solidstate compounds. Consequently, as the available number ofstarting grains within the 1 cm3 sample exceeds realistic
estimations for the number of phases present in the phase
diagrams, the SSC concept can provide access to all existing
compounds in a high-dimensional phase space in one single
preparation step. The experimental implementation of theconcept was demonstrated by the authors by the synthesis of alibrary of ferri- and ferromagnetic oxides. After milling thereactant mixture to reduce the size of the grains, surfactants
were added to obtain a suspension, by passing the emulsion
through a separation column, and then a magnetic-field
gradient was used to extract the magnetic particles. Analysesof single grains by scanning electron microscopy (SEM)
revealed a library consisting of individual grains of magnetic
Fe oxides.[212] As calculations show, the number of reactions
performed in parallel in a single sample can be orders ofmagnitude higher than achieved by present 2D approaches.
Furthermore, this concept is not restricted to inorganic
chemistry, but also has a counterpart in organic or molecularchemistry in the form of branched architectures of functionalized monomers that lead to the formation of unique,asymmetric dendritic species with multiple functionalities.[214]4. High-Throughput Analysis and Characterization
Every high-throughput synthesis technique automaticallygenerates the need for a corresponding and appropriate highthroughput characterization method for testing the generated

sample libraries for desired properties (functions). As alreadystated in Section 3.1, not only may the throughput become thebottleneck, but also the spatial resolution of the analyticalmethod may be limiting if very high sample “densities” areproduced by continuous composition spread techniques.
In principle the HTS tools to be applied for the evaluationof libraries of combinatorially developed materials can bedivided according to the different sampling methods into
in situ (or even operando) and post-reaction methods, oralternatively according to the measurement mode used inserial and parallel techniques, as classified by Potyrailo.[215, 216]
The development process is depicted schematically in
Figure 16. The first step in this development process is theidentification of the analytical problem, by using wellestablished criteria for the analysis capabilities to select theadequate method. The factors to be specified are, forexample, the analysis turnaround, sample size, quantification
precision and accuracy, need for the availability of samples forfurther characterization, etc. If the analytical method has notbeen used previously in HTS for this particular analyticalproblem, an appropriate conventional technique using larger
sample sizes or other required parameters should be chosen
as a reference technique for validation of the new method.
Among the truly parallel methods for library screening
developed so far, a number of methods immediately attracted
general interest, such as resonance-enhanced multiphoton
ionization (REMPI),[217] emission-corrected IR thermography(ecIRT),[218] as well as laser-induced fluorescence imaging(LIFI).[219] Each technique has its field of application; forexample, IR imaging is a powerful tool for the detection ofheats of reactions, such as catalytic activities or heats ofabsorptions, in combinatorial libraries. The use of ecIRT
enables temperature differences down to 0.02 K to be
detected and the heat evolution identified from catalyzed
gas-phase reactions with small catalyst amounts (< 20 mg).
Reactions have been observed at temperatures up to 650 8C,
thereby indicating that the method can be applied over a wide
temperature range.[220, 221] Quantification of ecIRT data
through integration of the heat spots on an image has also
been described.[221] However, ecIRT cannot differentiate
between desired and undesired reactions. Rapid, sequential
HT mass spectrometry was applied early on by several
research groups for the screening of catalyst activities andselectivities.[222–225] The use of gas chromatography in HTE

Figure 16. Strategies for the development of new high-throughput screening methods (from Ref. [216]).
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was described early on in catalysis research.[124, 226] The use of
HT-GC and HT-MS on larger libraries was described in detailby Weiss et al.[227] Here, the authors made use of the short MS
analysis times of conventional instruments, which can collectlarge numbers of MS scans within seconds, and interfaced aregular MS instrument through a capillary with an open
reactor system. The problems, such as sources of error anddata-storage considerations as well as the handling of themeasured data when using such a sequential MS analysis
approach with libraries have been described in detail.[228, 229]
The screening of enantioselectivity has been problematic,
since the usual times for analysis with conventional chiralcolumns in GC or HPLC applications is much too long forsequential applications in HT experiments. A variety ofmethods, such as UV/Vis analysis, fluorescence analysis, IRthermographic assays, circular dichroism assays, chromatographic assays, parallel capillary electrophoresis, mass spectrometric assays, radioactivity assays, NMR, and IR assays
were developed within only a few years for the rapid
screening of enantioselective catalysis. The methods havebeen reviewed by Reetz,[230] and most of them have also beendeveloped by his research group. The most rapid (more than7000 ee determinations per day) and most versatile method
for the analysis of chiral products of HTE appears to beparallel capillary electrophoresis.[231]
Among the techniques with potential to be parallelized,
spectroscopic methods are most promising, because a numberof 2D detectors have been developed which dramaticallyaccelerate sampling and allow for the direct imaging of asample so that the spatial distribution of different components of the library can be obtained simultaneously in a single
measurement. This approach is different to conventional
microscopy as it maps a specimen by running a series ofspectra in a 1D row or in a 2D grid thereby allowing
comparison of any one point with surrounding points.[232] The
photoluminescence of the 25 000 materials library mentioned
before was investigated after UV excitation (at 254 nm) using
optical imaging with a CCD.[10] Sun described how phosphor
libraries can be made in both thin-film and powder form byusing masking strategies and liquid-dispensing systems,
respectively.[233] After annealing the libraries at a hightemperature, photoluminescence images were taken under
UV (254 nm) illumination, and revealed some interesting
tricolor UV phosphors. Measurement of the photoluminescence images under a spatially uniform X-ray field of 12 keVgenerated from a synchrotron radiation source provided a few
leads for efficient X-ray scintillators. In fact, the human eye isso sensitive that it can in most cases pick up the phosphor leadof interest directly from the library under irradiation, but ascientific CCD camera in combination with a spectrophotometer has been set up to perform high-speed spectral
acquisition and calculation.
An impressive variety of image analyses for materials
properties have been developed at the US National Instituteof Standards and Technology (NIST). These analyses can beused to visualize such complex phenomena as polymer
dewetting, adhesion measurements, or cell-materials interactions in HTE.[234] A typical example is shown in Figure 17. The
multilens contact adhesion test (MCAT) has been developed

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Figure 17. Multilens contact adhesion test (MCAT), monitored by a
CCD camera (left side) and false color (here in gray) images (rightside). The brightest spot indicates the longest contact and thus bestadhesion (from Ref. [234]).

to measure adhesion reliably in HT. In this test, an array ofover 1000 microlenses (here polydimethylsiloxanes) isbrought into contact with a complementary substrate. The
contact area and displacement of each microlens are monitored by a CCD camera and 820 images are collected torecord the entire process of interface formation and failure.
The adhesion of each lens is calculated automatically anddisplayed by false colors (here in gray). Figure 17 shows three
images of the contact process of nine microlenses—from top
to bottom: no contact, contact of two lenses, and contact ofseven lenses. In the associated false colors the brightest
images had the longest contact and thus the best adhesion.
Laser-induced fluorescence imaging (LIFI) has been usedby Su and Yeung to screen for heterogeneous catalysts. The
method relies on the change in fluorescence properties uponbond breaking and bond formation, processes typical forcatalysis. It has been used to screen for new mixed-oxide
catalysts for the selective oxidation of naphthalene and thecoupling of benzene and phthalic anhydride to anthraquinone.[235]
The optical imaging approach with a CCD was extended
to the combinatorial screening and optimization of organic
light-emitting diodes (OLEDs), that is, devices that will findapplication in the next generation of flat-panel-display
technology.[236] In a neighboring spectral region, a wide
variety of infrared-based techniques have also been investigated for high-throughput analyses of samples interfaced to
an infrared beam of light. Although microbead analysis by an
IR beam has been extensively used as a characterization toolin the pharmaceutical industry, Lauterbach and co-workers
demonstrated a major improvement in the characterization of
catalytic activity by using FTIR imaging approaches.[237–239] In
principle, FTIR measurements can be performed either in thetransmission mode for transparent substrates or in thereflectance mode for nontransparent ones. In the latter case,there are potentially severe problems with regard to opticalinterference fringes produced in the spectra from thin, flat
films on a reflective surface,[240] which can only be avoided bycatalytic systems with enough surface roughness to give a
diffuse scattering of the IR beam. The feasibility of FTIR
imaging to study gaseous or solid-state reactions was demon-

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ChemieCombinatorial Materials Researchstrated in several transmission cells.[237, 241] By using attenuatedtotal-reflection (ATR) imaging Chan and Kazarian studied
samples under a broad range of humidities and applied highthroughput testing to pharmaceutical formulations.[242] TheirFTIR imaging system consisted of a step-scan spectrometercoupled with a macrochamber extension and a 64 V 64 focal
plane array (FPA) detector with a size of 3.8 V 3.8 mm2.
Images were acquired through an inverted ZnSe pyramid
crystal not originally designed for imaging purposes. The
aspect ratio meant that the size of the imaging area was 3.8 V
5.3 mm2. By using a device that can deliver microliter-sized
droplets, that is, an ink-jet printing technique, and dispensing
10 droplets at each location, they were able to form samples
on the ATR crystal with a diameter of 200–250 mm. Multivariate and univariate analyses of IR imaging data were also
used to study NH3 decomposition as well as NOx storage andreduction (NSR) catalysts.[243, 244] Their optical set-up consisted of a spectrometer, several refractive optical elements, agas-phase array (GPA) sampling accessory, and a mercury
cadmium telluride (MCT) FPA detector with a size of 64 V 64
pixel. This arrangement is shown schematically in Figure 18.

Figure 18. Experimental set-up used by Lauterbach and co-workers toanalyze the reaction products of 16 heterogeneous catalysts in parallelby FTIR imaging.[243]

The GPA is based on an array of 16 stainless-steel tubes,
capped by barium fluoride windows on each end. Each tube
had a separate inlet and outlet to maintain separation of the
products being analyzed. The effects of the number of coadded mirror scans of the spectrometer used in the datacollection together with the number of factors used in the data
analysis on the predictive ability of the multivariate approachwere characterized by using three multivariate factor basedmodels of PCR and PLS. Another development of parallel
real-time detection systems for the analysis of the products ofheterogeneously catalyzed gas-phase reactions is based on thephotoacoustic effect.[245] This method relies on the detectionof pressure pulses, which are generated by exciting a selected
type of molecule with a laser pulse. Prerequisite for thistechnique is that the molecule to be analyzed has anabsorption band in a frequency range which can be excitedby the wavelength of a laser. The absorbed energy isradiationlessly converted into molecular translation, so thatit produces, because of the pulsed or modulated laser beam, apressure pulse which is detected by a microphone. The
intensity of the pressure pulse is directly correlated to theAngew. Chem. Int. Ed. 2007, 46, 6016 – 6067

product concentration. Spatial resolution is achieved becauseof the fact that the time taken for the acoustic pulse to reachthe microphone is different for each channel. The detection
method has to be changed for molecules with very low
extinction coefficients, which can not be detected by microphones. The sensitivity can be increased by amplifying thesignals from each channel by the use of resonance tubes
integrated at the end of each tunnel in the gas outlet. Withcylindrical resonance chambers, these tubes can be arranged
in a parallel arrangement and therefore are suitable for
quasiparallel operation without complex guidance of the laser
beam. The laser modulation frequency must fulfil theresonance conditions of the tubes. The standing wave
amplified by a lock-in technique operated in the phasedependent mode is detected by simple electret microphones.
To ensure that the lock-in amplifier amplifies only the signalof one channel at one time, a multiplexer is used for switching
within the single channels, thus giving up spatial resolution
and truly parallel detection, which requires good time
resolution. Analytical evaluation of the systems and catalytic
testing of the prepared materials was performed for CO
oxidation and oxidative dehydrogenation (ODH) of ethane.
To ensure a complete parallel combinatorial workflow inthe discovery of new thin-film photocatalysts, an HT evaluation method was developed by Nakayma et al. for screening
photocatalytic activity by using a 2D pH imaging method.[246]First they generated thin-film libraries of Co-doped TiO2 byusing a laser MBE technique combined with a masking
system. Control of the composition was achieved by 2D X-ray
fluorescence (XRF) analysis. Subsequently, a thin liquid filmof ferric sulfate was placed on the library and then irradiatedwith visible light. Electrons of photogenerated electron-holepairs reduce iron(III) to iron(II) ions and simultaneously
holes oxidize water molecules to oxygen. The resulting
increase in the proton concentration in the thin liquid film
was measured using a light addressable potentiometric sensor(LAPS) developed by Hafeman et al.[247] A LAPS is an
insulated semiconductor device that responds to changes insurface potential at solid–electrolyte interfaces through theeffect of such a potential on the electric field within thesemiconductor. It is composed of a silicon substrate, a silica
thin-film, a silicon nitride insulator, and an electrolyte
containing an agar gel. The readout of the sensor at eachpoint is the photocurrent generated by a laser beam. The
photocurrent intensity depends not only on the proton
concentration at the irradiated area, but also on the appliedbias voltage. This bias is selected to show the highest
sensitivity to pH changes. For pH measurements, the photocatalyst library is simply placed top-down on the agar gel, sothat the proton can diffuse through the gel onto the silicon
nitride surface where they are absorbed. Electrochromic
counterelectrodes (CE) have also been used to monitor
pH changes in electrochemical cells. Here, a WO3-coatedconducting glass acts as an ion-insertion electrode, whichintercalates protons from the background electrolyte tobalance the charge passed by the working electrode. Owenand Hayden used this method as a parallel optical screen foranalysis of the electrochemical oxidation of methanol on Ptbased electrode arrays.

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The rapid development of biological and pharmaceuticaltechnology has posed a challenge for high-throughput analytical methods. For example, multiplexed high-performanceliquid chromatography (HPLC) and capillary array electrophoresis (CAE) have been used for the combinatorial
screening of homogeneous catalysts, but achieving a highdegree of multiplexing, such as 96 capillaries in CAE, is nottrivial.[248, 249] Thus, many attempts to find new methods forlibrary screening focus on the development of scanning
methods with rapid serial measurements of physical properties instead of parallel testing. In particular, the more complex
the technique and the smaller the scale on which the method
operates are, the more likely the serial measurement will beused.
To date, a variety of screening techniques and instrumentation using scanning-probe techniques have been developed
for the rapid characterization of structural, compositional,
optical, electrical, and magnetic properties. In particular,scanning superconducting quantum interference device(SQUID) microscopes (SSM) have been employed for the
rapid screening of magnetic properties in libraries, thereby
detecting the magnetic field emanating from the sample. The
SSM is equipped with a miniature SQUID ring of 10 mmdiameter near an edge of an atomic force microscope (AFM)
cantilever to sense local magnetic fields perpendicular to thefilm surface without the need of an external field.[250, 251] In thisdevice, the sample is set on a variable-temperature stage andmechanically scanned against the SQUID sensor with ascanning range of 10 mm V 10 mm whilst keeping the distance
between the tip and the sample constant at 5 mm. The sample
temperature has been controlled in the range 3–100 K using aheater surrounding the sample stage. The field sensitivity andspatial resolution are 50 pT in the direct current mode and5 mm, respectively. Hasegawa et al.[251] have performed HT
SSM measurements on composition spreads of the manganite
perovskites La1xCaxMnO3 and Nd1xSrxMnO3 obtained after
annealing a gradient system deposited at room temperaturefrom three precursor sources by PLD in a high vacuum
deposition system. In both types of films, SSM successfully
observed spatial variations of the magnetic field, whichcorresponds to magnetic phase transitions with respect tochemical composition. This approach was later extended to
combinatorial studies of other transition-metal oxides such as
Co-doped TiO2, Ge-based magnetic semiconductors, andHeusler alloys.[252] Another development in the field ofmagnetic thin-film analysis uses the magnetooptic Kerr
effect (MOKE) for characterization. The magnetooptic
Kerr effect as well as the Faraday effect correspond to achange in the intensity or polarization state of the light either
reflected from (Kerr) or transmitted through (Faraday) amagnetic material. Since the change in the polarization state
or intensity is proportional to the local magnetization of thematerial, it is possible to use these two effects to examine
magnetic properties. There are three principal modes ofoperation for MOKE: longitudinal, transverse, and polar
MOKE. The measurements mentioned above are based on a
new method for MOKE microscopy described by Silva andKos[253] with which it is not necessary to apply an external
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image. All previously developed longitudinal MOKE microscopy methods perturbe the magnetic structure of the sample
with an applied magnetic field. An alternative method isscanning Kerr effect microscopy SKEM, in which the sample
is excited with an AC magnetic field while the MOKE signal
is extracted from an optical detector with phase-sensitive
lock-in detection. Scanning MOKE microscopy has been used
intensively to study the magnetic properties of complex
systems by utilizing the approach of continuous phase
diagramming CPD,[146] as described previously. For example,
the alloy system CoxMnyGe1xy grown epitaxially on Ge(001)substrates by MBE was chosen by Tsui and Ryan because anovel half-metallic ferromagnetism had been predicted forthis system.[147, 254] Similarly, high-resolution scanning Hall
probe microscopy (SHPM) was used for real-time imaging of
local magnetic fields near the surface of a sample. It ischaracterizedpﬃﬃﬃﬃﬃﬃﬃ by both high magnetic field sensitivity (ca. 2.9 V
108 T Hz at 77 K) and high spatial resolution (ca. 0.85 mm).
The technique involves scanning a mm-sized Hall probe
manufactured in a GaAs/Al0.3Ga0.7As heterostructure with
two-dimensional electron gas. Sampling was successful at low
temperatures just 0.5 mm above the surface of the sample. The
Hall probe was microfabricated by optical lithography.[255]This technique has been applied to several problems in thearea of superconductivity for the characterization of thinfilms.[256]Many microscale methods can be used to study different
materials phenomena. In a similar way that SKEM and
SHPM can be applied to the study of the magnetic propertiesof thin films, microscale thermal conductivity measurements
can give new insights into order–disorder transformations andcrystallographic site preferences in intermetallic compounds,
the effect of solid–solution formation on conductivity, andcompositional point defect propensity. Both elemental substitution and the formation of point defects decrease thethermal conductivity, since both increase the scattering of thefree electrons in metals and intermetallic compounds. On theother hand, ordering in crystals decreases the electron
scattering and thus increases the thermal conductivity. In
materials with free electrons, thermal conductivity is correlated to electrical conductivity through the Wiedemann–Franz law, so it can be used to estimate electrical conductivity.
For insulating materials, thermal conductivity is carried byphonons and the Wiedemann–Franz law no longer holds. In
this case, thermal conductivity can be used to study lattice
vibrations. Zhao et al.[134, 136] developed an accurate method
for mapping the thermal conductivity with micrometer-scale
resolution by using time-domain thermoreflectance with afemtosecond pulsed laser. For this type of measurement, a
100-nm thin Al film is first sputter-coated onto a sample
acting as a transducer by absorption of the laser pulse, thus
enabling a sensitive measurement of temperature changes. At
the wavelength of a Ti:sapphire laser (l = 770 nm) used forsensing, the optical reflectivity of Al shows a strong temperature dependence as a result of a special band-structurefeature. The femtosecond pulsed laser beam is split into twoparts, a pump and a probe beam, to measure thermoreflectance. The two beams are modulated at different frequencies
to reduce possible interference. The pump beam is used to 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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ChemieCombinatorial Materials Researchheat the sample, whereas the probe beam monitors the decayof the temperature increase introduced by the pump beam.
The thermal properties of the sample are subsequently
evaluated by matching the temperature decay observed
from the experiment with those from theoretical calculations
on the basis of heat flow models.
The formation of thermal conductivity on the mm scale
was applied, for example, in the study of ordering phenomenain the Cr-Pt and Ni-Al binary diffusion couples, and revealed
increased thermal conductivity in regions where ordering,that is, phase formation occurs. This finding means themethod is well-suited to discover and locate new compounds
in phase diagrams, especially in continuous composition
libraries or continuous phase diagram approaches.
Thermoreflectance measurements are well-supplemented
by the localized mapping of YoungRs modulus using instrumented nanoindentation. During nanoindentation experiments the load and displacement of well-defined indentation
probes—usually trigonal pyramid-shaped diamonds—arerecorded continuously while they are pushed into a sample
in a controlled manner. Indentation hardness is determinedby analyzing the unloading segment of the force–displacement curve usually by using the Oliver–Pharr[257] method,
irrespective of the choice of indenter geometry. Several
corrections have been implemented into commercial nanoindentation systems to account for friction, compliance
between the indenter and mechanical system, exact contact
area, etc. Nanoindentation imposes a complex stress fieldwithin the sample, but over the years much has been learnedin regard to correlating the results with those obtained byclassical forms of mechanical property testing, so that YoungRs
modulus data measured by nanoindentation and those fromhandbooks now show good agreement. Mapping of theYoungRs modulus of the Pd-Pt-Rh ternary system as part of
the Cr-Pd-Pt-Ru diffusion multiple has been used for testing
the capabilities of the technique.[134] The modulus follows alinear relationship for Pd-rich compositions, but deviates
positively from a linear rule-of-mixtures modulus for Pt-richcompositions, which shows there is a more complex behavior
than expected from simple mixing rules. The results are,however, consistent with first principles calculations of themodulus for the binary system, again proving the usefulness ofthe diffusion-multiple approach on the validation of fundamental models of alloying.[134] The use of nanoindentation forscreening combinatorial libraries of thin films is currently stillin its infancy. For a more detailed review we recommend therecent report by Warren and Wyrobek.[258]
The number of studies combining combinatorial andnanoindentation specialities is expected to grow considerably
in the near future, because many high-technology industries,
especially the microelectronics industry, face serious integration issues related to the mechanical integrity of small
amounts of materials. Considerable work in the area ofnanoindentation has also been performed on thin films withlow dielectric constants k which play an important role as gatematerials in the fabrication of silicon chips. Alternatively,
high-throughput characterization of electric properties suchas the dielectric constant and loss tangent required that thediscovery and design of new dielectric materials can be
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performed in the radio or microwave frequency region byusing scanning microwave microscopy (SmM),[259] also calledscanning evanescent microwave microscopy (SEMM).[260] The
implementation of SmM can be formally divided into two
categories according to the style of the resonator probe: one isthe coaxial cavity resonator probe[260] and the other is the LC(where L stands for inductance and C capacitance) lumpedconstant resonator probe.[259] In both methods the linear
dielectric constant beneath the probe needle is detected as ashift of the resonance frequency; the advantage of the coaxial
resonator is its stability and the high quality of the measured
data. The lumped-constant resonator method has predominantly been used to probe the nonlinear dielectric constantby applying an additional low-frequency voltage to thesample; the advantage of this method is the extremely small
probe size which results in a high lateral resolution and asimpler principle of operation, thus making practical operations easier. A combination of the LC resonator probe withan atomic force microscope AFM is also feasible forfacilitating the simultaneous measurement of sample morphology and dielectric constant.[261] Several quantitative
measurements of the dielectric constant, tangent loss, andsurface conductivity have been reported in the characterization of combinatorial library samples with SmM. Okazaki
et al. have performed SmM scans on BaxSr1xTiO3 thin film
libraries deposited on Nb-doped SrTiO3 and showed thedielectric constant was affected by the lattice strain.[259] In
contrast, Lippma et al. observed compositional variations at
the cell edges of combinatorial perovskite thin film libraries
generated by PLD with a carousel design and linear movablemasks.[140]The analysis techniques for the screening of combinatorial
libraries mentioned above focus on the characterization ofmagnetic, electrical, and mechanical properties of materials.
Low-temperature fuel cells such as the hydrogen polymer
electrolyte membrane fuel cell (PEMFC) or direct methanol
fuel cell (DMFC) have attracted much interest in the search
for new competitive alternative energy sources. They havealso created the need for new electrooxidation catalysts withhigh efficiency as a result of the inability of existing anodecatalysts to oxidize fuels other than hydrogen at sufficientlevels. Typically, Pt-Ru alloys are used because the addition of
Ru reduces the extent of Pt deactivation caused by thepresence of CO in the fuel, which can exist either as a byproduct from upstream reforming or be formed as a partial
oxidation product during the direct oxidation of liquid fuels.
Scanning electrochemical microscopy (SECM) has been
employed for the characterization of electrochemical activity
in the search for new electrooxidation catalysts. SECM has
already been reviewed,[262] and the method has been used for anumber of combinatorial characterizations of fuel-cell catalysts.[174, 263–265] In an SECM, a fine electrode is placed near asurface by an x-y-z positioning system to measure theelectrochemical current between the tip and substrate while
using the H+/H2 redox couple to provide the potential at the
microscope tip. During the scans, the tip potential is varied toyield conditions where protons are reduced at a diffusioncontrolled rate. Variations in the tip current are monitored tocharacterize the relative reactivity of the substrate in the 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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applied conditions, that is, electrolyte, bias voltage, temperature, etc. The diffusion-limited current obtained by using
ultra-microelectrodes (UMEs) with a tip radius of 1 mm in a
1 mm solution of a typical redox species is approximately
200 pA; thus, typical SECM is highly sensitive.[262] The
operation of an SECM can be fully automated, but thereliable evaluation of materials libraries with SECM is nottrivial. A more detailed description of these can be found in
Ref. [263]. SECM has become a routine analytical techniquethat can perform a range of analyses, including topographic
imaging of conductors and insulators.
To characterize interfaces in layered systems, as forexample, in dielectric multilayer devices, to obtain important
information on interface structures and stoichiometries, it isnecessary to perform high-resolution transmission electron
microscopy (HRTEM). The problem in combinatorial material synthesis is the time needed to fabricate the individual
HRTEM specimen from a library with a large number ofmembers. To solve this critical problem, Chikyow et al.
employed for the first time a “microsampling method”
involving micromanipulation techniques together with thinning in a focused ion beam (FIB) to enable HRTEM sample
preparation to be applied as a semi-automated characterization tool.[266] Figure 19 shows schematically the workflow
for sample preparation (top) as well as an example for aninterface structure of the dielectric material SrTiO3 grown on
an As-terminated Si(100) surface at 200 8C (bottom).
To understand the phenomena at the SrTiO3/Si interface,a temperature-gradient sample-heating system consisting of

Figure 19. Top: Schematic illustration of the “microsampling method”
for the preparation of HRTEM samples. Bottom: HRTEM image of theinterface structure of SrTiO3 on As-terminated Si(100) grown at 200 8C
which reveals amorphous SrTiO3 (from Ref. [266]).

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an Nd:YAG laser point heating and thermal diffusion was
attached to the preparation chamber. The SrTiO3 layer
becomes amorphous at 200 8C with a black line running at
the interface with Si, which is indicative of arsenic, which also
diffuses into the Si substrate. Crystallization of SrTiO3 occurs
above 550 8C, but still with an amorphous interface region ofvarying thickness. It is interesting to note that the thickness of
the amorphous layer again increases above 600 8C.
Apart from the scanning probe microscopic techniques
described above, there are a number of other mapping
methods, such as scanning X-ray fluorescence (XRF) microscopy for compositional analyses, and scanning X-ray diffraction (XRD) measurements for structural characterizations of materials libraries, both of which use microfocused
synchrotron X-ray beams. Since these have now become
standard characterization techniques that are available commercially, we refer the reader to the literature.[267, 268]

5. HT Applications and Discoveries
5.1. Luminescent Materials
Phosphors, and more generally luminescent materials, are
key materials in fluorescent lighting, flat-panel displays, X-ray
scintillators, and other applications. Today, most commercially viable white-light-emitting diodes (LEDs) are preparedas phosphor-converted LEDs (pc-LEDs) through a combination of a material emitting blue light at 460 nm and a yellow
phosphor, with the blue-light-emitting material based on thewide band gap semiconductors gallium nitride or indium
gallium nitride and the yellow phosphor on the YAG:Cesystem. With the exception of the YAG:Ce phosphor andsome organic luminescent materials, there have been noreports for a long time on yellow phosphors as downconversion materials that have significant emission in the
450–470 nm emission range. Since the life-time of organicdyes is often too short, and some inorganic phosphors underconsideration pose some environmental problems both intheir preparation and in their use as they contain toxic
elements, the development of new phosphors with highquantum yields and stability, as well as no environmental
hazards is still challenging. This is especially true for thegeneration of a warm white light, as YAG:Ce emits only agreenish-yellow color that is not warm. This problem can only
be solved if the yellow phosphor is combined with anotherred-emitting phosphor to give two-phosphor blends or bydeveloping a novel long-wavelength yellow phosphor.
With a combinatorial chemistry approach Park et al.[269]found a new yellow phosphor based on silicate materials thatemitted light in the 450–470 nm excitation range. In contrast
to former investigations, for example, as in Refs. [10, 233],
quaternary libraries can also be obtained as bulk materials by
solution-based combinatorial syntheses by using a computerprogrammed liquid-dosing system instead of thin films by
evaporation techniques. After performing “finer screenings”,
the two-phosphor blend of Ba2+- and Mg2+-co-doped
Sr2SiO4 :Eu and Sr3SiO5 :Eu was found to emit broad bands
in the green and yellow spectral range. Although the quantum 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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ChemieCombinatorial Materials Researchefficiency of the Sr3SiO5 :Eu was not higher than commercial
phosphors (82 % compared to 100 % for the YAG:Cesystem), the luminescence yield of the InGaN-based twophosphor blend was slightly higher than that of the commercial InGaN-based YAG:Ce (930 mcd compared to 910 mcd
for YAG:Ce) with also slightly different CIE chromaticity
points, and good enough for many practical applications.
Still another approach for realizing white-light diodes
consists of using a soft UV-light-emitting material on
excitation at 400 nm and RGB phosphors that result intricolor or three-band white LEDs. Inorganic oxides are thebest candidates for the RGB phosphors for three-band whiteLEDs, even though their luminescence is inferior to that ofeither organic dyes or other inorganic phosphors, such as
sulfides. However, as mentioned above, organic dyes haveproblems in regard to their life-time stability, and sulfides
pose some problems in use because sulfur tends to soak into
the InGaN material, which is then followed by erosion. The
research group of Sohn employed an evolutionary optimization process involving a genetic algorithm and combinatorial
chemistry (GACC) for the development of new red[270] andgreen[271] phosphors suitable for tricolor white LEDs. Theydeveloped a solution-based combinatorial chemistry methodthat allows a 54-membered library to be generated per
generation in only 2–3 days. In the first generation, the GACC
starts with 54 randomly chosen compositions. A large numberof zero elements were introduced to reduce the composition
dimensionality. Evolutionary operations such as elitism,selection, crossover, and mutation were then applied byusing the actually measured luminescence intensities of all
members in the library to generate the subsequent generation. The selection, cross-over, and mutation rates were all
set at 100 %. After ten generations, the luminescence of thegreen phosphors was improved by a factor of about six during
the GACC process, an improvement that has, according to theauthors, never been reported before either in the case ofphosphors or catalysts.[271] Recently, a strong red and green
luminescence was also found in rare-earth-calcium oxyborate
systems. A strong dependence of the luminescence intensity
on chemical composition was found in amorphous, thin CCS
film libraries composed of Y-Ca-B and Eu-Ca-B mixed oxides
prepared by combinatorial pulsed laser deposition.[272]
Despite the life-time problems of OLEDs, they haveundergone tremendous progress over the last decade because
they may find application in the next generation of flat-paneldisplay technology. The disadvantages are balanced by anumber of advantages, that is, their relatively low power
consumption, wide viewing angle, ease of fabrication, color
tenability, and their ability to be made on plastic substrates.[236] A typical OLED consists of a hole-transportlayer (HTL) and an electron-transport layer (ETL) sandwiched between two electrodes, one metallic and one madefrom a conducting glass to allow the transmission of light. The
performance of OLEDs can be increased considerably if
luminescent organic dyes are incorporated as dopants intoeither the HTL or ETL layer, or both, during fabrication.
Many factors, including dopant level, placement of the doped
layer(s) in the device structure, dopant concentration, host–
guest compatibility, thickness of the individual layers, elecAngew. Chem. Int. Ed. 2007, 46, 6016 – 6067

trode materials, and interfaces between them, influence theperformance of the OLED, thus offering a wide field for
combinatorial optimization with high-throughput methods.
Sun and Jabbour[236] used spin-coating from solution todeposit HTLs of polycarbonate (PC) as the host for rubrenedye (5,6,11,12-tetraphenylnaphthacene) molecules. In the
ETL, the green-light-emitting material 8-trishydroxychinoline aluminium (Alq3) was incorporated by vacuum deposition and the layer thickness varied by a sliding-shutter
mechanism moving in a stepwise fashion at a deposition
rate of 0.8 T s1. A maximum of the external quantum
efficiency of 1.2 % at 10.8 V applied electric field was foundat an Alq3 thickness of 60 nm. The authors proved theusefulness of HTTs for the fabrication of OLEDs by
optimizing the dopant profile in a given host, in this casethey focused on the red-light-emitting material 4-(dicyanomethylene)-2-tert-butyl-6(1,1,7,7-tetramethyljulolidyl-9-enyl)-4H-pyran (DCJTB) in an Alq3 host material. The device
structure as well as the quantum yield results revealed asignificant improvement over the rubrene OLEDs(Figure 20). In a similar approach, Schmidt and co-workers
described a combinatorial vapor deposition technique to

Figure 20. Top: Typical structure of a red-emitting OLED with thechemical structures of the molecules used for device fabrication.
Bottom: External quantum efficiency versus bias voltage for OLEDs
having 1.5 %, 2 %, 2.5 %, and 2.8 % DCJBT in an Alq3 host (fromRef. [236]).

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efficiently screen new materials and configurations in thinfilm multilayer OLEDs.[273]Besides organic dyes, other phosphors based on inorganicoxides have also been tested in regard to their use in flatpanel displays, such as field-emission displays (FEDs) andplasma display panels (PDPs). Thus, borophosphate phosphor
libraries doped with rare-earth elements have been generated
by a scanning multi-inkjet delivery system for solution-based
combinatorial syntheses followed by parallel screening of thesynthesized libraries for VUV photoluminescence on a homedesigned cathode gas Xe/He or Xe/Ne discharge lamp.[274]
New ZnO-based phosphors have been discovered andoptimized by using combinatorial methods to fabricate
libraries of thin films by PLD on sapphire or Pt-coated siliconwafers as substrates.[275] ZnO has been doped with theelements (Y,Eu), V, W, (W,Mg) in such amounts that it has
to be assumed that almost every ternary or quarternarycompound of the phase diagrams is observed as a mixture
with other phases in the phosphors despite the fact that, forexample, X-ray diffraction experiments did not allow a
positive identification of particular vanadate phases becauseof the low crystallinity of the samples. The authors found thatthe new phosphors had high low-voltage cathodoluminescence efficiency that potentially will allow their use in flatpanel display and lighting applications.

5.2. Other Optically Functional Oxides
ZnO has been used quite commonly as a base material in a
number of combinatorial investigations that aimed to discover and optimize new transparent conducting oxides(TCOs). TCOs play a critical role in many current andemerging optoelectronic devices such as OLEDs (see previous section). The unique combination of high transparency
in the visible region of the solar spectrum (typical transmittance > 85 %) together with high electronic conductivity(typically > 1000 W1 cm1) also makes them ideal for applications such as transparent electrodes in liquid-crystal
displays (LCDs) and solar cells. Commercially, the TCO
market is dominated by Al-doped ZnO (AZO), the system
In2O3/SnO2 (ITO), and F-doped SnO2, with ITO offering thebest combination of high optical transparency together withhigh electrical conductivity. As the displays get larger andlarger and the reaction times have to be faster and faster, theneed for new materials has to be met by improved formulations—again offering combinatorial high-throughput methods the possibility of an accelerated investigation of the large
TCO parameter space. Taylor et al. have grown compositionally graded, combinatorial libraries of indium-doped ZnO(IZO) by cosputtering ZnO and In2O3 on glass at 100 8C withan In content ranging from 5 to 50 %.[276] They were able tocover almost 50 % of the ZnO-In2O3 phase space with only
three depositions. The highest conductivity was found insamples with 48 % In. Quite high electron mobilities ofgreater than 25 cm2 V1 s1 and optical transmittances greaterthan 80 % were found for the samples with a high In content,
as well as a distinct jump in mobility between 20–25 % In. The
authors considered these properties sufficient for incorpora-

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tion into the flat-panel displays. Glass materials have also
been studied to evaluate time-temperature-transfer (T-T-T)
diagrams by using a combinatorial evaluation system developed by Inoue et al.[277, 278] By using a CCD camera (together
with a computer system compiling the glass-forming regions)to analyze the crystallized area in the glass sample libraries
annealed simultaneously in a furnace with a temperature
gradient, they were able to reduce considerably the laborious
routine work for the preparation and screening, relative to aconventional method. The effect of post-processing steps suchas plasma treatment on sol–gel-derived semiconductor libraries were studied by Rantala et al.[279] By doping the SnO2
with Sb as well as treatment with a radio-frequency argon
plasma, they were able to increase the conductivity of thelayered glassy SnO2 films considerably. A sol–gel route has
also been used to produce arrays of Al-doped ZnO as
potential TCOs through hydrolysis of a zinc acetate/ethylene
glycol precursor in aluminum nitrate solutions.[280] Potential
dielectric materials have been synthesized automatically by
sol–gel procedures, and the sols deposited on Si libraries witha pipetting robot. After calcination, the libraries wereanalyzed by automated AFM in the ultrasonic piezo mode.[281]5.3. Dielectric and Ferroelectric Materials
A systematic approach for the discovery of new dielectricmaterials has already been discussed in the investigation of
the crystallization in amorphous Zr-Si-O dielectric compounds by using the co-deposited continuous composition
spread approach.[127] A “generalized” CCS approach thatallows the simultaneous study of the combined effects of two
parameters, which are imposed as spatial variations along two
different orientations of a planar substrate (such as chemicalcomposition, film thickness, growth temperature) was appliedby Christen et al. for the epitaxial growth of libraries of theelectrooptic materials SrxBa1xNb2O6 (SBN) on Mg(001) by
PLD.[137] SBN is an attractive ferroelectric material, because itshows an exceptionally large electrooptic coefficient r33, thus
making it a potential material of choice for miniaturized
electrooptic modulators, real-time holography applications,and information-storage technologies. By changing the Sr to
Ba ratio in SBN, the r33 coefficient can be varied, and values
30–40 times larger are reached than are observed for the
congruently melting LiNbO3, the current industry standard.
They clearly observed variations in the optical and structuralproperties as a function of growth temperature for a series of
Sr0.5Ba0.5Nb2O6 thin films on MgO(001) substrates depositedat different growth temperatures spanning a range of 500 8C.
The same research group extended the CCS approach to thegrowth of epitaxial heterostructures, that is, superlattices
consisting of repeated stacking of SrTiO3 and SrxBa1xZrO3
layers, where the parameter x varied continuously across the
sample. The periodicity was chosen to be 200 T, withsuperlattice peaks in the X-ray scans clearly proving theformation of the desired structure. The corresponding titanate
SrxBa1xTiO3 was at the center of interest in the investigations
performed by Xiang, who developed a strategy to lower the
leakage current in next-generation integrated capacitors by 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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Angewandte

ChemieCombinatorial Materials Researchengineering Schottky barriers at the interfaces between boththe electrodes and the dielectric material. However, theincorporation of Schottky barriers could degrade otherimportant device performances, such as charging time. So
the best approach for a reduction in the leakage current is to
directly reduce the conductivity in the dielectric material
itself.[282] To construct a capacitor device library Xiang
deposited a 100–200-nm-thick amorphous layer of
La0.5Sr0.5CoO3 (LSCO) from a stoichiometric target at room
temperature using PLD. After annealing the sample at 850 8C
to form an epitaxial LSCO bottom electrode, the substrate
was remounted in the PLD chamber to deposit different host–dopant combinations in three different host regions (BaTiO3,
Ba0.7Sr0.3TiO3, and Ba0.5Sr0.5TiO3) using 2D high-precision
deposition masks. In the orthogonal direction, the substrate
was divided into separate Ce, Y, La, and W dopant regions,each containing 0–3 % dopant added as a gradient to each
host. In a complex sandwich structure with dopant layers
embedded between pure and identical host layers, Pt counterelectrodes were deposited with a lithographic mask after ahigh-temperature ex situ annealing to interdiffuse the dopants and to ensure epitaxial growth. The resulting library was
subsequently characterized by Rutherford back scattering(RBS), to evaluate the degree of interdiffusion, and by
scanning evanescent microwave microscopy (SEMM), to
determine the dielectric constants.[142] The HT screening of
the dielectric constant and loss of the dielectric constant of asingle phase strip is shown in Figure 21.

programmed to perform weighing, pipetting, and mixing of
the starting materials with the help of the corresponding
auxiliary tools. After drying and calcination, the products
were characterized by means of X-ray diffraction by using a
combinatorial X-ray diffractometer developed for HTS andequipped with a position-sensitive proportional counter(PSPC) as well as a movable x,y translation stage. Powder
XRD data revealed that the products were single or multiphase and represented up to six different crystal structures:spinel solid solutions LiFe5O8-Li4Ti5O12, ramsdellite solid
solutions Li2Ti3O7, pseudobrookite Fe2TiO5, rocksalt-typesolid solutions between LiFeO2 and Li2TiO3, and rutile
TiO2. As reported by other authors, ramsdellite-type
Li2Ti3O7 shows excellent charge and discharge cycling performance when used as an electrode material in lithium
batteries. A Cr-doped variant of the same structure typereveals reversible deintercalation and intercalation of Li ions.
To date, there are no reports of Li-Ni-Ti oxides with aramsdellite structure. Alternatively, the robotic system mentioned above was connected to a combinatorial electrodearray of 16 current collectors, to which counterelectrodes
were attached.[284] Two multichannel potentiogalvanostats,each of which had eight channels, were used as current
sources, and all the cells operated simultaneously at constantcurrent. The system was used to characterize LiCoO2 libraries
prepared from aqueous LiOH solutions and aqueous CoO
particle suspensions by the robotic system measuring charge–
discharge curves. An overview of the electrochemical characterization system is given in Figure 22.
LiCoO2 was also the subject of a combinatorial approachcalled “combinatorial computational chemistry”, which was
proposed by Miyamoto and co-workers.[118] They investigated
the structural properties of lithium transition metal oxides

Figure 21. High-throughput screening of the dielectric constant anddielectric loss from a single strip from a 5500-member dielectricmaterials library (from Ref. [142]).

5.4. Battery Materials
Systems containing TiO2 were not only investigated as
dielectric or ferroelectric materials, but also in combination
with lithium oxide as a component for solid-state battery
applications. Fujimoto, Takada et al. prepared pseudoternarycompounds of the Li2O-X-TiO2 system (with X = Fe2O3,
Cr2O3, and NiO) by using a fully automatic combinatorial
robot system that enables a complete combinatorial workflow.[283] Either aqueous salt solutions (Li, Cr, Ni) or slurries ofnanoparticles suspended in water (Fe, Ti) were used as
starting materials. The robotic arm of the system wasAngew. Chem. Int. Ed. 2007, 46, 6016 – 6067

Figure 22. Combinatorial electrode array for testing electrode materials
for batteries (top) and schematic cross-section (bottom; from
Ref. [284]).

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LiMO2 (M = 3d transition metal) with a layered rocksalt-type
structure, which revealed a poor reversibility of the charge–
discharge cycle of LiNiO2 because of large structural changes
resulting from significant differences in the ionic radii of Ni3+
and Ni4+. This effect can be reduced through doping of
LiNiO2 with other 3d transition metals, such as Mn. Whitacre
et al.[164] described a methodology for batch-fabricating hundreds of submillimeter-sized thin-film solid-state batteries
with spinel-type LiyMnxNi2xO4 cathodes, sputtered lithium
phosphorous oxynitride LiPON as the electrolyte, andevaporated, micropatterned Li metal as the anode layer.
The process flow for Li anode fabrication has already beenshown in Figure 16. It was found that the microfabricatedbattery assemblies had similar electrochemical performanceparameters as bulk-fabricated powder electrodes with comparable composition ranges. Dahn et al. have applied HT
methods to study thin-film alloy libraries of Sn, Co, and Cu forpotential applications as anode materials in Li ion batteries byelectrochemical methods and XRD. Amorphous phases seemto be associated with a good performance. The addition ofcarbon was found to positively affect the charge–discharge
cycling and stability.[285]5.5. Magnetic Materials
Perovskite manganites are highly correlated electronicsystems that reveal a number of interesting optical, electrical,
and magnetic properties as a function of the doping concentration, ionic radii, and other parameters which are accompanied by electronic phase transitions such as spin-orbital
ordering and smectic phase formation. Xiang also applied his
CPD approach to rare-earth perovskite manganites of theformula RE1xAxMnO3, where RE = La, Nd, Eu, Gd, Tb, Er,
Tm, and Yb, A = Ca, Sr, and Ba, and x = 0–1.[144] Several
different continuous phase diagrams were generated on
15 mm V 15 mm large single-crystal substrates (SrTiO3(100)or NdGaO2(110)) by using an eight-target carousel and a highprecision in situ linear shutter system for gradient depositionsof the precursors. The electronic and magnetic properties ofthe postannealed film were characterized by SEMM[144] andSSM,[251] respectively. The SSM was equipped with a minature
SQUID ring with an outer diameter of 10 mm near an edge ofan AFM cantilever to sense the local magnetic field Bz
perpendicular to the film surface with and without a magnetic
field. Figure 23 shows 2D magnetic images observed by SSM
at 3 K within a scanning range of 300 mm V 300 mm of acomposition spread of La1xCaxMnO3 films with various
values of x. In general, a ferromagnetic material is divided
into domains with different magnetic axes instead of being
homogeneously polarized. In thin films, the magnetic
moments tend to lie parallel to the film surface because thisreduces the magnetostatic energy. In this case the domainboundaries emit or absorb magnetic fields, which is detectedin SSM as positive or negative Bz and indicated as white or
black regions. Regions inside the domains are, in contrast,
gray colored.
If one observes experimentally both the magnetic domain
width d as well as the maximum field Bzmax  Bz(0;h) at a

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Figure 23. 2D magnetic images of a compositions spread library of
La1xCaxMnO3 (LCMO, with x = 0.078–0.888) thin films observed by
SSM at 3 K and different magnetic fields Bz. Scanning areas are
300 mm P 300 mm for all images (from Ref. [251]).

probe–sample distance h and at the domain boundary d = 0,
the saturation magnetization Mz can be calculated. From themeasurements it is evident that Ms shows a local minimum at
x = 0.2, which is equivalent to a phase boundary between
ferromagnetic insulator (FI) and ferromagnetic metal (FM)states and is consistent with the magnetic properties of bulk
materials in this compositional range. In contrast, the SSM
results differ remarkably from those of bulk studies for x >0.5, with the SSM measurements strongly indicating that aphase separation into ferromagnetic and charge-order nonmagnetic phases occurs in this compositional range.[251]Apart from manganites, alloy systems in particular havereceived much attention in the development of new magnetic
materials by combinatorial synthesis because of the ease ofevaporation of metallic elements in PVD deposition chambers by every kind of evaporation source, that is, Knudsen
cells, e-beam evaporators, as well as magnetron sputteringsystems. Specht et al. developed a technique based onsynchrotron radiation that allows for the rapid structuraland chemical characterization of ternary alloys over a wide
range of composition by XRD and fluorescence measurements.[148] By this technique they were able to construct thephase diagrams and contour maps of lattice parameters fromisothermal sections by examination of 2500 compositions of
the ternary metallic alloy system Fe-Ni-Cr in a single experiment that took about 4 h. By using a high-flux synchrotron
beamline, diffraction patterns were recorded with a 1024 V
1024 pixel X-ray CCD camera with a pixel pitch of 60 mm thatwas located 10 cm behind the sample. Typical measured phase
diagrams of libraries annealed at different temperatures(samples A, B) and generated with different depositions
sequences (samples A, C) are shown in Figure 24. Each layer
was grown with a linear layer thickness gradient by a sliding
shutter driven by a stepping motor and rotated by 1208 after
each layer for deposition of the next layer, thereby resulting ina triangular arrangement of the three elements in the phase
diagram. Interdiffusion of the elements and phase formation
was achieved by a postannealing step. As samples A and C

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ChemieCombinatorial Materials Research

Figure 24. Measured phase diagrams of the ternary system Fe-Ni-Cr at
different annealing temperatures (samples A, B) and for different
deposition sequences (samples A, C; from Ref.[148]).

were deposited with different layer sequences, but thediffraction data reveal similar phase diagram sections inFigure 24, equilibrium data were obtained.
“Giant” magnetostriction alloys such as TbFe2 (terfenol)
or Tb0.3Dy0.7Fe2 (terfenol-D) can reach strains of 0.1–0.2 %,while those of shape-memory alloys (SMAs) can easily
exceed 1 %. As already mentioned before, the exchangespring mechanism of Kneller and Hawig describes how theswitching fields can be reduced and strain susceptibility
enhanced.[155] Ludwig and co-workers deposited TbFe/FeCoand FePd/Fe multilayers by magnetron sputtering on Si(100)substrates to study the role of magnetostatic and magnetoelastic interactions in exchange-spring multilayers to understand the microscopic details of the exchange spring.[156] The
systematic investigation of the multilayers as a function of thenumber N of bilayers showed that in the case of (TbFe/
FeCo)N bilayer stacks, the coercivity of the films drops
abruptly with increasing number of bilayers to a saturation
value of about 60 Oe when the number of bilayers is greaterthan 10. Compared to a single FeCo film with a coercivity of
about 168 Oe, the coercivity of 112 Oe of a multilayer withjust two bilayers (TbFe/FeCo)N=2 is significantly lower. The
authors explained this by considering the field-dependent
micromagnetic structure of the bilayer stack, as depicted in
Figure 25. With saturation in the negative direction, thereversal of the magnetization in the multilayer occurs by
nucleation of “twin” domain walls (Figure 25 a). As the fieldstrength increases (from 117 up to 118 Oe), the reversal
proceeds by lock-step motion of the twin wall across theentire sample (Figure 25 b). A magnified view of the twin
domain walls clearly shows its complex nature in the form ofNPel wall and quasi NPel wall combinations with a sandwich
structure (Figure 25 c). The solid arrows in Figure 25 d, which
reveal schematically the magnetostatic coupling between
stray fields of domain walls in different layers, denote therotation of the magnetization within a domain wall, whereas
unfilled arrows indicate the stray field emanating out of theAngew. Chem. Int. Ed. 2007, 46, 6016 – 6067

Figure 25. a,b) Motion of twin-domain walls in (TbFe/FeCo)N=2 bilayer
stacks as a function of the field. c) Magnified view of the twin walls.
d) Schematic view of the magnetostatic coupling between stray fieldsof the domain walls in different layers (from Ref. [156]).

NPel walls that causes a fluctuation of the magnetization in
the adjacent layers, thus giving rise to quasi-NPel walls. The
formation of such twin walls leads to an overall decrease in
the wall energy and thus coercivity. Multilayer thin-film
libraries prepared by combinatorial deposition have also beenused for the investigation of hard magnetic properties in the
Fe-Pt system.[150] Additionally, Fe50Co50/Co80B20 multilayerswith various FeCo layer thicknesses have been studied fortheir applicability in microsensors and high-frequency devices.[151]Tsui and Ryan compared the deposition and co-deposition of multilayers by using combinatorial MBE techniques togenerate continuous phase diagrams (CPDs) by considering
the Co-Mn-Ge system as an example.[147] For this purpose,
multilayers containing monolayers and submonolayers of Ge,
Mn, and Co were deposited sequentially by using a combination of shadow masks, sample rotation, and pneumatic
source shutters to obtain alloys by so-called artificial alloying
and sequencing by interdiffusion of the elements. The multilayer approach also has special advantages in the productionof metastable alloys, in particular, to impose an artificial
stacking sequence along the growth direction, which can be
critical for setting up desired properties such as half-metallic
behavior. Half-metallic behavior together with a structuralcompatibility for epitaxial growth on Si, Ge, and GaAs
substrates has been predicted for Heusler alloys,[286] such as
Co2MnGe, which is an interesting material for spintronic
applications. Films of complete ternary combinatorial libraries (for example, CoxMnyGe1xy) or two-variable libraries
sliced through the ternary system (for example,(Co1xMnx)1aGea) have been produced with 25-T thickcapping layers for ex situ measurements.[147] Scanning
RHEED was used to track the structural evolution of thelibraries in situ and Rutherford back scattering spectroscopy
used to measure the compositions ex situ. Additionally,magnetooptic Kerr effect (MOKE) imaging and scanning
SQUID magnetometry was applied to study magnetic properties. A room-temperature magnetic phase diagram of a 250T-thick combinatorial Co-Mn-Ge library grown on Ge(001) 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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by MBE, illustrated as the differential scanning MOKE
intensity at  5 kOe (that is, DI = I(5 kOe)I(5 kOe)), isshown in Figure 26. Yellow and red areas correspond to themagnetic regions. The directions of the magnetic field andFigure 26. Magnetic phase diagram of a 250-Q-thick combinatorial
library of Co-Mn-Ge measured at a differential scanning MOKE
intensity at  5 kOe (from Ref. [287]).

light polarization were vertical and the horizontal, respectively. The inset in the right section of Figure 26 gives moredetailed information on the indicated section. The color scale
bar represents the coercive field strength in Oe. Other Gacontaining phase diagrams, that is, Ni-Mn-Ga, Co-Mn-Ga,
and Co-Ni-Ga, were investigated by Matsumoto and coworkers by using a combinatorial strategy to quickly survey
the vast compositional landscape of Heusler alloys andrelated compounds by co-deposition of different elements ina triangular configuration.[252]of the Pt metal was also attempted through combination of Pt
with oxides such as WO3 and MoO3.[288] Several explanations
have been proposed for the origin of the synergism in thenoble metal/base metal oxide system:[289] 1) the bifunctional
activation of carbon monoxide and oxygen or water molecules on adjacent, but different active sites, 2) the creation ofa new site for the activation of CO at the interface, 3) the
relaxation of the strong CO-Pt adsorption through anelectronic interaction. Furthermore, for example, three different aspects can be considered for the electronic interaction:formation of a Schottky junction; electron exchange withdonor and acceptor surface states; and modification of theredox properties of the supported metal cluster by the acid–base properties of the oxide support. Kobayashi et al.
proposed that not only a comparison of the catalysts in one
reaction, but also the comparison of interrelated reactions
with a common catalyst library generates important information for elucidating the catalytic synergism.[289] They therefore
studied the effect of a given set of catalysts in one libraryconsisting of 5 different noble metals and 12 different basemetal oxides on both the water gas shift reaction and thesteam reforming of methanol, and compared the results. Theirfindings of the first screening stage are summarized in
Figure 27. The high activity of Pd/MnO2 for both reactions

5.6. Fuel-Cell Materials
Polymer electrolyte membrane fuel cells (PEMFCs, often
also called proton exchange membrane fuel cells) haveenormous potential as stand-alone power sources. Theenergy conversion efficiency of a standard fuel cell is directly
governed by the activity of the anodic and cathodic materials,
which are targets for development in PEMFC technology.
Combinatorial approaches are attracting increasing attention
as a novel and powerful methodology for the high-speed
survey and optimization of new functional materials for fuelcell technology.
Among the PEMFC catalysts examined so far, a highperformance can frequently be achieved by the catalytic
synergism of noble metal/base metal oxide combinations or
precious metal alloys. For example, support metal oxides areoften selected to suppress carbon deposition during hydrocarbon reforming, a feature which can be related to the acid–base properties of the oxides. The selectivity for the formationof hydrogen in the product is also strongly affected by themetal oxide support. The strong acidic and corrosive conditions generated by the nafion polymer electrolyte also limits
the materials that can be used in PEMFCs. PtRu alloys
usually show the highest performance among the electrocatalysts examined to date. Improvement in the CO tolerance

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Figure 27. Hydrogen production from the water gas shift reaction (top)and methanol steam reforming (bottom) measured on a library of
precious metal/metal oxide combinations (from Ref. [289]).

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is noticeable, whereas the second best catalyst system isdifferent for the two reactions: Ir/CeO2 for the water gas shift
reaction and Ru/CeO2 for the methanol steam reformation.
On the basis of these results, the authors concluded that thecatalytic synergism is not a simple reflection of the physicalstructure of the catalyst but that the catalytic reaction also
contributes to the synergism. If the elementary steps in thewater gas shift reaction and methanol steam reformation are
considered, it can be seen that the activation of water, theoxidation of a carbonyl group, and hydrogen recombination
are involved in both reactions. One difference, however, isthat the water gas shift reaction does not involve the CH
dissociation step. Thus, analogies and differences between
related reactions with common elementary steps can offer the
chance to elucidate the synergistic mechanism.
Other authors have reported on the application of thescanning electrochemical microscope (SECM) for spatiallymapping the kinetics of heterogeneous electron-transfer
reactions to enable screening measurements to be performed
for combinatorial studies on electrooxidation catalysts.[265] For
this Jayaraman and Hillier used multielement band electrodes
containing various compositions of binary PtxRuy and ternary
PtxRuyMoz alloys deposited by pulsed electrochemical deposition onto patterned substrates. After verification of thecatalyst compositions through a combination of Auger
electron spectroscopy and energy-dispersive X-ray spectroscopy, the activity in regard to the hydrogen oxidation reaction
was probed in sulfuric acid solutions using a scanningmicroelectrode tip placed in proximity to the catalyst surface
and recording the cyclic voltammograms at selected points on
the band electrodes. Interestingly, the cyclic voltammetry
curves of the PtxRuyMoz electrodes differ from those of pure
Pt, pure Ru, and pure PtxRuy electrodes. The addition of Mo
produces an additional electrochemical current in the potential range between 0.3 and 0.6 V. This observation suggeststhat the Mo component is undergoing an oxidation/reduction
process. The Pourbaix diagram for Mo indicates that a stable
oxide with a composition of MoO2 or MoO3 (including theMagneli phase region) will form in this pH range. The authors
thus speculated that these Mo-containing electrodes would be
able to dissociate water and provide hydroxide or oxidesurface species with the ability to oxidize carbon monoxide at
low potentials. This finding needs to be highlighted, particularly in view of the catalytic synergism discussed above. The
authors are currently extending their methodology to examine additional regions of composition space in the PtxRuyMoz
system as well as multicomponent electrodes with additional
metals that exhibit stable oxide formation at low potentials.
Catalysts based on Pt-WO3 were also prepared by McFarlandand co-workers by using automated systems for highthroughput electrochemical synthesis and then screened fortheir applicability as fuel-cell electrooxidation catalysts,
particularly as DMFC catalysts.[290] The same research group
investigated Au nanoparticulate electrocatalysts on TiO2
substrates for the electrooxidation of CO by using a 96-wellpolypropylene reactor block assembly, as mentioned
before.[171]Low-temperature fuel cells typically rely on platinum
alloy catalysts, such as Pt-Ru. Despite their comparitively
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high complexity, high-throughput methods for the search ofalternative electrode materials were developed early on in thefield.[291] Mallouk, Smotkin, and co-workers have recently
compared four of the HT electrochemical methods (linear
sweep voltammetry (LSV), optical screening, array fuel cell
testing, and single fuel cell testing) developed for DMFC
applications through a ranking of the anode catalysts. Theycame to the conclusion that the LSV of disk electrodes is mostreliable in applications at 60 8C.[292]Guerin and co-workers developed both hardware andsoftware for the fast sequential measurement of cyclic
voltammetric and steady-state currents in 64-element halfcell arrays.[293] It is interesting to note that the 64-cell array
uses only one reference and one counterelectrode (Figure 28).
This setup allows the parallel screening of all 64 electrodes
and catalysts deposited on these electrodes for various fuelcell applications. Peak potentials, currents, and charges can bemeasured in a single experiment.

Figure 28. Electrochemical 64-cell arrangement with a single reference
and counterelectrode (from Ref. [141]).

The use of array fuel cells for precise HTS of libraries ofmembrane electrodes for hydrogen cathode catalysts for
PEMFCs as well as for DMFC anode catalysts has been
described by Smotkin et al.[294] The libraries were prepared by
ink-jet delivery of metal salts on carbon paper, and subsequently reduced by borohydride solutions. The authors alsoemphasized the potential problems and pit falls in HT
searches for fuel-cell electrodes. On arrays of 100 electrodes
Hayden and co-workers studied particle size effects of Au on
TiO2 catalysts for electrocatalysis (oxygen reduction). The HTdata were validated with measurements on rotating disk
electrodes (RDE) and the Au particle size distribution wasdetermined by TEM measurements. The best electrocatalytic

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performance was achieved with particle sizes in the range of
2.5–3 nm.[295]5.7. Coating Materials
There are several different classes of coatings, but
combinatorial approaches have been applied primarily
either to hard coatings or coatings based on polymericmaterials.
The variety of process parameters during the PVD ofmetastable hard coatings make a conventional approach forthe development of new coatings time-consuming andexpensive, while the increasing complexity of modern coatings has led to the demand for a cost-effective method in thedevelopment of new products for the advanced materials
industry. These two factors have generated the need for theadaptation of combinatorial techniques to the specificrequirements of the coatings industry. Hard coatings in theform of 1D or 2D laterally graded coatings such as (Ti,Al)N,(Ti,Al,Hf)N, or (Ti,Al,Si)N, which were deposited by meansof reactive magnetron sputtering and plasma-enhanced
chemical vapor deposition (PECVD) by using a composition-spread approach, were investigated with respect to therelationship between structure, composition, and the desired
material properties by the research group of Cremer and
Neusch-tz.[268, 296–298] A combination of electron-probe microanalysis (EMPA) and scanning X-ray diffraction was
employed as a fast and reliable way of investigating thecomposition, crystal structure, and texture of the material
libraries. Based on these investigations, the influence of Hfand Si additions on the structure, texture, and grain size of(Ti,Al)N hard coatings was determined.
Besides hard and polymeric coatings, metallic overlayers
on substrates have also attracted attention for special
applications. An HT concept for studying and optimizing
the composition and thickness of potential switchable mirror
materials (for example, Pd on Mg-Ni) was introduced byBorgschulte et al.[299] Switchable mirrors are shiny metal alloy
films on glass, which become transparent upon exposure tohydrogen. Potential applications include windows for buildings and vehicles or visors for helmets. The studies revealed
strong metal–support interactions as the origin of theobserved thickness dependence of the switchability andreversibility.

5.8. Membranes
Vankelecom, Jacobs, and co-workers have successfully
developed a 16-fold HTT to screen for potential membranematerials.[300] In the validation experiments, a membranedevelopment was carried over four generations. Genetic
algorithms were used to drive the development of polyimidebased nanofiltration membranes by variation of eight parameters (polyimide, NMP, CH2Cl2, THF, 1-hexanol, acetone,water, 2-propanol) comprising the membrane casting solution. The performance of the membrane was tested at apressure of 10 bar with a methyl orange indicator in 2-

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propanol. After a total of only 192 membrane preparations in
4 generations, several new membranes outperformed all 3
commercial reference membranes (Starmem 120 and 240,
MPF-50) in terms of permeance and retention.[300, 301] With thehelp of genetic algorithms, novel polyimide-based solventresistant nanofiltration membranes have also been developedby HT techniques.[302]5.9. Polymers
Polymeric materials, polymerization catalysts, and polymer blends belong to the group of complex materials
originally believed not to be suitable for HTT. This originalassumption was not without reason, since polymer properties
depend, among other things, also on the molecular weight,
and measurements of molecular weight distributions used totake hours. Many organometallic polymerization catalysts aswell as many polymerization processes are highly sensitive toimpurities, oxygen, and moisture. The reproducible screeningof many catalysts or polymerization processes was viewed to
be technically impossible. Many mechanical or opticalpolymer properties, such as scratch resistance, hardness,elasticity, transmittance, and reflectivity, are bulk properties,
which are highly dependent on the blend composition andtemperature treatment, which do not lend themselves easily
to tiny samples on libraries. Despite these problems, thedevelopment of HT techniques for polymer research has beenvery successful and has led to the first commercial applications. Today HT techniques are applied in many fields ofpolymer research.
5.9.1. Polymerization Catalysts for Polyolefins
The application of HT techniques to the identification ofpolymerization catalysts began early on in the field. The
scientists at Symyx built the first parallel polymerization
reactor and reported in 1998 the discovery of new ethylene
polymerization catalysts based on Ni- and Pd-diimine complexes.[303] The use of a fully integrated HTT for primary andsecondary screening as well as rapid polymer characterization
was reported in 2003 and led to the discovery of Hf complexes
for the polymerization of higher olefins.[303–305] M-llen and coworkers reported the development of a split&pool concept
for the development of catalysts for olefin copolymerization
reactions, where fluorescence microscopy was used to screen
for the polymerization activity of immobilized Zr catalysts on
silica beads tagged with rylene dyes.[306] A new family of Cr
catalysts for ethylene polymerization was discovered by
Maddox and co-workers using HTT.[307] They found very
active catalysts in the ligand parameter space of salicylaldimine with bulky o-phenoxy groups and small imine substituents. Catalytic activities of 7000 g mmol1 h1 bar1 with Mw of1100 g mol1 and activites of 95 g mmol1 h1 bar1 with Mw of
0.93 V 106 g mol1 were reported. Figure 29 and Figure 30
show the screening results and the ligand structure of one of
the best catalysts.
In a collaboration between British Petroleum and Imperial College, HTS was applied to the search for new Cr

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Figure 29. HTS results for ethylene polymerization (from Ref. [307], reproduced with permission from The Royal Society of Chemistry).

Figure 30. Typical polymerization catalyst with a bulky triptycenyl
substituent (from Ref. [307], reproduced with permission from The
Royal Society of Chemistry).

catalysts for ethylene polymerization.[308] The study was basedon the above discovery of salicylaldimine ligands. In the
primary screening, a library of 205 such Cr catalysts was tested
in a 24-well reactor under standard polymerization conditions. Subsequent libraries were used to amplify leads and thehits were validated under conventional conditions. Linear
high molecular weight polyethylene with catalytic activities of3000 g mmol1 h1 bar1 was obtained by using bidentate 6anthracenylsalicylaldiminato systems with alkylimino donors.
A new class of tridentate o-tryptycenyl-substituted salicylaldimine ligands were discovered, which are thermally robust
and oligomerize ethylene with catalytic activities of
10 000 g mmol1 h1 bar1 to provide linear a-olefins.
Adams et al. reported on the discovery of new imidotitanium catalysts for the polymerization of ethylene.[309] The
catalysts were prepared by semi-automated parallel syntheses
from 50 commercially available amines. While details on thepolymers and catalysts are given, no details on the highthroughput polymerization screening methods used areprovided. At 100 8C and 7 bar ethylene, activities of up to
10 000 mol mmol1 h bar (Mw 274 000 g mol1) or Mw of 1.5 V
106 g mol1 at an activity of 4800 were reported.
A robust system for the synthesis and testing of ethylene
polymerization catalysts has been described by Schunk andco-workers.[310] Catalysts based on Fe, Ni, and Cr wereprepared through combinatorial ligand variations with thehelp of a synthesis robot (Figure 31). Polymerizations wereAngew. Chem. Int. Ed. 2007, 46, 6016 – 6067

Figure 31. Activities of FeII catalysts with diimine or diiminopyridine
ligands in the polymerization of ethylene (from Ref. [310]).

carried out in a multiclave reactor (8 V 30 mL) at 50 8C and10 bar, and the resulting polymers were characterized by GPC
and DSC. The best catalysts provide activities of nearly
140 kg(PE) mmol1 h with an Mw value of > 20 kDA. An Hfbased metallocene-free catalyst for the production of highly
isotactic polypropylene has also been discovered through theapplication of HT techniques.[311]
HTTs have been developed to screen for mixtures of threecatalysts for ethylene polymerization.[312] Unusual catalysts
mixtures were discovered, which produce branched polyethylene, which is not obtainable with single or two-component
catalysts. The properties of the new polymers were dependent
on the catalyst ratios.
5.9.2. HT Studies on the Formation of Polymers
Vapor deposition polymerization (VDP) in combination
with masking has been used to generate libraries of aromatic
polyimides on PTFE surfaces. FTIR measurements were
performed to characterize the films, and UV as well aspolarized light microscopy were used to investigate thecomplex interplay between evaporation and orientation
behavior before, during, and after thermal imidization.[313] 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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The screening of the molecular weight of polymers, whichusually requires hours per sample by conventional methods,
can now be carried out in minutes in an automated fashion on
short GPC columns with the help of robotics.[312] Pasch et al.
have shown how size-exclusion chromatography (SEC) andhigh-pressure liquid chromatography (HPLC) can be accelerated for HTS applications to provide relative molecularweight distributions of a variety of polymers (PEG, PEO,
epoxy resins) in 2–6 minutes per sample.[314]In the HT development of pressure-sensitive adhesives,
Mehrabi and co-workers used the absorbance of visible lightin conjunction with a dye for the determination of film
thicknesses. The adhesive properties of thin films in 48 arrays,
prepared with a liquid dispenser, were measured automatically by recording force–displacement curves with a sphericalprobe adhesive tester in combination with an x-y stage. Profile
parameters related to tack, peel, and shear were obtained forevaluation of each potential adhesive.[315]
A high-throughput method for screening moisture vapor
transmission rates (MVTR) of polymeric barrier films has
been developed that is based on a nafion-crystal violet (CVN)
sensor that changes color from yellow to green uponabsorption of water. HTS was demonstrated by depositing
20 emulsion-based PVC films of varying thicknesses onto the
CVN sensor film and aging them at 40 8C and 90 % relative
humidity for 72 h. MVTR values were accurately determined
to a level of 0.9 g m2 day1.[316]Weathering is another important problem of materials in
outdoor applications which is very time consuming andusually costly to determine. Potyrailo et al. successfully
applied fluorescence imaging and spectroscopy to quantify
photodegradation in arrays of materials after short exposure
times.[317] The fluorescence methods detect trace amounts ofdegradation products arising from weathering and are much
more sensitive and faster than the conventional yellowness
index, with which a good correlation was found. It has beenreported that the screening throughput can be increased by afactor of 150–800 compared to the conventional determination of color change and reduction in gloss.[317]
The deposition of polymer films with continuous gradientsin temperature, thickness, or composition has been perfectedby researchers at NIST to optimize beneficial properties.[318]Thickness gradient films were prepared by spreading a
polymer solution by a knife edge with a constant accelerationof the edge movement. Composition gradient libraries wereprepared quite cleverly by continually introducing and withdrawing polymer solutions A and B to and from a vial, whileat the same time a syringe continually extracted solution fromthis vial. The syringe content was then deposited as a line on
the substrate and orthogonally spread with a knife edge
coater (Figure 32). Such composition gradient libraries lendthemselves to efficient studies of polymer blends, which
represent about a quarter of all polymers used.
Temperature gradient libraries can be obtained by placing
a library on top of an aluminium block, on one side of which isa heat source and on the other a heat sink to generate a linear
temperature gradient across the surface. Typical ranges are
70–160 8C over a length of 4 cm. In combination withcomposition (c) and thickness (d) libraries, T-c- and T-d-

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Figure 32. Deposition of composition gradient polymer films (fromRef. [318]).

dependent phenomena, such as dewetting, phase transition,and disorder have been studied very effectively. Thicknessand temperature-gradient libraries were mapped automatically by optical microscopy to investigate dewetting behavior.[319] Simon et al. have used an automated nanoindentation
technique to determine the dependence of the indentation
modulus on the blend composition (PLLA-PDLLA).[320] A
cold-plasma reactor was developed to prepare combinatorial
gradient libraries of copolymers of CO2 with ethylene.[321]Another important property of polymers is wettability,
which is widely used to predict adhesion properties, surface
wetting, and to control surface cleanliness. Bradley and coworkers have presented a simple and effective method todetermine contact angles in an automated fashion in parallelby dispensing liquid droplets automatically and recording thedroplet areas by imaging. The contact angles can be calculated automatically from the known relationship between thevolume and droplet areas.[322]Amis, Karim, and co-workers have reported the combinatorial mapping of surface energies of libraries of diblock
copolymers.[323] After depositing a self-assembled monolayer(SAM) of octyldimethylchlorosilane on the surface of a clean
Si wafer, a surface energy gradient was generated by agradient of UV/ozone radiation. The induced change in thesurface energy was characterized by contact angle measurements on water and diiodomethane droplets. Thin films of PSPMMA block copolymers with three different molecularweights were cast on top of the SAM with a thickness
gradient. The orthogonal gradients of surface energy andthickness create a library with a vast number of combinationsof the test conditions. The optical image shows regions ofcloudiness (islands and holes, which scatter light) and clear
areas, where the color change is associated with the change inthickness (40–100 nm). The films are characterized by AFM
imaging. The clear areas are attributed to ordering of theblock copolymers (Figure 33).
The determination of the mechanical properties ofpolymers is important and nontrivial. Van Vliet and coworkers have developed a nanomechanical profiling ofcopolymer arrays with material volumes on the nanoliterscale.[324] The library of 1728 materials, consisting of 576
discrete polymers in triplicate (Figure 34), was printed on astandard glass slide in less than 24 h by a robotic fluid 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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Figure 33. Optical photograph of a combinatorial gradient libraryshowing the morphology of the thin-film block copolymer as a functionof film thickness and surface energy. Islands and holes (not desired)on the surface scatter light causing the film to appear cloudy (lighterin color). The darker areas do not have surface features and do not
scatter light (from Ref. [323]).

handling system. The library, the spot size, and the monomers
used are shown in Figure 34. The whole library was characterized in 24 h by continuous automated acquisition andanalysis of the nanoindentation. Measurement errors wereless than 7.5 % of the maximum elastic modulus measured.[324]The chemical properties of polymers determine theirapplicability in different fields and need to be investigated forpotential applications. An HTS method for the parallel
evaluation of the solvent resistance of polymers was introduced by Potyrailo et al.[325] The authors used a 24-channel

acoustic wave sensor system to map the solvent resistance ofpolycarbonate copolymers. The study of the relationshipbetween the copolymer composition and solvent resistanceled to a cubic model that quantitatively describes structure–property relationships.
Conventional quality control of thermoset resins (used foradhesives, composites, coatings) involves destructive mechanical testing as well as NIR and fluorescence spectroscopy.
Eidelman et al.[326] have reported the use of FTIR microspectroscopy, confocal microscopy, and axisymmetric adhesion testing to study discrete epoxy samples cured at different
temperatures and to follow curing across continuous gradient
combinatorial libraries. Together, these techniques provide acomprehensive picture of the changes in the chemical andphysical properties within the prepared libraries.
An instrument for the parallel measurement of thethermomechanical properties of polymers in libraries withup to 96 samples was reported by Hajduk and co-workers at
Symyx Technologies.[327] Force sensors record the forces
applied oscillatorily by a pin array as a function of time,environmental conditions, and motion of the translation. Thismethod allows the determination of the modulus and loss
tangent of the samples as a function of time or temperature.
Combinatorial near-edge X-ray absorption fine structure(NEXAFS) has been developed by Genzer and co-workers at
NIST for the mapping of the bonding and molecularorientation of self-assembled monolayer gradients in polymer
films.[328] Measurements at the C and N edges were used tomap the surface density and molecular orientation of stressed
gradient layers of fluorinated polymers as well as gold
nanoparticles in gradients of amine-terminated organosilane
films.

Figure 34. Discrete polymer library. Left: pairwise combinations of 24 monomers printed as 576 spot arrays in triplicate on a standard glass slide;
middle: differential interference contrast image showing spots with diameters of 300 mm and thicknesses of 15 mm; right: monomer structures(from Ref. [324]).
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Chemometric calibration of Raman spectra has been used
to obtain the elastic modulus, stress data, density, methylgroup content, and 1-hexene content from copolymer libraries of ethylene with 1-hexene.[329] The accuracy of thecalibration is sufficient for screening applications, and canbe used for predictions. This simple approach employs the fullpower of HTE in an application where conventional measurements are difficult and time consuming.
Potyrailo et al. have prepared one-dimensional libraries ofpolymer composites with the help of a microextruder.[330] Theapplication was tested with bisphenol A polycarbonate incombination with TiO2 pigments and various UV absorbers.
The additives were varied systematically and the one-dimensional library was extruded as a continuous strand with adiameter of 1 mm. Reproducible step changes in the composition could be generated every 30 s. Figure 35 a shows thebottleneck. In a valuable overview, M-lhaupt and co-workers
described how the limiting factors can be overcome to allow
efficient HT screening of copolymer materials.[331] A typical
5 h per sample HR NMR analysis could be replaced by 40
samples per hour by ATR-FTIR measurements. The authors
point out that, for many practical applications, moderate
throughput under conditions close to those of real life isadvisable. Copolymers can be prepared in an automatedfashion on a gram scale in vial arrays at a rate of about 100 perday. Emphasis has focused on providing a large variety ofcharacterization data. The application of multivariate analysis
with NIR has led to the determination of branching, melting
points, and molecular weights.[331]5.10. Gas Sensors
Sensors are a growing market in which there are increasing demands on selectivity and sensitivity. The properties ofgood sensor materials—rapid response, high selectivity, andstability as well as rapid regeneration—result to a large extent
from the chemical composition and microstructure. Several
HTTs have been developed, which allow extensive screeningof parameters for various types of sensor materials. Vapor
deposition was used early on to prepare 64 materials in anelectrode array on Si wafers.[332] Such an approach is limited,since porosity, microstructure and homogeneous doping,which affect sensing properties, cannot be controlled properly.
5.10.1. Resistive Gas Sensors

Figure 35. Performance testing of a 1D library of polymer compositions. a) White light and fluorescence images of a 1D library after
irradiation at 845 kJ m2, b) spatially resolved fluorescence profiles of
the 1D library at increasing levels of weathering exposure (dose: 0,175, 355, 495, 675, and 845 kJ m2), c) weathering response of the 1D
library of polymeric compositions containing increasing amounts of
the UV absorber T234 at increasing levels of weathering exposure(from Ref. [330]).

library as a coil. The fluorescence image shows the spacing of
the members. Weathering studies in Figure 35 c show theeffect of the UVabsorber on the stability. The large advantage
of such an approach is the realistic preparation conditions,which improve the transferability of the HT data to theperformance of real polymer composites.
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Simon et al. used the wet synthesis of mixed oxides incombination with a ceramic library on an Al2O3 library platewith 64 printed Pt electrodes for the development of resistive
sensors.[333] Application of sol–gel synthesis by the use of a
special reactor allowed parallel measurement of temperatureeffects and resistance during exposure to pollutants.[334] The
effect of various doping elements on a tungsten oxide
containing 0.5 % Ta was monitored by a completely automated determination of the sensor signals with HT impedance
spectroscopy (in the frequency range of 10–107 Hz).[335]The complete set up for HT impedance screening for gassensing materials has been described by Simon et al.,[336] who
used doped In oxides as potential sensor materials forhydrogen. The layout of the electrode array is shown in
Figure 36.
The gas-sensing properties of nanocrystalline La-doped
CoTiO3 for the detection of low ppm levels of propane andethanol were discovered by Siemons and Simon using HT
impedance spectroscopy (Figure 37).[337] The experimental
setup and HT analysis with impressive visualization in thescreening of sensor properties on application of a sequence ofpollutants has been reported by Koplin et al.[338]HT screening with gas sensor systems has also been
explored in various applications by the research group of
Yamada. They combined, for example, different gas-sensing
semiconductors for the rapid analysis of benzene derivatives.[339] The composition of a variety of potential electro-

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Figure 36. Layout of an 8 P 8 electrode array for sensor development(from Ref. [336]).

Figure 38. Sensor microarrays prepared by electrochemical polymerization on platinum electrodes. The detection of HCl with co-polymersof aniline and 3-aminobenzosulfonic acid is described as an application (from Ref. [342]).

Figure 37. Response behavior of doped CoTiO3 samples at 475 8C to asequence of pollutants with the normalized sensitivity as the target
quantity (from Ref. [337]).

chemical sensor materials for H2, Co, NO, NO2, and propene,
discovered by HT techniques, has been reported by the
research groups of Maier and Simon.[340] The authors usedautomated liquid-phase synthesis for the preparation of
porous thick-film sensor materials on 64 electrode arrays.
They used HT impedance spectroscopy to study the effects of
doped SnO2, WO3, ZrO2, CeO2, In2O3, and Bi2O3 materials on
the reponse towards the test gases.
5.10.2. Polymeric Sensor Materials
Polymeric sensor materials have the desirable properties
for the detection of chemical and biological agents in gases
and liquids. The combination of HTE with micro- andnanofabrication and microfluidics is leading to innovative
sensor solutions. Modern sensing concepts cover ion-selective
electrodes, optochemical sensors for ions, composite resistor
polymeric films for vapors, biosensors from conducting
polymers, and polymeric biosensors. The field has developed
rapidly, as documented in a recent review by Potyrailo.[341]
Wolfbeis and co-workers[342] used an 8 V 12 microarray(Figure 38) to deposit polymers by electrochemical synthesis,
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followed by HT characterization of their chemosensitive
properties to gases. The response time, recovery time,
reversibility, reproducibility, sensitivity, and linearity could
be studied in such adsorption–desorption cycles.
Optical sensor materials respond to analytes with achange in their optical properties, such as absorption,reflectivity, luminescence, or optical decay. A typical exampleof the development of such sensors by HT methods isprovided by Apostolidis et al., who described the automatedselection of the most suitable combinations of polymer types
and indicators with plasticizers for the detection of O2.[343]

5.11. Heterogeneous Catalysis
Catalysts can be differentiated by their phase of application (heterogeneous and homogeneous catalysts) or by fieldof application, such as biocatalysts, polymerization catalysts,
petrochemical, and fine chemical catalysts. HT techniques
have been developed in all these areas.
The application of HT techniques for the development of
petrochemicals and fine chemicals has been reviewed recently
by Corma and Serra.[344] The same authors reported on the
successful use of semi-automated evolutionary strategies (ES)to optimize a selective epoxidation catalyst for cyclohexene(Figure 39)[345] as well as the strategy and results of a search
for a new catalyst for the isomerization of light olefins. Thislatter study was driven by a genetic algorithm (GA) andresulted in interesting conclusions on the effect of calcination
temperatures on the formation of tungsten-based acid sites
and the disappearance of sulfur-based acid sites in mixed
WOx/ZrO2 systems.
In 2001 scientists at UOP had already developed a
combinatorial multiclave which could be used to explore

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Figure 39. Development of Ti-MCM-41 catalysts by using genetic
algorithums for the epoxidation of cyclohexene (from Ref. [346]).

hydrothermal space efficiently and effectively.[347] The setup
has been used for both the discovery and scale-up of
microporous solids. A noble-metal-free dehydrogenation
catalyst has, for example, been developed successfully by
HT techniques and commercialized.[348] A catalyst for thedehydrogenation of methylcyclohexane to toluene was developed, starting with four non-noble metals of different
proportions and four different supports (alumina, titania,
zirconia, and silica) prepared in different ways and thenapplying a statistical DoE for optimization.
An optical method for the parallel evaluation of hydrodesulfurization (HDS) catalysts was developed by Staiger
et al., who proposed using binaphthothiophene as a dye forthe parallel screening of HDS activity. The UV/Vis band at
353 nm was used as a direct measure of the catalytic
activity.[349] Impregnation of ZSM-5 zeolites with transition
metals was used in HT experiments in a search for new
catalysts for the coupling of methane with CO. The screening
was carried out in a 40-tube gas-phase reactor. Benzene andnaphthalene on Zn/ZSM-5 were the main hydrocarbon
products at temperatures as low as 500 8C, although theyield was significantly lower than that of traditional methane
dehydrogenation catalysts.[350]
The new large-pore zeolite ITQ 30 was discovered by the
research group of Corma with the help of HT techniques.[351]
The strategy applied involved the variation of selectedsynthesis parameters, automated synthesis of all samples,and HT characterization by XRD. Data-mining techniques(Pareto analyses) were used to extract useful knowledge.
Corma and co-workers also used artificial neural networks toguide the HT synthesis of zeolites. This strategy allowed
synthesis regimes to be predicted, which differentiated clearly
between the formation of beta and UDM zeolites(Figure 40).[352]Serra et al. applied an evolutionary strategy to optimize
zeolite catalysts for the conversion of toluene and methanol tostyrene and ethylbenzene, respectively. Within three generations, the best catalyst systems outperformed the reference
system.[353] The synthesis of new IWR zeolithe polymorphs
was accelerated by combining the experimental design of6056

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Figure 40. Quality of the predicted formations of beta and UDM
zeolites by neural networks (from Ref. [352]).

structure-directing agents, high-throughput, and data-mining
techniques. Pure silica ITQ24 as well as borosilicate polymorphs have thus become accessible.[354] The synthesis ofzeolites with pore sizes larger than 14-membered rings was
believed to be hindered by the required O-Si-O bond angles.
HT techniques has led the research group of Corma to
identifying the untypical synthesis conditions for the generation of a new silicogermanate (ITQ 33) large-pore zeolitewith stable, linear 18-membered-ring channels.[355]In a series of manuscripts, scientists at Symxy Technologies reported the development of various catalyst systems forthe oxidative dehydrogenation of ethane to ethylene.[124, 356]
The Ni-Ta-Nb and Ni-Co-Nb systems provide catalysts which
dramatically outperform the state of the art Mo-V systems. At
only 300 8C, ethane conversions of over 20 % at selectivities ofover 86 % are reported for Ni62Ta10Nb28Ox.[128, 357] Urschey
et al. reported the discovery of novel butane dehydrogenation
catalysts by HTE. Emission-corrected IR thermography
combined with conventional gas-phase validations led to theidentification of Hf3Y3Ti94Ox as a promising catalyst for theoxidative dehydrogenation of n-butane to n-butene at 450 8C(63 % selectivity for butene at 32 % conversion of nbutane).[358]
An HT technique has been reported by Hancu et al. forthe chlorination of aromatic hydrocarbons.[359] The chlorination of o-xylene with zeolites was carried out in a 48-wellarray reactor and product analysis was performed afterwards
by conventional GC. The selective formation of 4-Cl-o-xylene
was found to be affected by the nature of the zeolite, the 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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Angewandte

ChemieCombinatorial Materials Researchbifunctional co-catalyst, and the operating temperature. The
reaction can also be carried out in the absence of solvents. The
highest selectivity was obtained with the H-beta zeolite.
The production of hydrogen from water and hydrocarbons(steam reforming) is of fundamental importance for thedevelopment of fuel cells. The activity of present noble-metalfree catalysts, such as CuZn or FeCr, is not sufficient.
Research groups from Symyx and Honda reported resultsfrom a fully automated HT technique for primary andsecondary screening in the search for improved catalysts forthe production of hydrogen.[360] The best Pt-free catalysts (NiMn-In-Sn) operated in the temperature range 250–450 8C,
while the best low-Pt catalysts (for example, PtCeCoVMoFeNa) operate at 200–350 8C.[361] Copper-free catalysts havebeen developed for the water gas shift reaction by applicationof evolutionary algorithms and HTE. The best catalysts are
based on Cr and Fe on ZrO2 as support materials.[362] In an HT
search for coking-resistant and noble-metal-free catalysts forthe dry reforming of methane, Kim and Maier identified NiCe mixed oxide as the most promising catalyst from the morethan 5000 formulations studied. After doping the catalysts
with Zr or Al, they showed high catalytic activity, without theneed for preactivation, as well as high coking resistance andexcellent long-time stability.[363] Mechanistic studies on thisnew catalyst material revealed the solid solution of Ni in CeO2
as the dominating microstructure responsible for the unusual
catalytic behavior.[364] In situ detection of the formation ofsyngas through the optical read-out of Cu reduction has been
applied by Omata et al. for HTS of catalysts for oxidative
methane reforming under pressure.[365]
Uniformly sized, multimetallic catalyst nanoparticles
deposited onto different substrates (for example, g-Al2O3,
CeO2, TiO2, SiO2, or Y-ZrO2) can be prepared by highthroughput through pulsed laser ablation (HT-PLA). The
method was developed by Senkan et al., and its use wasdemonstrated in a search for catalysts for the selective
oxidation of propylene.[366] Borade et al. have reported thedevelopment and scale-up of catalysts by HT techniques forthe selective oxidation of alcohols in the liquid phase by airand H2O2.[367] Redox molecular sieves based on vanadium
were identified as superior catalysts. IR thermography wasused by Schuyten and Wolf to identify the most active
catalysts for the selective oxidation of methanol to CO2 andH2 from libraries of catalysts with composition variation.
Validation of the hits was performed in conventional flow
reactors. The best catalysts within the Cu/Zn/Pd systemprovided, after promotion with 10 % Zr, a 95 % H2 selectivity
at quantitative MeOH conversion.[368] Noble-metal-free CoMn catalysts for the selective low-temperature oxidation of
CO with air have been discovered with the help of HTE by
Saalfrank and Maier.[369] The authors applied a directed
evolutionary strategy, best described as hit selection from thestarting library, followed by compositional sequential optimization, and doping to generate the subsequent libraries.[370]Doping of the optimized ternary catalyst with Pt resulted in amoisture-stable, selective catalyst for the oxidation of CO.[371]
The direct, selective methanation of CO has been developed
for gas purification of hydrogen for ammonia synthesis and isalso of interest for fuel-cell applications. An HT technique has
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been presented by Yaccato et al. which allows the efficient
search for new catalysts to competitively convert CO and CO2
into methane. Ru, Rh, and Ni appear to promote methanation, while Pt tends to catalyze the reverse water gas shift
reaction.[372]
Co, Ce, and In impregnated H-ZSM-5 catalyst libraries
have been studied for the reduction of NO with methane. A
multichannel UV-adsorption setup was developed to evaluate
the catalyst performance. The best catalyst identified contained a 1:1 ratio of Ce/In at a loading of 2 % on the zeolite.[373]A five factor, two-level full factorial design was used by
Schmitz et al. to develop supported Pt catalysts for theoxidation of NO in an HT approach that was composed of
automated synthesis, screening, and statistical analysis. The
relative order of influence of the factors at an optimal
reaction temperature of 200 8C was: support > pretreatment > loading > calcination atmosphere > calcination temperature > precursor salt.[374]Noda et al. presented a simple method to rapidly screen
for catalysts capable of growing vertically aligned singlewalled carbon nanotubes (SWCTs). The best catalysts discovered are based on Mo-Co material on silica supports.[375]
Automated thermogravimetric analysis (TGA) has been used
to examine libraries of alkali-metal-doped mixed oxides fortheir relative activity to combust diesel soot.[376] The strong
influence of alkali-metal ions on the activity of diesel sootcombustion catalysts was also confirmed by studies by Olonget al.[377] In this investigation, HTS was performed by ecIRT,
and only selected hits were further characterized by TGA. In
an interesting study on the HT search for low-temperature
combustion catalysts for air pollutants, the authors noted astrong dependence of catalytic performance on the nature of
the model pollutants used (dimethylamine DMA, benzene,
and dimethylsulfide). The best catalyst (Rb3Co10Cu48Mn39Ox)
combusts DMA at 150 8C. The authors also found several
catalysts, such as Co20Cu50Mn30Ox, which significantly reduced
the formation of NOx during quantitative DMA combustionat 250 8C.[378]5.11.1. Formulations
Formulations are the backbone of many product developments in industry, and combinatorial or HT approaches are
perfect means to accelerate their developments. Typicalexamples of materials based on formulations are paints,
detergents, coatings, adhesives, and composites. As a consequence of their systematic, but somewhat empirical nature,formulation developments are centered in industrial research& development departments. The following example from
BASF is an illustration of a typical formulations problem.
Polymer coatings are affected by a large number of parameters, as illustrated in Figure 41.
Robotic systems are used to vary parameters and identify
optimal formulations. Figure 42 shows flow curves of 30
combinations of thickener (A–F), solvent, and binder for
paint formulations. The results of microindentation measurements as a function of acrylate binder and amount of
isocyanate cross-linker are shown in Figure 43.[379] Clearly,
the materials generally become softer with increasing elas- 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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Figure 41. Multiparameter space for the formulation of coatings (fromRef. [379]).

ticity. The best materials with sufficient hardness but still
acceptable elasticity can now be easily spotted.
Combinatorial methods to prepare and screen polymer
formulations for biomaterials have been used successfully by
the research group of Kohn. The development was driven by
efficient parallel synthesis of suitable polymers, rapid screening assays for various cellular responses in the presence of thepolymers, and semiempirical modeling using an artificial
neural network to predict protein adsorption and cell
growth.[380]
It is estimated that 46 000 pieces of plastic float on every
square mile of our oceans. The development of biodegradable
plastic materials is thus of increasing environmental importance. Lochhead et al. have developed HT approaches toaccelerate the search for such new materials. Within a threemonth study, 2,4-dihydroxyphenol was identified as the only
suitable coupling reagent out of 110 polyphenols for the
preparation of biodegradable packing materials.[381]

Figure 43. Effect of different types of acrylate binder and varying
amounts of isocyanate cross-linker on the elasticity and hardness of
UV coatings (from Ref. [379]).

6. Promises, Problems, and Successes
6.1. Promises
When introduced approximatly 12 years ago, the application of combinatorial chemistry in materials research promised:* acceleration of basic research;* fast discovery of knowledge;* reduced development times;* reduced time for products to the market;

Figure 42. Development of paint coatings: optimization of the rheological behavior as a function of the thickener (A–F) and solvent (fromRef. [379]).

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Angewandte

ChemieCombinatorial Materials Researchrapid sampling of large parameter spaces;
rapid collection of comparable data;* discovery of new materials.
**

As documented in many examples in this Review, all ofthese promises have been fulfilled. HTE has developed into
an extremely successful new technology and the last threepromises above are also applicable to basic research.
Unfortunately, most of the scientific community has still not
realised how valuable the automated sampling of large
parameter spaces really is. The most important advantages
include reproducible preparation of materials and comparability of measured data. Such collections of comparable data
allow the study of correlations and trends in ways neverpossible by conventional one-at-a-time experimentation.

6.2. Problems
Despite the many successful examples mentioned above,
HTE cannot be applied to all problems. High-throughput not
only generates data rapidly, it also generates false positives
and negatives, of which the experimentor must be aware.
There is no documention of how many HT applications have
had to be abandoned because of the lack of agreement withdata from conventional experiments. Poor HTT performancein individual cases may result from principal problems, butmore likely they may be the result of a poor choice oftechnology. Many of the above mentioned examples arerather elaborate and document large efforts dedicated to thedevelopment of a suitable HT technique. When applying
HTTs, it is essential in the early tests to already verify theagreement of the HT data with those obtained from conventional tests.
A general acceptance of HT techniques has not beenreached and it is still often conceived as a means to replace
intelligent planning by a large number of experiments. Many
scientists in academia and industry have not realized thedramatic progress made in HTT and their view is still affectedby the following prejudices:* not suitable for the development of complex materials;* findings or hits may not apply, since HT conditions often
do not correspond with realistic production or conventional laboratory conditions;* only a simple parallelization of experiments without use ofscientific knowledge;* suitable only for industrial developments;* not suitable for basic research.
Most of these arguments have long been disproven bystate of the art techniques in the field. It is a personal decision
to accept or ignore this. Another more psychological barrier is
to allow HT philosophies into the planning and execution ofexperiments—which many view as a threat to the conventional approaches of daily laboratory work.
More serious is the general lack of access to HT workflows
and technologies. Many laboratories are not equipped for
HTE and also lack experience and manpower. The installation of permanent HTTs in a laboratory requires relative
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expensive HT equipment and the use of complex softwaretools, which are also either very expensive or have to be
developed in-house. The use of HT equipment may result in a
dramatic increase in consumables (such as solvents or
precursors), while the software requires at least one permanent staff member for proper use, maintenance, and adjustments. In academia, the former may become unaffordable,
while the latter is often prohibitive. Another problem isinterdisciplinarity, especially in academia. It is difficult to finda graduate chemistry student who is at the same time a goodexperimentalist, able to interface, construct, and modify
equipment, and is aware of artificial intelligence and softwaretools. Furthermore, the permanent change of co-workers, who
leave for first employment, does not allow the proper
maintenance of sophisticated HT workflows by graduate
students. For industry, the implementation of HTTs is therefore associated with high investments of capital and manpower and, because of the risk involved, smaller companies inparticular are hesitant. These factors are responsible for thewell-recognized lack of HTE in academia and smaller
companies. The lack of presence in academia also leads to alack of HTT in education, which furthermore reduces the
future acceptance of these technologies. Although this is
generally true, these arguments should not prevent scientists
from implementing HTT in the laboratory, even if it is at amoderate level and on a small budget. If done carefully, evensmall levels of HT, such as running ten instead of one
experiment at a time, can have dramatic effects on efficiency,
as well as with additional benefits of increased comparability
and reproducibility.
Complex synthesis procedures developed for the conventional preparation of catalysts or materials are often notsuitable for automation, parallelization, and HTE. Here,alternative methods suitable for HT have to be developed
before HTE can be applied. This often prevents the use of
HTE in specific applications.
There are also solutions to a broader access to HTTs. HTT
centers or institutes could be created, where workflows andsoftware would be available for companies and academia tohire. One such institute, FLAMAC, has just been founded in
Gent, Belgium, where partners can test or use workflows forcoatings and developments in other formulations. In academia, departmental workflows could be installed, which
could be shared similarly as has been the general practice withexpensive analysis equipment (such as NMR, MS, or electron
microscopy). In the area of laboratory equipment, many
companies offer affordable systems of parallel reactors orlaboratory robots, which can contribute to significant acceleration in academic laboratories or small- and medium-sizedcompanies.
As evident from the many examples cited above, many
specialized solutions exist for individual problems in materials research. The lack of general workflows or technologies
furthermore reduces the broad use. Too many specialized
solutions (hardware and software) and the complete lack ofstandards raise the barrier further.
Another problem is the broad lack of informatics tools forgeneral uses, such as data bases, sophisticated visualizations,data mining, DoE, and automation of the control of work- 2007 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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flows. A lack of affordable generalized software solutions isevident and is clearly responsible for the still broad use of
Excel sheets in many laboratories. At present, the use of thesophisticated methods described above is limited to companies and a few laboratories. This situation will certainly
change with time, as general software tools—such as thevisualization and data-mining package Spotfire—continue to
implement many of the accepted modeling and data-mining
tools for general use.

6.3. Successes and Discoveries
Many success stories and discoveries in the HT area havealready been summarized above. Some of these groundbreaking discoveries are a blue phosphor, a red phosphor,ethane dehydrogenation catalysts, catalysts for the water gas
shift reaction, various new zeolites, a polyimide nanofiltration
membrane, Cr-based and Fe-based catalysts for ethylene
polymerization, CO oxidation catalysts, dry reforming catalysts, electrochemical sensor materials, dielectric materials, an
optically transparent ferromagnet, and an optically transparent transistor. These successes are not only limited tomaterials and catalysts for industrial base chemicals, but also
the development of catalytic processes for pharmaceuticals
and pharmaceutical intermediates (not considered in thisReview) is often under severe time pressure and can be
speeded up significantly up by HTE. For example, Lefort
et al. described their protocols used to accelerate the development of a catalytic process for the fabrication of animportant intermediate through enantioselective hydrogenation of a substituted cinnamic acid derivative, which resulted
in a multi-ton process at DSM.[382]
HTT has not only led to the acceleration of conventional
synthesis and characterization through parallelization andautomation, it has also led to many new synthesis methods
and synthesis strategies, such as spatially resolved thin film
deposition, composition-tolerant sol–gel methods, and gradient libraries for materials and polymers. HTTs have also led
to many new characterization methods, such as rapid screening of the molecular-weight distribution of polymers, rapid
screening of enantiomeric excess, parallel screening of heatsof reaction by emissivity-corrected IR thermography, parallel
screening of wettability, an increasing variety of 2D scanning
methods, and laser-based techniques. The development of
QCAR, QSAR, and QSPR have only become possible with
HTTs. One might ask the question, why such a sudden floodof new methods, and why these methods are not used inconventional research? The answer is simple: demand. In
conventional research the established methods are sufficientand their reliability is well known. For example, there was noneed for a rapid determination of the molecular-weight
distribution of polymers, so why bother? Furthermore, why
use a new method with a larger error for single measurements?
It has been shown above that HTT can now routinely beapplied to fast automated preparation, characterization, andtesting of materials of many kinds. Reduced development
times, higher success rates, and better reproducibility have led

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many companies to install their own HT operations (BASF,
BP, Bayer, Degussa, DOW, Dupont, Exxon Mobile, GE,
Henkel, UOP, etc.). Several HT companies have also beenfounded (Symyx Technologies, hte-AG, Avantium, Ilika,
Bosch Lab Systems, Accelergy, etc.). For example, Symyx
started operation in 1996 with 2 employees and today they
have over 350 employees. The hte AG was founded in 1999
with 5 employees and now has over 100 employees. It is these
specialized companies which push hardware and softwaredevelopments as well as their integration to the boundaries of
HTT that allow them to achieve productivities and throughput that regular R&D or academic laboratories can neverreach. It is therefore not surprising that these technology
leaders increasingly sell complete HT development plants or
HT laboratories in the multimillion US$ price range. The
increasing demand for such highly sophisticated systems also
highlights the increasing trust and need for HTT on a larger
scale.
Particularly difficult to report on is the actual products on
the market that were developed by HTTs. HTT is still a young
technology that is used by companies to save time and costs. It
takes several years to get a product to market (scale up,
customer-specific developments, production technology, patents, permissions, environmental evaluations, long-time performance, etc.). Most companies are very hesitant to reveal
success stories, especially when associated with materials
optimization, complex formulations, or more efficient catalysts. However, some first examples of HTT products havebeen revealed[383] and are summarized in Table 1.

Table 1: Summary of successful product developments based on HTT.
Developer

Customer

Product

Symyx

Agfa
DOW
JSR
BASF

radiography detector DirectriX
catalyst for versify elastomers
polymer for electronics applications
heterogeneous catalysts for intermediates
silyl additive for antifouling boat paints
catalyst for asymmetric hydrogenation
polymerization catalyst for propylene (SHAC)
C5C6 isomerization catalyst
catalyst for polycarbonate

hte-AG
ArkemaDOW
UOPGE

7. Conclusions
In this Review with selected examples it has been shownthat HTT has been validated in many areas of materials
research and has been applied successfully to a wide area of
applications, although many additional contributions in theliterature worth mentioning could not be covered. HTTs havealready led to many discoveries and the first products
developed by HTE are on the market. Many researchgroups associated with basic research have not yet realizedthat many types of basic research can benefit from theintroduction of parallel experiments and it is highly recommended that research groups think about the application of
HTE methods. It is hoped that this article will stimulate somereaders to apply HTE on a moderate level in their daily work.

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Angewandte

ChemieCombinatorial Materials Research

HT methods have demonstrated their power and they are
already on their way to becoming standard technologies. In
the long run, laboratories and companies without HTTs willlose out against laboratories or companies using HTTs. Moreand more materials will be discovered, developed, or
optimized by the use of HTTs, which could lead to a dramatic
shift in the competitiveness. HTTs are becoming an increasingly important factor of R&D in industries and academia.
The integration and broad use of HTT may become a decisive
factor in maintaining technological advantages in a global
market.
In contrast to drug development, where HTT alreadyreaches sampling rates of 2 million samples per day, its
perfection in materials research will advance more slowly
because of the wide variation of technologies and the many
isolated solutions. The important future quests for materials
research, such as renewable energies, climate change, andgrowing problems with global food supply, will increasingly
depend on HTT.
We thank the members of our research group, G. Frenzer, D. K.
Kim, P. Rajagopalan, M. Kr2mer, N. Olong, M. Mentges, D.
Rende, M. Seyler, and T. Weiss for their help with compiling theliterature section. All the financial supporters over the last ten
years, including MPG, BMBF, BMWA, DBU, Hoechst, Bayer,
Creavis, Umicore, and Heraeus are also gratefully acknowledged. W.F.M. thanks the members of the “DECHEMAArbeitskreis Hochdurchsatzforschung”, especially T. Brinz
and W. Schrof, and their “Positionspapier Hochdurchsatztechnologien in der Materialforschung”.[383]Received: September 8, 2006
Published online: July 19, 2007

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