Invited Paper

High throughput methodologies for chemicals and materials RD&E1

by

John D. Hewes, Ph.D.

National Institute of Standards and Technology

Advanced Technology Program

Chemistry and Life Sciences Office

100 Bureau Dr., Stop 4730

Gaithersburg, MD 20899-473 0

I. SUMMARY

The U.S. chemical process industry (CPI) has annual revenues over $400 billion and supports the downstream

innovations of other critical U.S. industries. Innovations in the chemical process industry support over $1 .2 trillion in

product sales and service for the downstream value chains. Yet R&D funding within the chemical industry has been

relatively flat over the last decade at about $12-14 billion while being focused increasingly on applied research and

process development.2

Global market pressures are driving the chemicals and advanced materials industries to improve RD&E productivity as

measured by return on investment for new products. The principal drivers are reduced cycle times and higher quality at

lower cost, with reduced environmental impact. One approach to increased productivity is high throughput research (HT

RD&E) (also known as "combinatorial chemistry"), where a convergence of technologies enables a parallel approach to

discovery and process development. These methodologies produce "libraries" of new solid-state and soluble materials in

a matter of hours and days, rather than months and years, at a fraction of the cost of traditional serial approaches. New

materials have already been reported with unique chemical, optical, and electronic properties utilizing a variety of

parallel screening approaches.3

The CPI and materials industries have indicated a need to accelerate the implementation of this capability in the United

States. Industry has indicated that the Advanced Technology Program (ATP) of the National Institute of Standards and

Technology (NIST) can facilitate the emergence of new technologies. The ATP can spur the fusion of these new

technologies for subsequent diffusion to other areas. It can facilitate the integration of complex systems; the ATP can

help the integration of otherwise diverse technologies; and the ATP can reduce the cost of implementing high throughput

RD&E so that more R&D cost-sensitive industrial sectors will be able to invest in this new capability earlier. This

position paper is a response to industry's interest in the development of a portfolio of projects in the ATP to fund

methodology development in the area of high throughput RD&E for advanced materials (catalysts and biocatalysts,

polymers and polymer blends, electronic materials, biomaterials, etc.) that could accelerate the building of synergies,

promote inter-industry developments, and counter significant foreign competition in the CPI and materials sectors.

The ATP has responded to the need4 of industry for Federal Government investment in this area by awarding three

project proposals from the FY 1999 Open Competition that competed successfully against the ATP Selection Criteria.

These projects are attempting to develop breakthrough technologies for applications in polymer coatings and

heterogeneous catalysts. The need for further growth has been expressed, and the ATP continues to encourage

applications for funding in future Open Competitions in the area of high throughput methods for RD&E of chemicals

and materials, as well as other high technical risk areas that have the potential for broad economic benefit for the nation.

This report is a collection point for non-proprietary business and technical information gleaned from industry input,

for example as obtained at an Industry Probe Working Group Discussion held in March, 1998, public ATP

Workshops held November 18, 1998 in Atlanta, GA, November 16, 1999 in San Jose, CA, as well as ATP's

participation in many industrial forums in the last two years. Complete review articles can be found in the

references.

Keywords: combinatorial chemistry, combinatorial methods, high throughput screening

In Combinatorial and Composition Spread Techniques in Materials and Device Development. 46 Ghassan E. Jabbour, Editor, Proceedings of SPIE Vol. 3941 (2000) • 0277-786X1001$l 5.00

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NIST Special Publication 947

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.SP.947
II. THE ATP PROCESS

The goal of the ATP is economic growth and the good jobs and quality of life that come with economic growth. ATP

awards are made strictly on the basis of rigorous peer-reviewed competitions designed to select the proposals that are

best qualified in terms of the technological ideas, the potential economic benefits to the nation (not just the applicant),

and the strength of the plan for eventual commercialization of the results. The ATP protects the confidentiality of

documents submitted by industry as required by the ATP statute. The ATP does not fund projects that are predominantly

basic research or product development. The ATP submits all proposals to peer review by following the process outlined

in Figure 1.

FULL PROPOSALS I *

I SCREENING I

+

TECHNOLOGICAL AND ECONOMIC REVIEW

TECHNOLOGICAL MERIT ECONOMIC MERIT

Innovations in the technology • Economic benefits

• High technical risk & feasibility • Need for ATP funding

• Quality of R&D Plan • Pathway to economic benefit

I[ HIGH TECHNOLOGICAL

& ECONOMIC MERIT

SEMIFINALISTS

V

IDENTIFIED

FIGuRE 1 . THE ATI SELECTION PROCESS

Non-proprietary white papers (not proposals) submitted by industry, academia, and government facilities might outline a

specific opportunity area and describe the potential for U.S. economic benefit, the technical ideas available to be

exploited, the strength of industry commitment to the work, and the reasons why ATP ftinding is necessary to achieve

well-defmed research and business goals. These position papers contain no proprietary information and state as

succinctly as possible the goals of a proposed technology challenge that needs the benefit of a cluster of synergistic

projects to maximize benefit to the nation's economy.

ATP project proposals and optional pre-proposals submitted to AlP are evaluated against the scientific and technical

merit of the proposal and the potential for broad-based economic benefits to the United States. A fifty-percent weighting

applies to the scientific and technological merits of the proposals: innovations in the technology; high technical risk and

feasibility; and quality ofthe research plan. A fifty-percent weighting is applied to the economic merits ofthe proposals:

economic benefits; the pathway to economic benefit; and need for ATP funding. Overall, proposals are ranked

competitively according to the six components of the two Selection Criteria as expressed in the written proposal.

Optional pre-proposals may be submitted year-round and provide a mechanism to receive written feedback on the

strengths and weaknesses of the project plan and on how to improve the competitive potential of a subsequent full

47

I DEBRIEFING I

FINAL SELECTION Cooperative

Agreement

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48

proposal. Applicants are strongly urged to initiate proposal preparations early and to follow instructions carefully.

Proposal Preparation Kits for each new competition are distributed via the ATP Mailing List (telephone l-800-ATPFUND to register) and on the AlP internet world wide web site http://www.atp.nist.gov/atp/apply.htm.

III. PROBLEM STATEMENT

Major forces—globalization of markets and the pace of technological change—continue to drive private sector R&D to

more focused, shorter-term investments to maximize near-term returns to the shareholders. Increased pressure on

manufacturers to produce "faster/lower-cost/better" has increased the demand for new products made from new materials

and/or utilizing new processes while utilizing more environmentally-friendly materials and processes. In order to achieve

these goals, the CPI and materials sectors are expected to follow a trend occurring in other technology sectors and will

focus on core business areas with greater dependence on strategic partnerships. The move to outsource research and

development efforts to outside firms (the "discovery and development industry") and/or create facilities in countries with

lower-cost labor is an emerging business model in the CPI and materials sectors.

During the 1990's, the pharmaceutical industry responded to market pressures (product launch times, return on R&D

investment, large revenues for blockbuster drugs, reduced profits from health management organizations, etc.) by

switching from serial discovery processes for generating and analyzing drug targets to using "combinatorial chemistry"

research methods. This methodology can qualify a large number (a "library") of possible candidates ("hits" from primary

screening, "leads" from secondary screening); in 1999, the ability to screen 1 million distinct compounds per year was

realized in the pharmaceutical discovery process, with R&D costs per lead dropping approximately two orders of

magnitude. The capability to convert traditional discovery processes to an "assembly line" was facilitated by the

convergence of several technologies applied to a well-defmed market opportunity: computer software (data bases,

molecular modeling, machine control software, and statistics); more cost-effective high-speed computers; robotics;

MEMS (micro-electromechanical systems) technologies; and sensors.

Figure 2 illustrates how one can differentiate the key steps of a typical high throughput RD&E process:

Target Defmition utilizing expert opinion, hypothesis, and computer modeling;

Library Design with computational inputs such as quantitative structure-property relationships (QSPR), and molecular

modeling. Design ofExperiments (DOE) is required to reduce the number ofsamples that will be necessary to defme

sample spaces within the experimental universe or to direct screening to other spaces within the universe;

Library Fabrication involves the automated deposition and/or processing of an n-dimensional matrix of physical samples;

Library Characterization in a parallel or massively parallel mode involves the use of robotics and sensors to rapidly and

automatically analyze the library of targets for desired properties;

Data Collection and Analysis using the data-base and artificial intelligence tools—"informatics"—--expanded into the

more complex realm of materials properties.

Figure 2. The High throughput Process Flow

Scale-up &

Validate

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25,000

FIGuRE 3. COMBINATORIAL VS. CONVENTIONAL REACTOR THROUGHPUT5

Industrial sectors other than the pharmaceutical industry recognized the attributes of the new drug discovery paradigm

and are implementing high throughput screening of new materials. Serial discovery processes rely on the preparation and

characterization of individual samples from bench scale (mg. or grams) to pilot scale (grams to kilograms). Parallel, HI

methods can perform the same preparation and characterization using automated laboratory instrumentation. As shown

in Figure 3, there are expectations that HI screening can significantly accelerate the discovery of new catalysts. An

emerging trend is to continue the parallel process flow into the process and product development stages to realize

substantial increases in the number of samples that can be analyzed.

Many ofthe market factors that influenced drug discovery are presently driving a need for reducing the cycle time for the

discovery and process development of new advanced materials and lower-cost chemical products such as pharmaceutical

intermediates, fme and specialty chemicals, and commodity chemicals and materials. The technology spill-over from

drug discovery has resulted in the development of high throughput (HI) methodologies for inorganic materials and fme

and specialty chemicals and materials. Because HI techniques are especially suited to complex mixtures containing

many different components and/or processing conditions, this methodology lends itself to the discovery of new advanced

materials that are gaining performance through the use of multi-component formulations, for example the addition of

dopants to electronic materials or polymer blends for engineering plastics. In addition, HI RD&E permits the screening

of compositions that would not otherwise be attempted, that is, it maximizes serendipity. For example, Symyx

Technologies Inc.6 has reported the identification of a ternary fuel cell catalyst composition (M-M'-M") of high

selectivity and conversion containing transition metals that show little or no catalytic activity in the three possible binary

mixtures (M-M', M-M', M'-M"). Applications beyond catalysts have been explored, for example phosphors,

thermoelectric materials, and optoelectronic devices such as ZnO-based compound semiconductors for light-emitting

diodes (LEDs).7

In the pharmaceutical industry, new drug candidate molecules are tested for biological activity by chemical means such

as gas chromatography, nuclear magnetic resonance spectrometry, mass spectroscopy, fluorescence spectroscopy, or the

response of a biochemical receptor. Advanced materials, on the other hand, require performance-based characterization

that is often application-specific. For example, selectivity and conversion analysis for a matrix of heterogeneous catalyst

formulations will require the development of sensors for sampling the product/reactant mixtures produced by the catalyst

lead sample array, not just an analysis for elemental composition or molecular activity.

Materials processing typically involves more energetic reaction environments than pharmaceutical processing, with

temperature and pressure requirements as high as several hundred degrees and hundreds of Pascals. Micro-scale solid

state samples may also be subject to significant influence from the substrate onto which they are deposited--interfacial

effects can produce phenomena that are not reproducible in bulk samples of manufacturing scale. Thus, advanced

materials suffer from "scalability", or differences in micro-scale to lab- or pilot-scale properties. Finally, solid state

49

20,000

15,000

j

10,000

5,000

Time (Months)

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50

compositions may develop into different (kinetically-controlled) metastable structures depending on processing and

testing conditions. Therefore, sample libraries must undergo validation at every process step.

The leverage of tools developed for drug discovery, e.g., activity-focused/solution-state systems, to solid state materials

is challenging due to the diversity of potential design, fabrication, and analysis parameters. Some of these challenges are

showninTable 1.

TABLE 1 . DRUGDISCOVERY TARGETS VS. SOLID STATE TARGETS

Drug Discovery vs. Solid State Materials

. Discrete molecules ofC, H, F, N, 0, P • Extended structures ofmany elements

nntentiallv in metastahie states

• Finite number ofactive sites, can be characterized Ill-defmed distribution ofactive sites and

and modeled computationally stnictiires

• Purity >85%; parallel purification techniques "Pure" solids are meaningless especially with

employed before characterization small samples having interfacial effects with the

library substrate

• Structures reproducible (a priori) Reproducible structures difficult, if not

impossible, to create a priori

• Chemical characterization, biological activity well • Characterization ofmultiple independent

developed for rapid or parallel methods properties and composition not straightforward

• Descriptors for diversity Few or no ideas exist about how to do it

• Registration of library samples straightforward Few or no ideas exist about how to do it

• Synthetic building blocks available • A few building blocks available

Iv. TECHNOLOGY CHALLENGES

Information gained from the many public discussions8 in this area has been supplemented by additional input in the form

of non-proprietary position papers submitted to the ATP by industry. In addition to identifying key areas of technology

development and application areas, these data describe the technical and commercial barriers to implementing this

methodology in the global CPI and materials sectors.

The application of high throughput discovery and process development for chemicals and materials will drive the

enabling integration of a hardware- and software-based infrastructure toward specific product applications. The longterm vision is to have high-throughput research become part of expanded enterprise-wide systems that include tools for

hardware interfaces, technology assessment/decision, and logistics. Because HT RD&E is currently highly capital

intensive, with start-up costs in the range of $8M to $20M,9 discontinuous innovation in generic andlor modular

hardware and software technologies will be necessary to drive down costs and facilitate its implementation in the

industrial sectors that have lower returns on R&D investment, such as exist in CPI and materials sectors.

A. SOFTWARE

The basic underlying software technology must be capable of defming profitable experimental spaces and visualization

of complex data relationships, and of correlating target materials with properties to permit data-base queries from a broad

spectrum of data mining engines and the development of structure-property relationships. This requires interfacing with

data visualization tools at the back end and statistical experimental design engines on the front end while remaining

compliant with enterprise-wide systems for knowledge management and maintaining control ofexperimental hardware.

The overall view of software integration is shown in Figure 4, where the integration oflnformatics, Modeling, and

Design are high-risk opportunities. .

Informatics. Integrated packages linking modeling, development and management of databases and search engines,

hardware control, data visualization, and logistics. Data base search engines will need to be interoperable with the

diverse flavors ofdatabases currently in use;

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. Development of Quantitative Structure Property Relationships (QSPR) for materials. The term Quantitative

Structure Activity Relationships (QSAR) is used in organic combinatorial synthesis; . Acceleration ofthe design process from atomic level chemistry to engineering design by developing

relationships between chemistry, processing, microstructure, etc. and processing involving metastable states,

etc.; . Development of a query language for linking many different methods for querying the data with appropriate

query optimization methods; . Assembly of a high-performance data mining toolbox that extends a database management system with

additional operators;

S Connection to the diverse metrics in materials design, where important properties are sensitive to numerous

ranges of length or time scales, for example from 1 O m. to 1 02m. and nanoseconds to years; . Development of tools to present complex, multi-dimensional data relationships to the human interface. HT

RD&E establishes the new paradigm for the researcher who now must interpret data surfaces and not just data

points.

Design of experiments. Due to the potentially high number of candidates available in HT methodology, the design

of the sample library requires rational chemical synthesis or process information to reduce the number of samples and

experiments without increasing the probability for endless searches, false positives, or false negatives. . New tools will have to be developed to enable the integration of this information into molecular- and

property-modeling engines. The increased amount of data that can be input into computational engines will

require a significant increase in speed, bandwidth and storage. • Advanced, high-speed quantum calculation programs such as Wavefunction, Inc.'s program SPARTAN1° and

MSI's program Cerius" will require interfacing with databases and experimental design programs; • Advances in experimental strategy for dealing with large, diverse chemical spaces, using space-filling

experimental designs, predictive algorithms, and optimization techniques.

51

FIGuRE 4. THE INTEGRATION OF SOFTWARE SYSTEMS

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52

B. HARDWARE

The basic underlying hardware technologies needed for HT library fabrication and analysis are enabling and emerging

technologies that are fmding applications in other arenas. Broad technical needs have been identified by industry (Table

2).

Increasing computer throughput with, for example, massively parallel computers and high bandwidth

networks;

Micro-machines and micro-reactor technologies (MRT) based on micro-electromechanical systems (MEMS)

will address the need for higher library densities to facilitate reduced raw materials costs for library fabrication

and economies of scale and modularity in laboratory instrumentation. Construction of solid state materials

libraries currently requires automated onto substrates, using, for example, micro jet, laser ablation, vacuum

deposition (PVD, CVD), or micro-fluidics in a lab-on-chip application. Micro-scale methods have already been

commercialized for health care diagnostics with liquid samples. Preliminary market penetration in the CPI and

materials arena will be with systems utilizing solution state reaction systems using homogeneous catalysts.

S There is an growth of activity in this area, with links to the HT RD&E conmiunity, especially for drug

discovery 12 One prototype microreactor is shown in Figure 5.13 There is a growing international

effort to understand MRT for distributed manufacturing of chemicals and for high throughput screening.

Principal components of MRT are analogous to large-scale machines—reagent mixers, reactors, distribution and

separation. The key technical challenges for MRT are in component integration, development of modular

systems, and development of engineering tools to design and build microscopic systems. Since fluid flow in

these devices is laminar, a significant challenge is in understanding fluid dynamics in these systems. Clearly,

the convergence of the microelectronics technologies with micro-reactor technologies will accelerate in the near

future, and are being tracked with interest by many parties for their economic potential. The current technology

leaders for chemical process development and high throughput screening are the German Institut fir

Mikrotechnik Mainz'4, and Forschungszentrum Karlsruhe.'5 Research in the United States is centered primarily

at the Pacific Northwest National Laboratory16 and at the Massachusetts Institute of Technology Microsystems

Technology Laboratory.'7 A collaboration between DuPont Experimental Station and Massachusetts Institute of

Technology (MIT) has produced a circuit board-level discovery plant containing multiple socket-borne

(interchangeable) catalytic reactors with integrated fluidics control, heat transfer, separation, and mixing for HT

discovery and process development.'8

FIGuRE 5. PROTOTYPE MIcRo-REAcToR FOR FLUIDIC SYSTEMS FROM MIT

U

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FIGuRE 6. MICROREACTOR ASSEMBLY FROM THE INSTITUT FÜR MIKR0TEcHNIK MAINZ

Micro-scale sensors. High throughput methods will drive the development of advanced sensors and sensor

arrays. The current technology relies on contact and non-contact methods of characterization and external

control of process conditions. A significant impetus for developing micro-scale sensors has been the U.S.

Department of Defense,'9 primarily in response to battlefield detection of chemical and biological warfare

agents and portable power generation, and from National Aeronautics and Space Administration (NASA) for

micro-robotic space exploration. The CPI sector is moving toward smaller, more integrated sensing devices in

process control of manufacturing sites. Robotics, next-generation "titer plates", lab-on-a-chip designs, and rapid

scanning devices for HT materials innovation will be with application-driven tools targeting specific physical

properties that can be analyzed at microscopic levels. Automated library processing is especially challenging for

new materials development since samples within a library may require different or non-equilibrium processing

parameters across the library. Therefore, with the impetus toward MRT lab-on-chip devices, integration will

drive the development of foundry methods to produce on-chip optical sources (e.g., semi-conductor lasers) as

well as detectors. Finally, the capability for interpretation to bulk characteristics from micro-scale will place

increasing pressure on computational tools such as QSPR.

TABLE 2: TECHNOLOGY CHALLENGES

SOFTWARE

Technology Challenge

Library Design

Statistics

Modeling

Literature/Patent Databases

- Development of higher-order designs

- (Reviewby NSF is pending)

- Query languages; visualization; integration

Informatics

QSPR (structure-property predictions)

Database Query Engines

- Propertyprediction, large-scale correlations, integration into

experimental design tools -New languages, genetic programs -

Inter-operability, enterprise-wide integration

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HARDWARE

Techno1oy Challenge

Screening

Thermal properties

Optical Characterization

Mechanical Properties

Electrical Properties

Chemical Properties

2-dimensional or parallel sensors for: - Electrical and Thermal Conductivity

- Fluorescence, luminescent properties -Modulus, Tensile

Strength, Impact resistance

- Molecular Weight - Polymer architecture/morphology

- Catalyst Turn-over, Selectivity, Conversion

Processing

Control ofphysical environment - Control oftemperature and pressure over library array with

control over individual sample sites or wells - Sample size--control of interfacial diffusion, mass transport

properties, etc.

Deposition

Thermally-driven (e-beam, laser, etc.)

Laser ablation

Micro jet

Vacuum Deposition

Robotic pipetting of nano-aloquots

- Delivery offmite samples or composition spreads of

consistent, known composition at microscopic sizes:

reproducibility. - Reduction of cross-talk of sample properties through diffusion,

etc. across substrate surface

Micro-Reactor Technologies

- Development of standards for modular component

interconnections - Process control devices tuned to MRT

- Modeling for fluid flow, heat and mass transfer; - Substrates: glass, polymer, metal - Surface micro-machining using wet or dry chemical etching,

. . . .

laser ablation, mechanical micro-millmg, LIGA processes.

Systems integration

Reactor design

. Manufacturmg processes:

54

V. PROBLEM STATEMENT

The two major technological hurdles are systems integration ofthe hardware and software tools, and the scalability of

micro-scale results to end-use scale.

A. SYSTEMS INTEGRATION

The transfer oftraditional serial research methodologies to multi-dimensionalparallel methodologies will require the

integration of previously diverse computational and characterization tools for sample library design, sample library

fabrication, characterization, and informatics.

B. SCALABILITY

The ability to utilize data obtained from libraries of micro-scale samples will require scientific advances in the areas of

interfacial effects and structure-property relationships.

C. COMMERCIAL CHALLENGES

The major commercial hurdle is validation that HT RD&E methodologies lead to increased productivity, for example in

terms of increased return on investment (ROI) and higher net present value (NPV) for new products. Time-based

competition is driving many industries to increase R&D funding at the expense ofreducing allocations to capital assets.

The "new economy" may bring about the acceptance ofnew metrics, for example the rate ofRD&E expenditures vs. the

rate ofcapital investment in manufacturing assets.2° In addition, the concept ofintellectual property as a valued asset is

becoming more widespread as enterprise-wide knowledge management becomes increasingly viable.

There is a resistance to believe that HT discovery and process development methodologies will impact R&D productivity

in most firms. Large capital investments will be made only by the few large companies that can guarantee a retum within

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one or two years. The CPI and advanced materials sectors 'will not adopt HT methodology until commercial impacts are

validated, and the R&D capital assets can be economically utilized. The bulk ofthe smaller firms manufacturing

specialty chemicals and materials would conceivably be a target customer, however their entry will be retarded pending

reduced entry costs. These industries are characterized by R&D budgets that are typically 3% to 4% of sales, with profit

margins in the range of 8% ' As indicated earlier, improved return on RD&E investment and faster time-toproduct launch are expected to result in higher overall NPV. Because the CPI and materials sectors generally exhibit

cycle times of 7 tolO years for concept-to-product launch, given end-user qualification and manufacturing design and

construction cycles, HT RD&E projects initiated now will not reach commercial validation until 2003-2005 at the

earliest.

Notably, numerous large companies have reported publicly that their HT RD&E efforts have been technically successful

in catalyst discovery and process development, at a typical entry cost of $5M to $20M.2' In order to reach a competitive

critical mass, HT RD&E methodologies must reach industries and companies that cannot make such a substantial capital

investment. There is, therefore, a role for the Federal Government to gain a significant impact on the national economy

by investing in the development ofnew, lower-cost tools that will ultimately reduce entry costs for industries that fmd

implementation prohibited.

VI. ANALYSIS OF SOLUTION

The implementation ofthis emerging methodology by the advanced materials industry will enable new technologies having

broad technological and economic impact. The principal drivers are lower development costs, reduced innovation cycle

times, and higher performance materials for industrial and consumer products--to impact the accelerating market needs of

"faster-less expensive-better".

Since February 1998, the NIST ATP has been collecting input on the needs ofU.S industry for new techniques and

strategies for HT R&D. The role ofgovernment support in response to industry needs in a relevant time frame, and the

economic value to taxpayers of a potential investment, are important considerations.

VII. COMMERCIAL OBJECTIVES

A. BACKGROUND

A new paradigm is now taking hold in the RD&E centers ofJapanese, European, and U.S. advanced materials industries

of catalysts, polymers, specialty and fme chemicals, optical materials, and electronic materials.22 High throughput

methods2 for materials RD&E leverages the combinatorial chemistry methodologies developed over the past ten years in

the pharmaceutical industry. The implementation ofthis emerging methodology by materials innovators will enable new

technologies having broad technological and economic impact as manufacturers strive to meet original equipment

manufacturer (OEM) demands. The bottom line is that more complex compositions can be created and analyzed in a

reduced cycle time and at lower cost. The flip side is that this should also be a watershed for basic research in elucidating

new phenomena as well as in developing the new technology platforms.

Since February 1998, the NIST ATP has been gathering primary and secondary market research through an Industry

Working Group, by holding public workshops (3 March1998, 28 Nov1998, l6Nov1999), and by a proactive outreach

effort at conferences and workshops. The NIST ATP leveraged this knowledge base to understand U.S. industry needs

with respect to the ATP Mission. The ATP's cost-sharing ofhigh-risk industrial research appears to correlate uniquely

to industry's critical success factors.23

There are significant scientific and technological challenges to implement HT methods in advanced materials. These

challenges can borrow from advances made in other areas such as drug discovery and bioinformatics, however in most

cases the technology transfer is not straightforward. The transfer of traditional serial research methodologies to parallel

methodologies will require the integration of otherwise diverse computational and characterization tools for library

design (statistics, design of experiments), library fabrication (sample deposition, automation), characterization (sensors,

automation, data acquisition), and informatics (data handling, visualization, decision tools). The scalability of the results

obtained will require scientific and technological advances in the areas of interfacial effects and structure-property

prediction.

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As OEMs and materials manufacturers focus on their core business areas--assembly andmanufacture--the advanced

materials industries are beginning to outsource discovery andprocess development. This is resulting in the formation of,

and dependence on, small firms that are structured as discovery- and/or high throughput methods service providers (the

"discovery and process development industry"). There are currently seven of these service firms world-wide, and their

competencies lie in an ability to focus integrated hardware and software systems toward profitable research areas such as

catalysts and electronic materials. The HT RD&E environment includes materials manufacturers, discovery service

providers, and hardware and software tool providers (Figure 7).

B. IMPACT ON INDUSTRY

ATP's support of industrial implementation ofhigh throughput methods could significantly improve the competitive

stance ofU.S. industry and provide broad economic impact. Industry representatives have indicated that a reduction in

the time to launch a new catalyst for chemicals manufacture can be reduced approximately two years utilizing HT

discovery methods. This two-year reduction in break-even point (BEP) may approach $20M for a typical $ lOOM

chemical plant. ATP can further decrease the time-to- market through co-funding the high-risk development of new tools

that would normally be beyond the scope of traditional industrial research, resulting in a higher Net Present Value

(NPV).

Cash Flow ($)

FIGURE 8. ATP FUNDING IMPACTS TIME-To-MARKET FOR HIGH-RISK TECHNOLOGIES

FIGURE 7. THE MATERIALS INDUSTRIES HIERARCHY

Break-Even

Points — With Combi

Traditional

Time

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One market factor that might predict the movement of HT RD&E methods is the current level of spending for R&D in

these sectors. Implementation ofHT RD&E technologies is expensive; sufficient R&D funds must be available, and

acceptable returns on the investment may be precluded in some industries by their profit structure. Aerospace,

automotive, biomedical, telecommunications, and computers are the principal end-users of the chemicals and materials

sectors. Semiconductor and electronic hardware sectors are materials and device producers (OEM's), and analytical

instruments and software sectors provide technology infrastructure. The annual R&D budgets for these finns are an

indicator ofthe leverage that HT methods can have: assuming a 5%penetration into the infrastructure ($9.7B in 1997)

and supplier sector R&D ($13.4B), approximately $1 .2B in R&D budgets would be assigned to high throughput methods

development with a potential downstream increase of $905B in sales (pharmaceuticals excluded).

High throughput methods will eventually impact all of the advanced materials industries and high technology industries,

therefore the potential impact of the ATP technology cluster "Combinatorial Methods for Materials R&D" could be

large. Funding for two projects awarded in the ATP FY1999 Open Competition is shown below.

$50

$45

$40

$35

$30

$M $25

$20

$15

$10

$5

$0

FIGURE 9. ToTAL ATP AND INDUSTRYINVESTMENT

ATP can also have an important and probably unique role in funding research at NIST in this area through Intramural

Funding. This research addresses fundamental problems in developing new standards and measurement techniques that

will fmd general use by U.S. industry. Research funded for FY2000 through the ATP Intramural program will focus on: . developing the infrastructure to support new parallel methodologies and measurement tools that can be tailored to

industrial applications and properties; . validating new and existing methods and models for small sample sizes analyzed using high throughput approaches; . validating the applicability ofHT methods to new materials and research problems.

The NIST Measurements and Standards Laboratories (MSL) are uniquely qualified to participate in this area: NIST's

broad capabilities for scientific research and technology development funding address major challenges of high

throughput methods implementation. ATP is currently funding research in the areas ofpolymer array scaffolds for tissue

engineering,24 two-dimensional infrared array detection of inorganic and organic substrates,25 x-ray and microwave

measurement of dielectric ceramic thin films,26 analysis of dopants in compound semiconductor thin films,27 x-ray

57

Nonlinear DynamicslUOP LLP "Combinatorial Tools and Advanced Data Analysis Methods

for Heterogeneous Catalysts"

$14,715K (ATP) + $15,186 (joint venture, 5 year duration)

GE/Avery-Dennison "Combinatorial Methodology for Coatings Development"

$3,127K (ATP) + $3,200K (joint venture, 3 year duration)

2000 2001 2002 2003 2004

Fiscal Year

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studies ofsupported catalysts,28 and genetic programming ofdata query engines.29 The NIST MSL effort is expected to

grow significantly.

C. TECHNOLOGICAL CHALLENGES

Materials manufacturers are utilizing several business scenarios to obtain HT RD&E capabilities: by developing internal

capabilities (e.g., General Electric Corporate R&D); by contracting with service providers having a core competency in

high throughput discovery methods (e.g., Dow Chemical with Symyx Technologies); or by developing an independent

consortium or alliance partnership with individual tools providers (e.g., Avantium—a Shell spin-off in partnership with

the Dutch government, private investors, and three Dutch universities). These events signal a clear trend that the

materials industry is beginning to dis-integrate their front-end discovery efforts to smaller external entities. There are

currently seven companies known to be either performing front-end R&D or developing integrated systems for large

materials manufacturers utilizing HT R&D (ref. Table 5 1)

TABLE 5. HIGH THROUGHPUT METHODS PROVIDERS FOR ADVANCED MATERiALS

Parent Company

(Miscellaneous)'2

Company

(HT Materials R&D)

Financing!

Partnerships

Symyx Technologies (Santa Clara) IPO-l 1/20/99

Hoechst AGC, Celanesec, Bayer

AGC, BASFC, B.F. Goodrichc,

Dow Chemical

Unilever

ArQule Inc. Alveus Systems (Belmont, MA) N/A

BASF hte GmbH (Heidelberg) MPI-Kohlenforschung

BASF, Private fmancing

Charybdis Scylla (San Diego) Private financing

SRI International CombiCat (Menlo Park) Internal, clients

Catalytica Advanced

Technologies

Aperion (Mountain View, CA) (Announced June 1999)

Molecular Design (UK) Cambridge Discovery Chemistry

(Cambridge, UK)

BP Chemicals (Germany)

DSM (Netherlands)

Engeihard

Argonaut Technologies Symyx Technologies

Shell Oil Avantium Universities of Delft, Twente,

Eindhoven; the government of

The Netherlands; GSE, Inc.; other

shareholders.

VIII. CONCLUSION

Combinatorial methods have revolutionized drug discovery in the pharmaceutical industry and are poised to do the same

in materials science, biotechnology, chemistry, physics and other technological bases. These efforts are needed to

maintain U.S. leadership in chemicals and materials R&D by providing globally competitive increases in efficiency of

materials discovery and process optimization. Industry has correlated the impact of increased innovation throughput in

different areas to broad economic benefits.

HT methods R&D for advanced materials is about four years old.3° Current end users for HT RD&E are the chemical

process industry (catalyst discovery and chemical process development), specialty polymers, and electronic materials

(e.g., inorganic dielectric and phosphor materials discovery) intr31 One would expect that, as the barrier to entry

is reduced by lower cost tools and validation ofthe methodologies, lower-valued applications,32 for example, commodity

materials, will become targeted. Key commercial and technology drivers with regard to implementation of HT RD&E

methods are shown in Table 6.

58

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TABLE 6. MAPPING TEcHNIcALCHALLENGES TO ECONOMIC BENEFITS

Application Areas Technical Challenges Impacted Products Economic Benefits

Industrial Chemicals

and Monomers • Faster catalyst screening. • Capability of screening

extremely diverse

combinations of catalyst

ingredients.

• Industrial

chemicals

• Engineering

Thermoplastics • Other plastics

• Lower cost • Lower energy usage

• New products based on

newly affordable raw

materials

Polymers • Catalysts • Polymer blends • Surface modifiers

• Faster screening

• Process optimization

• Engineering

plastics

• Thermoplastics

• New products

• New markets such as

automotive glazing

• Reduced domestic

energy consumption. Ceramics • Thermal barrier coating

optimization

• Electronic properties • Higher strength

• Aircraft engines,

advanced power

machines, • Conductors, semiconductors, dielectrics • Machine tools

• Higher engine

temperatures, increased

service life, and reduction of

downtime

• Higher component densities and speeds

• Machining of new

alloys, increased productivity

Advances in both hardware and software will be required to implement HT RD&E methods more broadly. The basic

underlying software technology must be capable defming profitable experimental spaces and visualizing complex data

relationships, and of correlating target materials with prope.rties to permit data-base queries from a broad spectrum of

data mining engines and the development of structure-property relationships. This requires interfacing with data

visualization tools at the back end and statistical experimental design engines on the front end while remaining compliant

with enterprise-wide systems for knowledge management and maintaining control of experimental hardware.

Through competitive proposal submissions from industry teams to the ATP Open Competitions, the ATP can reduce the

cost of implementing high throughput RD&E by cost-sharing the high technical-risk aspects of developing new, generic

tools so that cost-sensitive industrial sectors will be able to invest in this new capability. Successful proposals to the ATP

have the potential to facilitate the emergence ofnew technology platforms by stimulating the development of

partnerships; it can spur the fusion ofnew technologies for subsequent diffusion to other areas; it can facilitate the

integration of complex systems; it can help the integration of otherwise diverse technologies.

59

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60

REFERENCES

1 Certain commercial equipment, instruments, or materials are identified in this paper in order to specify the

experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by the

National Institute of Standards and Technology, nor is it intended to imply that the materials or equipment identified are

necessarily the best available for the purpose. 2 The Global Competitiveness Report, 1996, World Economic Forum, Geneva, Switzerland WORLD BANK, From Plan

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Angewandte Chemie-International Edition 1999, 38: (17) 2495-2532. 4 Five industry White Papers have been received in this area by the ATP. In addition, pre- and full proposals were

submitted to the FY1999 ATP Open Competition with two substantial awards made; significant requests have been made

to the AlP Combinatorial Methods web site; ATP public Workshops held in 1998 and 1999 drew approximately 75 and

50 representatives, respectively; and continued interest is being expressed in workshops attended by ATP staff. 5

Cawse, J., "Information Based Strategies for Combinatorial and High Throughput Materials Development: A White

Paper," General Electric Co. Corporate R&D, 1 1/1999. 6 Technologies, Inc., Santa Clara, CA. "Symyx's patent estate today includes eight issued U.S. patents, as well as

more than 155 patent applications in the U.S. and abroad. 5ymyx's comprehensive intellectual property portfolio

includes patents, patent applications and trade secrets directed toward composition of matter, libraries, synthesis and high

throughput screening methodologies, instrumentation and software" ref. http://www.symyx.com; Patents issued: U.S.

Patent 6,030,917, U.S. Patent 6,004,617 and U.S. Patent 5,985,356. 7KoinumaH., Koida T, Ohnishi T, et al. "Parallel fabrication ofartificially designed superlattices by combinatorial laser

MBE," Appl. Phys. A-Mater. 1999, 69: 529-53 1; Matsumoto Y, Murakami M, Jm ZW, et al., "Combinatorial laser

molecular beam epitaxy (MBE) growth of Mg-Zn-O alloy for band gap engineerg," Japan. I Appl. Phys. 1999, 2 38:

(6AB) L603-L605. 8 For-profit organizations (Knowledge Foundation, CHI, The Catalyst Group, etc.) as well as non-profit organizations

(American Chemical Society, American Physical SocieW, Materials Research Society, Association of Industrial

Chemical Engineers, etc.) have held extensive public discussions ofthis area. Consultation ofthe corresponding web

sites will re-direct interested parties to specific events. In addition, the AlP has held three public workshops:

http://www.atp.nist.gov/www/ccmr/ccmroff.htm. 9 Symyx Technologies press release, April 7, 1999 and Prospectus filed with the U.S. Securities and Exchange

Commission on November 17, 1999 prior to their Initial Public Offering (http://www.sec.gov). 10 http://www.waveftinction.com 11 http://www.msi.com 12 Ref. K.F. Jensen et al. Massachusetts Institute of Technology; R.S. Wegeng et al. Pacific Northwest National

Laboratories; W. Ehrhard et a!. Instut fir Mikroteknik Mainz; J.F. Ryley et al. DuPont, etc. 13 Catalytic micro-reactor with integrated heaters, temperature and flow sensors. Reactants enter at the ends ofthe bar of

the T-shaped reactor, mix and react in the heated channel over a catalyst, and exit at the end ofthe channel. Ref Gleason

et al. , http://web.mit.edu/cheme/www/People/Faculty.

'4W. Ehrfeld, 1MM, Mainz, Germany. 15 http://www.fzk.de/pmt/

16 R.S. Wegeng, PNINL, Redland, WA. 17 K.F.Jensen, MIT, Cambridge, MA, http://www-mtl.mit.edulmtthome/. 18 DL. Quiram et al. Proceedings ofthe 2000 AIChE Spring Meeting, 4" International Conference on Microreaction

Technology, 06 March 2000. 19 DARPA MicroFLUMES Program, http://www.darpa.mil/MTO/mFlumes/index.html. 20 D.A. Hicks, "Time Wars: Is There a Financial Undertow from Accelerating Technical Advance?" R-TManagement

2000, p. 34-39. 21 Forexample, trade journals and presentations at recent public meetings include statements by UOP LLC, General

Electric, DuPont, Dow Chemical, BASF, Shell, etc. 22 Fairley P., Chemical Week, August 11, 1999, pp. 27-33, and references therein. 23 Ref SWOT Analysis of U.S. industry vis a vis combinatorial methods, Appendix Figure 6

http://www.atp.nist.gov/www/ccmr/public.pdf

24Amis E. et al. Polymers Division, Materials Science and Engineering Laboratory, NIST.

25Heilweil E. et al. Optical Division, Physics Laboratory, NIST.

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26 Stranick S. et al. Microstructure Characterization Division, Chemical Sciences and Technology Laboratory, NIST; D.

Kaiser et al. Ceramics Division, Materials Science and Engineering Laboratory, NIST. 27 Handwerker C. et al. Metallurgy Division, Materials Science and Engineering Laboratory, NIST. 28 Fischer D., Ceramics Division, Materials Science and Engineering Laboratory, NIST. 29 • Devaney and J. Hagadorn, High Performance Computing Division, Information Technology Laboratory, NIST. °

XiangXD, Sun XD, Briceno G, Lou YL, Wang KA, Chang HY, Wallacefreedman WG, Chen SW, Schultz PG, A

Combinatorial Approach To Materials Discovery," Science 1995,, 268: (5218) 1738-1740. 31 Current age depends on what is considered combinatorial chemistry. M. Geisen, the "father of combinatorial

chemistry" published his first research paper in the 1980's, and Merrifield's Resin has long been used for separations,

but the methods did not become accepted and automated until the early 1990's. Ref I Combinatorial Chemistry 1999,

1(1), 3-10. 32 Combinatorial methods are most suitable to compositionally-driven materials previously discovered (laboriously)

using purely empirical methods and serial methodologies.

61

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