Combinatorial Approach to 

Thin-Film Silicon Materials 

and Devices

Preprint 

April 2003 • NREL/CP-520-33070 

Q. Wang, H. Moutinho, B. To, J. Perkins, 

D. Ginley, and H.M. Branz 

National Renewable Energy Laboratory

L.R. Tessler 

Instituto de Fisica “Gleb Wataghin” Unicamp 

D. Han 

University of North Carolina at Chapel Hill

To be presented at the 2003 Materials Research 

Society Spring Meeting 

San Francisco, California 

April 21–25, 2003 

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1

Combinatorial approach to thin-film silicon materials and devices

Qi Wang, Leandro R. Tessler1

, Helio Moutinho, Bobby To, John Perkins, Daxing Han2, Dave

Ginley, and Howard M. Branz

National Renewable Energy Laboratory (NREL), 1617 Cole Blvd., Golden, CO 80401 U.S.A.

1

Instituto de Física “Gleb Wataghin,” Unicamp, C. P. 6165, 13083-970 Campinas, SP, Brazil

2

Department of Physics & Astronomy, University of North Carolina at Chapel Hill, Chapel Hill,

NC, 27599 U.S.A.

Abstract

We apply combinatorial approaches to thin-film Si materials and device research. Our

hot-wire chemical vapor deposition chamber is fitted with substrate xyz translation, a motorized

shutter, and interchangeable shadow masks to implement various combinatorial methods. For

example, we have explored, in detail, the transition region through which thin Si changes from

amorphous to microcrystalline silicon. This transition is very sensitive to deposition parameters

such as hydrogen-to-silane dilution of the source gas, chamber pressure, and substrate

temperature. A material library, on just a few substrates, led to a three-dimensional map of the

transition as it occurs in our deposition system. This map guides our scientific studies and

enables us to use several distinct transition materials in our solar-cell optimization research. We

also grew thickness-graded wedge samples spanning the amorphous-to-microcrystalline Si

transition. These single stripes map the temporal change of the thin silicon phase onto a single

spatial dimension. Therefore, the structural, optical, and electrical properties can easily be

studied through the phase transition. We have examined the nature of the phase change on the

wedges with Raman spectroscopy, atomic force microscopy, extended x-ray absorption fine

structure (EXAFS), x-ray absorption near-edge spectroscopy (XANES), ultraviolet reflectivity,

and other techniques. Combinatorial techniques also accelerate our device research. In solar

cells, for example, the combinatorial approach has significantly accelerated the optimization

process of p-, i-, n-, and buffer layers through wide exploration of the complex space of growth

parameters and layer thicknesses. Again, only a few deposition runs are needed. It has also

been useful to correlate the materials properties of single layers in a device to their performance

in the device. We achieve this by depositing layers that extend beyond the device dimensions to

permit independent characterization of the layers. Not only has the combinatorial approach

greatly increased the rate of materials and device experimentation in our laboratory, it has also

been a powerful tool leading to a better understanding of structure-property relationships in thinfilm Si.

Introduction

The combinatorial approach (high-throughput experimentation) has been applied with

success in recent years to thin-film materials research [1-4]. However, the initial work on this

approach was begun by Joseph Hanak almost 30 years ago [5]. Hanak made a continuously

varied composition sample to study binary composition alloys. As now implemented, the

method dramatically shortens the processing time compared to the conventional approach.
2

Development of computer-automated, high-throughput characterizations makes possible full use

of the combinatorial approach. Combinatorial sample deposition, measurements, and data

analysis must all be optimized for successful research. Only recently has the combination of

deposition tools, computing power, automation, and, more importantly, characterization

techniques, become available to allow true combinatorial approaches. In our laboratory, research

that previously required up to a year can now be completed in a few weeks.

In spite of more than 25 years of hydrogenated amorphous silicon (a-Si:H) research, the

properties of thin-film materials and performance of devices for photovoltaic and related

applications remain a significant technical challenge. For example, the properties of undoped

thin-film Si that grows near the transition from amorphous to microcrystalline silicon [6, 7] not

only depends on the atomic H content in the Si film, but also on many other deposition

parameters such as substrate temperature, gas mixture, and gas pressure. Clear fundamental

understanding of these better materials is still not established; however, the applications have

advanced rapidly. The gradual nature of structural transition and the dependence on multiple

deposition variables make the research more difficult. For example, most doped a-Si:H thin

films have either B or P doped into a binary alloy (Si and H) or B doped into a tertiary alloy (Si,

C, and H). The challenges are even greater because, in applications, the doped a-Si:H materials

are normally very thin (tens of nm). In device applications, state-of-the-art solar cells also utilize

materials that are grown very close to a structural phase transition to improve performance [7]. In

addition to theses materials issues, the production of optimized devices is still laboratory

dependent: certain procedures are more successful in one lab than others. Each laboratory must

perform its own painstaking optimizations on its own deposition equipment. The properties of

the materials and the device performance are still lacking strong causal correlations to guide this

process to completion. Although there are some general guiding principles, device making is

still more often art than science—device optimization has often required years of slow, empirical

experimentation. Therefore, amorphous Si and related materials, and the devices made from

them, are excellent candidates for using the combinatorial approach. In this paper, we will

present our work on amorphous Si based materials and device research using our unique

combinatorial hot-wire chemical vapor deposition (HWCVD) system. However, applications of

this approach should not be limited to HWCVD. Combinatorial approaches to materials and

device research can be used profitably in plasma-enhanced CVD, sputtering, and other

deposition techniques.

Combinatorial HWCVD system

In NREL’s conventional HWCVD deposition system, a stainless-steel vacuum chamber

with a base pressure of less than 10-6 Torr is used. A spiral 0.5-mm-diameter, 13-cm-long

tungsten wire is heated to about 2000°C using an ac or dc current. The hot wire is normally

placed 5 cm below a typically 2.5-cm x 2.5-cmor 6.35-cm x 6.35-cm heated Corning 1737

substrate. Process gases such as SiH4 decompose on the wire surface. Atomic Si, H, and silane

radicals react in the chamber, and reactive radicals form a film on a substrate. For a-Si:H

deposition with SiH4 flow rate of 20 sccm and a chamber pressure of 10 mTorr, a film of devicequality a-Si:H can be deposited at a deposition rate of about 10 Å/s [8].
3

Figure 1. Schematic diagram of the NREL combinatorial HWCVD system.

Figure 1 is a schematic of our combinatorial HWCVD system [9] which is a modified

version of NREL’s conventional HWCVD system. There are two key modifications: The first is

to add a physical mask or a set of masks to deposit the film only on the selected partial area of a

substrate. The second is to add a sample manipulator (xyz) that allows a relative xy movement

between the mask and the substrate so that the film can be deposited at any position on the

substrate. The z-translations are used primarily to move the sample and then ensure a tight

contact between the substrate and the mask. This prevents the deposition of materials “shadows”

from reactant that would diffuse under loose-fitting masks. The vacuum chamber, filament, and

gas inlet are identical to NREL’s conventional system. The combinatorial deposition speeds up

the sample deposition primarily because pump down cycles between samples are avoided. The

system also adds considerable functionality, especially because we have developed a set of

masks that are interchangeable in vacuum.

Figure 2 shows the simple example of making a library of discrete variable samples by

combinatorial deposition. On the left is a shadow mask with a small open square in the middle.

We move the substrate or the mask, using the xy manipulator, to position 1 on the substrate, as

indicated in the center figure and deposit the first film. Then, we move the open square to the

position 2 and make the second film. The mask isolates each sample from the others. This

procedure was repeated for all 16 locations in this example. The optical image shows an actual

combinatorial sample on 2.5-cm x 2.5-cm glass substrate. The various gray scales or different

colors indicate the thickness or the optical index changes to the various deposition parameters.

This approach greatly reduces the time spent on the cycle of loading, heating, and

Throttling

Valve Control

SiH4 -> Si + 4 H

W Filament ~2000°C

Vacuum Pump

Shadow Mask

Sample xyz manipulator

Heater 

Process Gases

SiH4, H2, etc.

Substrate 
4

Figure 2. a) Schematic diagram of the mask used to deposit discrete square

samples; b) schematic of the sample pattern obtained by stepping the sample

beneath the mask between each of 16 depositions; and c) an optical image of the

resulting film.

Figure 3. Schematic diagram of the process for making continuously wedged

samples with continuously variable thickness. The shutter is placed close to the

shadow mask. The motor speed and deposition rate determine the thickness

grading.

SiH Motor 4+H2

Shadow Mask Motorized shutter

Wedged Film

Substrate

Hot wire

Shadow Mask

Shadow mask

1 2 3 4

5 6 7 8

9 10 11 12

13 14 15 16

y

x

a bc
5

Figure 4. Some deposition factors directly or indirectly determine the thin film

properties. This illustration shows the scope of deposition parameters that can be

chosen in the combinatorial depositions.

cooling in between the samples in the conventional deposition. A factor-of-10 reduction of total

deposition time can be achieved easily.

Figure 3 shows how we make samples with a continuously changing variable such as

thickness. In principle, the substrate temperature (by means of the hot and cold ends) and the gas

composition (by the means of timing the gas flow rate) can also be continuously changed. To

make a thickness-graded stripe sample, a physical mask with a rectangular aperture of 5 x 50 mm

and a motor-driven shutter are used. The thickness profile along the stripe is controlled by the

motor speed and deposition rate. After the film of one stripe is deposited, the substrate can be

moved to another location for deposition of another stripe. Libraries with as many as ten separate

wedged stripes are made on a 6.35-cm x 6.35-cm substrate. This combination of discrete and

continuous deposition provides a powerful tool to study the sensitive phase transition with regard

to the various deposition parameters. We will show our work on the thickness-dependent phase

transition from amorphous to microcrystalline silicon on one single substrate below.

In the hot-wire CVD process, many variables, also called “factors,” can affect the amount

of SiH4 in the reaction region, the density of reactants at the film surface and the film formation

reactions. These factors, taken together, determine the structure and properties of the films. For a

given deposition system, chamber geometry, chamber pressure, source of gas, gas flow rate,

direction of gas flow, gas mixture ratio, Tsub, substrate, deposition time, filament temperature,

distance from filament to the substrate, number of filaments, and post treatments are all

important factors. Figure 4 lists some of the important factors in any thin-film deposition that

affect the properties of the films. From an engineering point of view, the combinatorial approach

dramatically increases the throughput of experimentation and is an ideal tool to map the film

properties as a function of many variables. The mapping can be done with a short time even if all

the detailed mechanisms of growth are still unknown.

In one study, we selected three variables in the HWCVD process to create a small film

library to study the phase transition from amorphous to microcrystalline silicon. Silane flow rate

and hydrogen flow rate were obvious and convenient choices. We select the throttling valve

position (TVP) as the third variable because it is an independent deposition factor with

• System: chamber geometry

• Sources: gas and gas flow rate

• Input power

• Chamber pressure

• Substrate temperature

• Deposition time

• Substrate type

Film Properties 
6

Figure 5. Chamber pressure dependence on the H2 gas flow rate (a), throttling

valve position (b), and in a 2-D contour plot (c). The gray scale on the right

indicates the chamber pressure in mTorr.

which we partially control the chamber pressure. We use hydrogen as an example because of its

high flow rate. It will apply to other gases, too. The chamber pressure of hydrogen in the

chamber depends on the gas flow rate and the TVP. Figure 5 shows how pressure changes with

gas flow rate at the fixed TVP of 45 % (Fig. 5a) and with pressure varying with TVP at a fixed

gas flow rate of 15 sccm (Fig. 5b). Fig. 5c, shows a contour plot of chamber pressure as a

function of a gas flow rate and TVP. To clarify the meaning of TVP, the valve is fully open at

100% and closed at 0%. Pressure has a linear dependence on the gas flow rate (for a fixed TVP

of 45%) and rapidly increases with decreasing TVP below 50% (for a fixed gas flow rate of 15

sccm). Due to the nature of the pressure’s dual dependence, one can achieve the same pressure

by changing the gas flow rate or the TVP. However, the gas pressure alone is not enough to

determine that the same material will always be produced. For example, for a-Si:H films with

SiH4 gas, different combinations of gas flow rate and TVP with the same pressure give different

films. This is even more complex when using a mixture of gases such as SiH4, H2, and others. In

this paper, we plot our results based on the factor, TVP, even though pressure has a more

obvious physical meaning.

45 50 55 60 65 70

200

180

160

140

120

100

80

60

40

20

0

Flow Rate (sccm)

Throttling Valve (%)

0

50

100

150

200

250

300

200

100

0

Pressure (mTorr)

0 100 200 300

Flow Rate (sccm)

50

40

30

20

10

0

Pressure (mTorr)

40 50 60 70 80

Throttling Valve Position (%)

Chamber pressure (mTorr)

a

c

b
7

Figure 6. Left, Raman spectroscopy vs. H dilution at TVP of 60% and 3 sccm of

silane flow rate. Right, amorphous-to-microcrystalline Si phase diagram as a

function of SiH4 flow rate, H2 flow rate, and throttling valve positions. The dots

represent some of the experimental points where the sample was made. The

shaded area denotes a-Si, unshaded is area μc-Si, and the boundary in between is

the transition region.

Results and discussion

In this section, we examine several specific examples that demonstrate the power of the

combinatorial approach in thin-film Si research. These are (1) a small-scale materials library, (2)

a study of the thickness-dependent structure changes, and (3) the effect on a buffer layer at the

solar cell p/i interface.

1. Amorphous-to-microcrystalline silicon library

Figure 6 presents the a-Si-to-μc-Si phase diagram as a function of three variables: silane flow

rate, hydrogen flow rate, and throttling valve position (TVP, see above). The dots in the figure

illustrate the location of the samples in the hydrogen-TVP plane for one of the four silane flowrates we explored. In total, 130 samples were made sequentially on only 10 substrates (each

substrate has less than 16 samples) for a total of 9 vacuum breaks. In each hydrogen-TPV plane,

the shaded area represents materials in the amorphous phase and the unshaded area represents

material with a microcrystalline phase. The four planes represent silane flow rates of 3, 8, 16,

and 22 sccm, respectively. The boundary between the amorphous and microcrystalline phase is

where the materials in transition are located. The structure of each sample was determined by

the Raman spectroscopy and UV reflectance measurements (Model 1280, n&k Technology, Inc,

Santa Clara, CA). Raman spectra at the left of the figure represent a series of H-dilution samples

with silane flow rate of 3 sccm and TVP at 60%.

H2 Flow Rate (sccm)

Throttling Valve Position (%)

SiH4 Flow Rate (sccm)

0 50 100 150 200

3

8

16

22

50

60

70

80

a-Si:H μc-Si

Transition-Si

350 400 450 500 550 600

Intensity (a.u.)

Raman shift (cm- 1)

520 cm- 1

1:1

2:1

3:1

4:1

5:1

10:1

20:1

H2/SiH4

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

130 samples
8

We found that the material phase depends nonlinearly on all the variables: hydrogen flow

rate, silane flow rate, and the throttling valve position. From Fig. 6, one sees that the ratio of

hydrogen to silane is not a unique factor that describes whether the material will grow

amorphous or microcrystalline. At the lowest silane flow rates (3 and 8 sccm), it is easy to

change to μc-Si with the mixture of only a small amount of H2. At higher silane flow rates (16

and 22 sccm), it requires higher H dilutions and an open throttle valve to deposit μc-Si. This

film library has guided us for our many HW solar cells applications. Note that this phase diagram

is based entirely on measurement of thick (>200 nm) films. The thickness dependence of the

phase transition was addressed in a study of continuously thickness-graded samples as described

below.

Figure 7. Thickness dependence of a-Si-to-μc-Si phase transition in samples

continuously graded thickness. Left, an optical image of a combinatorial sample

with a thickness grading in horizontal direction and H-dilution in the vertical

direction, as indicated by the R for each stripe. Right, a summary plot on the

stripe number 2 of R = 2. The optical image of the stripe is placed on the top, and

a collections of six AFM pictures with roughly matched positions on the stripe is

under that. The figure below shows the thickness variation and the phase changes

along the stripe. The insert cartoon best describes the profile of the interesting

stripe with a large portion of transition materials.

2. Thickness-dependent phase transition

The left picture in Fig. 7 is an optical-reflection image obtained by placing a ten-stripe

continuously thickness-graded sample in a conventional color image scanner. This sample has

discrete H-dilution stripes arrayed in the vertical direction, deposited with H2-to-SiH4 ratios (R)

of 0, 1, 2, 3, 4, 5, 8, 10, 15, and 20. The SiH4 flow rate was fixed at 8 sccm. Each stripe has a

thickness grading ranging from about 200 to 1600 Å. This special sample varies by two

deposition parameters: ten discrete H-dilutions and continuously varied thicknesses. From these

0

200

400

600

800

1000

1200

1400

1600

1800

0 20 40

Position (mm)

Thickness (Å)

-1

0

1

2

3

Phase (0:a-Si,1/aμ,2/μc-Si)

a-Si:H

In transition

μc-Si

H-Dilution

 R

Thickness wedge

0

20

1

4

3

15

10

8

2

5
9

parameters, we can construct an evolutionary-phase diagram as a function of H-dilution and

thickness for HWCVD Si by measuring the Raman or UV reflectance of the sample [10, 11]. The

substrate temperature is 200°C, and the chamber pressure ranges from 6 to 57 mTorr, depending

on R. The total deposition time for the entire 10-stripe sample was just over 2 hours. The gray

scale change along each stripe indicates the thickness variation. The gray scale or color shift

among the stripes directly indicates both the decrease of deposition rate and an increase of μc-Si

fraction in the film with increasing R.

By measuring UV reflectance and observing the peaks at 275 and 360 nm, we are able to

quickly determine whether or not there is crystallinity within the top 100 Å of the film [3, 12].

We found that with R > 2, all the stripes are in μc-Si phase everywhere on the stripes. The stripe

with R=0, as expected, is entirely the a-Si phase. The stripe with R=1 was amorphous along most

of its length, showing the signal of μc-Si only at the thickest end. The stripe with R=2 has a long

transition phase. For this reason, it is of the greatest interest, and we have simulated it

accordingly to the need to develop high-throughput characterization techniques to measure this

special stripe.

The right side graph in Fig. 7 is a summary plot of film properties of surface morphology,

thickness, and corresponding phase along the stripe. The top picture is a scanner image of the

stripe. Just below this image is a composite of six AFM images arranged to be in roughly the

correct position on the stripe. This composite AFM image shows that the a-Si:H surface is rather

smooth compared to the much rougher μc-Si. Interestingly, a large range in the middle of the

stripe appears rather smooth, although the UV reflectivity and Raman measurements revealed

that this material is already undergoing the phase transition at this thickness. The roughness is

about 10 Å for a-Si:H, 15 Å for transition materials, and 46 Å in the μc-Si. The thickness of this

stripe changes from 200 to 1600 Å across its 50-mm length, as shown in the main graph. The

thickness increases quite linearly from 200 to 1600 Å along the positions from 0 to 40 mm.

However, in the last 10 mm the thickness is quite constant because (1) the deposition rate

decreases when μc-Si growth commences and (2) there is some deposition rate inhomogeneity in

our HWCVD reactor. To plot phase results, we denote a-Si:H with a 0; transition or mixed

phase Si as 1; and μc-Si as 2. For thicknesses less than 600 Å, the material is in a-Si:H phase.

For thicknesses of more than 1500 Å, μc-Si starts to grow, and between 600 and 1500 Å, the

material appears to be mixed phase (in transition). The wedge cartoon is a schematic illustration

of the phase evolution from amorphous-to-microcrystalline silicon in this stripe. Our results are

in qualitative in agreement with Collins’ in-situ ellipsometry measurement for PECVD films

[13].

Figure 8 shows the extended x-ray absorption fine structure (EXAFS) (Fig. 8a) and which

x-ray absorption near-edge spectroscopy (XANES) (Fig. 8b) results on the stripe (Fig. 7) that has

a large section of transition region from the amorphous-to-microcrystalline phase. The EXAFS

spectra have been measured along the stripe from a-Si:H to μc-Si as indicated with sample

coordinate x. From EXAFS spectra, one can perform numerical fitting to get the average

interatomic distance (r) and the radial Debye-Waller factor ( 2 σ incr ). The detailed fitting

procedure has been published elsewhere [14]. The results in Fig. 8a show the decrease of 2 σ incr

(which becomes negative) and the subtle decrease of r as the crystalline fraction of the sample

increases. The negative 2 σ incr is a consequence of the imposed average coordination N = 4: the

average coordination of both a-Si:H and μc-Si are expected to be below 4, and imposing a

higher coordination is compensated by a decrease in 2 σ incr .
10

Figure 8. EXAFS study (Fig. 8a) and XANS study (Fig. 8b) on the strips sample

in Fig. 7.a), incremental Debye-Waller factor (relative to single-crystal Si), and

average first neighbor separation. Four fold coordination was imposed in the

fitting procedure. The lines are guides for the eye. (b) x-ray absorption

spectroscopy signal with the single scattering (EXAFS) contribution subtracted.

The numbers in the figure represent the x coordinate, and the letters follow the

peak assignment. The coordination is the same as in Fig.7.

Figure 8b show the XANS spectra at various positions on the stripe together with that of a

c-Si reference [15]. In the single crystal, we can clearly identify the A, B, C, and D multiple

scattering peaks that are attributed to double scattering paths. In the a-Si:H side of the sample, no

peaks are found. In the μc-Si side, only peak A can be identified. In order to isolate the multiple

scattering effects, we have subtracted all spectra from the one obtained at x = 2.5 mm, where

only a-Si:H is present. In the a-Si part of the sample, indeed, there are no multiple scattering

signals. In the μc-Si part, the dominating path is due to scattering by two adjacent atoms of the

first coordination shell. This surprising result indicates that the bond-angle disorder of μc-Si is

enough to suppress the multiple scattering signals from atoms beyond the first coordination shell.

In amorphous silicon, bond-angle disorder suppresses even the contribution from the first shell.

The main consequence of this result is that the μc-Si formed at the transition region and even at

the end of the strip (highly μc-Si) is much more disordered than single crystal-silicon —to a

point that the second-neighbor shell disorder is comparable to the first-neighbor shell disorder in

a-Si:H.

3. Optimization of devices

In the thin-film devices such as solar cells, the device structure combines three or more

layers. This structure is naturally suited for the combinatorial HWCVD approach because

different masks can be used on each layer, thereby giving more information than in conventional

devices. Certainly, all device-makers would like to know how the properties of each layer relate

to device performance. By using the combinatorial approach, this kind of insight can be

obtained.

-0.002

0.000

0.002

Incre

m

ental s 2 (Å

2

)

0 10 20 30 40 50

2.34

2.36

2.38

2.40

r (Å)

Sample coordinate x (mm) 2 4 6 8

A B C D

Single

crystal

15.5

25.5

32.5

35.5

42.5

45.0

Signal

k (Å-1)

a b
11

Figure 9. Effects of a buffer layer and its thickness at p/i interface on a diode in

one combinatorial sample. Left, a schematic of device n-i-b-p structure and layer

locations (top and side views) of the combinatorial sample. The top dot array is

the top contact to evaluate the devices. The thickness-graded buffer layer is

deposited at the p/i interface, but offset to have the buffer layer on the substrate.

Right, the dark current as a function of the positions (the buffer layer thickness) at

various voltage biases. The scale of the thickness is plotted on top of the figure.

Figure 9 shows a combinatorial device we made to study the effect of a single device

layer— the thin buffer (b) layer between the p and i-layers — on diode performance. A

schematic of the device structure is shown on the left. Using a single mask, the thickness graded

buffer layer was offset from the n-i-p diode. In this way, part of the buffer layer was incorporated

into the device and part was deposited directly on the substrate. The cross section of the device

shows that n-i-p, n-i-b-p, and b can be measured independently. In the perpendicular direction,

the thickness of the buffer layer was graded. The 50-mm-long wedge incorporates 30 top Pd

contacts that we used to evaluate the device performance versus thickness. The thickness of the

buffer layer was directly measured on the offset b-layer. The graph shows the logarithm of the

dark current at various voltage biases, plotted as a function of diode position.

The diode position is directly related to the thickness of the buffer layer, as indicated

schematically by the triangular wedge above the graph. The results show that the buffer layer has

little effect on the reverse current but does affect the forward current. At V=1.5 V and with 450

Å of buffer layer the dark current, increases by about a factor of 10 when compared to either the

zero- or 700-Å-thick buffer layers. With only one sample, the effect of buffer layer and its

thickness on the device performance can be readily studied. Substrate n-layer i-layer p-layer 1 10 20 30 Thickness graded

1.0E-09

1.0E-08

1.0E-07

1.0E-06

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

0 10 2 0 30

Position of Diode

Current (A)

V=-1.5 V=0.9

V=1.5 V=2.1

713 Å 130Å 450 Å
12

Summary

We have demonstrated that combinatorial studies can be a powerful tool for materials and

device research in thin-film silicon. The combinatorial samples have not only greatly speeded up

the deposition process, but also stimulated development of many high-throughput

characterizations to measure the samples. Developing fast characterization and data analysis

tools for a large number of samples has become critical for optimizing processes and searching

for new materials. With our combinatorial HWCVD tool, we efficiently created a material

library of the transition from a-Si:H to μc-Si and were able to using this information to guide

our device research. We were able to provide new XANES information about the transition

material and hope to accelerate the understanding of ordering in the transition materials. For

thin-film device applications, we demonstrated that the combinatorial approach can also make

important contributions to device optimization and to correlation of films properties to device

performance. Increasing the experimental efficiency, i.e., the experimental throughput, is a

central motivation for the combinatorial approach. Based on our initial work, the combinatorial

approach has speeded up the rate of experimentation by at least a factor of 10 in our HWCVD

thin-film Si research.

Acknowledgements

The author would like to thank Richard Crandall, Brent P. Nelson, and Yueqin Xu for

discussions and help. This work is supported by the U.S. Department of Energy under

subcontract No. DE-AC39-98-GO10337 and DDRD research funded at NREL.

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 Combinatorial Approach to Thin-Film Silicon Materials and Devices: Preprint 

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National Renewable Energy Laboratory, 1617 Cole Blvd., Golden, CO 80401-3393 

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13. ABSTRACT (Maximum 200 words): We apply combinatorial approaches to thin-film Si materials and device research. Our hot-wire 

chemical vapor deposition chamber is fitted with substrate xyz translation, a motorized shutter, and interchangable shadow 

masks to implement various combinatorial methods. For example, we have explored, in detail, the transition region through 

which thin Si changes from amorphous to microcrystalline silicon. This transition is very sensitive to deposition parameters 

such as hydrogen-to-silane dilution of the source gas, chamber pressure, and substrate temperature. A material library, on 

just a few substrates, led to a three-dimensional map of the transition as it occurs in our deposition system. This map guides 

our scientific studies and enables us to use several distinct transition materials in our solar-cell optimization research. We 

also grew thickness-graded wedge samples spanning the amorphous-to-microcrystalline Si transition. These single stripes 

map the temporal change of the thin silicon phase onto a single spatial dimension. Therefore, the structural, optical, and 

electrical properties can easily be studied through the phase transition. We have examined the nature of the phase change on 

the wedges with Raman spectroscopy, atomic force microscopy, extended x-ray absorption fine structure (EXAFS), x-ray 

absorption near-edge spectroscopy (XANES), ultraviolet reflectivity, and other techniques. Combinatorial techniques also 

accelerate our device research. In solar cells, for example, the combinatorial approach has significantly accelerated the 

optimization process of p-, i-, n-, and buffer layers through wide exploration of the complex space of growth parameters and 

layer thicknesses. Again, only a few deposition runs are needed. It has also been useful to correlate the materials properties 

of single layers in a device to their performance in the device. We achieve this by depositing layers that extend beyond the 

device dimensions to permit independent characterization of the layers. Not only has the combinatorial approach greatly 

increased the rate of materials and device experimentation in our laboratory, it has also been a powerful tool leading to a 

better understanding of structure-property relationships in thin film Si. 

14. SUBJECT TERMS: PV; hot-wire chemical vapor deposition; x-ray absorption near-edge 15. NUMBER OF PAGES

spectroscopy (XANES); extended x-ray absorption fine structure (EXAFS); Raman 

spectroscopy; atomic force microscopy; microcrystalline silicon; 16. PRICE CODE

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