National Renewable Energy Laboratory 

Innovation for Our Energy Future 

A national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

NREL is operated by Midwest Research Institute ● Battelle Contract No. DE-AC36-99-GO10337 

Tolerance of Three-Stage CIGS 

Deposition to Variations Imposed 

by Roll-to-Roll Processing 

Final Technical Report 

May 2003 – September 2005 

M.E. Beck and J.S. Britt 

Global Solar Energy, Inc. 

Tucson, Arizona 

Subcontract Report 

NREL/SR-520-39119 

January 2006 
Tolerance of Three-Stage CIGS 

Deposition to Variations Imposed 

by Roll-to-Roll Processing 

Final Technical Report 

May 2003 – September 2005 

M.E. Beck and J.S. Britt 

Global Solar Energy, Inc. 

Tucson, Arizona 

NREL Technical Monitor: H. S. Ullal 

Prepared under Subcontract No. ZDJ-2-30630-14 

Subcontract Report 

NREL/SR-520-39119 

January 2006 

National Renewable Energy Laboratory 

1617 Cole Boulevard, Golden, Colorado 80401-3393 

303-275-3000 • www.nrel.gov 

Operated for the U.S. Department of Energy 

Office of Energy Efficiency and Renewable Energy 

by Midwest Research Institute • Battelle 

Contract No. DE-AC36-99-GO10337
This publication was reproduced from the best available copy 

submitted by the subcontractor and received no editorial review at NREL.

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TABLE OF CONTENTS 

1 Introduction................................................................................................................................... 

1.1 Background ............................................................................................................................. 

1.2 Technical Work Plan............................................................................................................... 

1.3 Technical Approach................................................................................................................

2 Maximum Cu Ratio During CIGS Growth...................................................................................

2.1 Bell Jar Studies .......................................................................................................................

2.2 Implications for Production ....................................................................................................

3 Film Growth..................................................................................................................................

3.1 Bell Jar Studies ......................................................................................................................

3.2 Production Ga/(In+Ga) Profile ...............................................................................................

3.3 Production Tsub and Na Precursor Sensitivity.........................................................................

3.4 Production Se Delivery Sensitivity.........................................................................................

4 Post-Deposition Treatments..........................................................................................................

5 Feedstock Purity............................................................................................................................

6 Further Production Sensitivities....................................................................................................

7 Technical Summary ...................................................................................................................... 

8 Team Activities............................................................................................................................. 

9 Phase III Publications, Presentations, and Reports....................................................................... 

10 References..................................................................................................................................... 

1

1 

3 

4

4

4

7

8

8

8

10

11

12

13

14

16

17

17

18

iii
LIST OF FIGURES 

Figure 1 Best-fit surfaces for a) efficiency and b) Voc as a function of maximum Cu ratio and atoms in stage 3.......... 6 

Figure 2 Interaction chart summarizing device efficiency from roll-coaters as a function of maximum and 

final Cu ratio .................................................................................................................................................... 7 

Figure 3 Results from experimental design varying deposition temperature and CIGS thickness (by source 

temperature or web thickness) in roll-coaters, at constant Cu ratio ................................................................. 7 

Figure 4 Desired (left) and undesired (right) IR profile for a GSE mimic deposition at ITN ........................................ 8 

Figure 5 Isc,/Voc characteristics of In/Ga flux test lots.................................................................................................... 10 

Figure 6 Fitted surface of CIGS to back contact adhesion as a function of Tsub during precursor deposition and 

rate ................................................................................................................................................................... 10 

Figure 7 Pmax as a function of Tsub during Na precursor deposition and rate.................................................................. 11 

Figure 8 Average production cell power as a function of Se rate delivery..................................................................... 11 

Figure 9 Box and whisker plot of efficiency for thioacetamide treated samples and control devices............................ 12 

Figure 10 Representative current-voltage trace for a treated and an untreated device ..................................................... 12 

Figure 11 CIGS device efficiencies with and without exposure to post-deposition treatment......................................... 13 

Figure 12 Box and Whisker plots of efficiency (left) and Jsc (right) versus source purity................................................ 14 

Figure 13 Distribution and average efficiency before and after Mo process optimization............................................... 15 

Figure 14 SIMS depth profile through standard back contact (400), and an alternate back contact sequence 

of two different thicknesses (277 and 339) ...................................................................................................... 16 

Figure 15 CIGS device efficiency as function of back contact type – #1 denotes the standard GSE 

back contact ..................................................................................................................................................... 16 

LIST OF TABLES 

Table 1 Sample and device characteristics.................................................................................................................... 5 

Table 2 List of statistically significant relationships from this study’s data ................................................................. 6 

Table 3 Cell performance summary for test lots ........................................................................................................... 9 

Table 4 Expenses or savings expected from increasing or decreasing source purity by one ninth ............................... 13 

Table 5 Metals purity levels.......................................................................................................................................... 14 

Table 6 Best device parameters..................................................................................................................................... 14 

iv
Executive Summary 

Two and three stage co-evaporation have come to be viewed as benchmark laboratory methods for CuInxGa1-xSe2 

(CIGS) absorber deposition, having produced CIGS device efficiencies greater than 15% reproducibly in a number of 

laboratories. Although quite successful and relatively easy to implement on a small R&D scale, scale-up to a commercial 

level proves to be challenging. Yet, large area, continuous manufacturing processes represent the most economically 

attractive path for thin film PV commercialization. Large area, continuous processes necessarily differ substantially from 

laboratory methods, and direct use of the processes developed in the laboratory is not feasible. Differences are imposed 

both by continuous processing of moving substrates, and by requirements for decreased costs and increased throughput. For 

implementation of viable, large scale PV manufacturing methods on low-cost substrates it is necessary to understand the 

tolerance of the established laboratory processes to variations in deposition procedures, as they apply to low-cost roll-to-roll 

(RTR) processing onto lightweight stainless steel foils. 

As a Technology Partner to NREL under the Thin-Film Photovoltaics Partnerships Program (TFPPP) the purpose 

of this subcontract was to move CIGS photovoltaics toward large-scale, cost-effective, manufacturing by examining the 

tolerance of three-stage deposition to changes in processing variables consistent with continuous RTR manufacturing at 

Global Solar Energy (GSE). The final objective of this work was the demonstration of commercial, low-cost and robust 

modules. Increasing production cell efficiency, as well as yield, represented the key aspects of this effort. 

Prior to this three-year program, GSE had demonstrated average large area production device efficiencies in the 

7-8% range with best devices greater than 10%. Goals under this TFPPP subcontract were to raise both numbers by 2 

percentage points. Pre-contract production yield was 20% and was to be increased to 80%. All work proceeded as planed: 

production yield was improved to 90% while the average production efficiency has been raised to 10%, with peak 

efficiencies exceeding 13%. 

During Phase I, a three-stage bell jar process was established at ITN, characterization of the GSE RTR production 

processes began, and the bell jar system was used to explore some sensitivities of the three-stage process. In Phase II, 

characterization of the GSE RTR production processes in terms of major variables was completed, further process 

sensitivities were explored in the bell jar, and application of process tolerance information to the roll-coaters began. Under

Phase III efforts begun in Phase II were completed, verification at the production level conducted, production RTR 

processes refined, and impacts of feedstock purity on resulting device quality assessed. 

More precisely, process sensitivities to the degree of Cu-rich excursion (2nd stage), final Cu/(In+Ga) ratio as well as 

Ga/(In+Ga) distribution were studied at the production level. Based on these experiments it was concluded that a maximum 

Cu ratio of 1.1 allows for a more robust process than a maximum Cu ratio of 1.0, while the latter may yield slightly higher 

absolute device efficiencies. As for the group III elemental distribution, various Ga/(In+Ga) profiles throughout the 

absorber yield maximum efficiencies, but a robust process can be achieved for a narrow profile only. 

Furthermore, the parameter space of the Na-precursor deposition and Se delivery have been analyzed. The former 

was found to have a significant impact on absorber adhesion, while insufficient or excessive Se delivery resulted in device 

performance degradation. Back contact optimization efforts lead to reduced Cr diffusion into the absorber while 

simultaneously enhancing CIGS adhesion. 

Finally, the cumulative efforts of this program lead to the conclusion that stationary bell jar experiments cannot 

adequately simulate the dynamics in roll-to-roll film growth. Further investigations of the process changes resulting from 

this work as to their impacts on product reliability, coupled with fine tuned, as well as cost-optimized production methods, 

form the cornerstones of future efforts at GSE. 

v
1 Introduction 

1.1 Background 

Two and three stage co-evaporation have come to be viewed as benchmark laboratory methods for 

CuInxGa1-xSe2 (CIGS) absorber deposition, having produced CIGS device efficiencies greater than 15% reproducibly 

in a number of laboratories. Although quite successful and relatively easy to implement on a small R&D scale, 

scale-up to a commercial level proves to be challenging. Yet, large area, continuous manufacturing processes 

represent the most economically attractive path for thin film PV commercialization. Large area, continuous 

processes necessarily differ substantially from laboratory methods, and direct use of the processes developed in the 

laboratory is not feasible. Differences are imposed both by continuous processing of moving substrates, and by 

requirements for decreased costs and increased throughput. For implementation of viable, large scale PV 

manufacturing methods on low-cost substrates it is necessary to understand the tolerance of the established 

laboratory processes to variations in deposition procedures, as they apply to low-cost roll-to-roll (RTR) processing 

onto lightweight stainless steel foils. 

Only limited information is available in the literature addressing the tolerance of the laboratory processes to 

several variations. Some studies have been published related to CIGS thickness,1

 maximum deposition temperature 

and time spent by the film in the Cu-rich stage,2,3

 Na content,4,5 rate profiles,6 and final overall Cu/(In+Ga) atomic 

ratio.7

 Not only are there additional, at times more important, absorber characteristics that define the quality of the 

resulting absorber for use in a PV device, but these experiments were conducted without correlation to practical 

commercial fabrication methods. Further variations to the deposition procedure may be encountered in the 

manufacturing environment and include: 

• Significantly shortened overall deposition times, 

• Instantaneous variations in the Se/metals flux ratio outside the typically-recommended envelope due to spatial 

distribution of metallic flux, 

• Impurities expected from less expensive, less pure source materials or alternative substrates, 

• Deviation of substrate temperature from the prescribed two- and three-stage values, 

• Variation in the fraction of group III elements deposited in the first versus third stages, 

• Variations in sample cool-down procedures and post-CIGS handling, and 

• Exposure to species outgassed and reflected from hot chamber walls. 

During the course of this subcontract, Global Solar Energy, Inc. (GSE) and lower-tier subcontractor ITN 

Energy Systems, Inc. (ITN) addressed these process tolerance issues. The definition and resolution of process 

tolerance issues satisfy many of the goals of the Thin Film Photovoltaics Partnerships Program (TFPPP). First, the 

investigation identified acceptable ranges for critical deposition parameters, providing upper and lower control 

limits for in-situ process monitoring components, thus increasing average efficiency as well as yield of product. 

Second, the exploration uncovered insensitivities to some processing procedures, allowing module manufacturing at 

increased throughput and decreased cost. The exploration allowed for a quantitative evaluation of the trade-offs 

between performance, throughput, and costs. Third, the program also satisfied the TFPPP goal of establishing a 

wider research and development base for higher-efficiency processing. Fourth, the acquisition of data defining 

sensitivity to processing has important implications for the required accuracy of process sensors and control. 

Finally, the program aided the photovoltaic community advance toward a better understanding of CIGS growth, a 

longer-term goal of the TFPPP. 

Three-stage co-evaporation of CIGS imposes stringent limits on the parameter space if high efficient 

devices are to result. Substrate temperatures during the 1st stage as well as during the 2nd and 3rd stage, Se partial 

pressure, and amount of Na supplied are critical for good nucleation, proper In-Ga-selenide precursor phase, and 

diffusion of Cu into the precursor as well as diffusion of Ga through the film. In addition, the degree of Cu-rich 

excursion impacts maximum performance and process tolerance. Enveloping the above is the basic timetemperature profile inextricably linked to the metals delivery rates. While high efficiency, three-stage deposited 

CIGS devices on the R&D scale are grown at about 20-45 minutes to thicknesses of 2 to 2.5 μm, the latter is not a 

viable approach for an economic manufacturing process. At GSE, CIGS films are typically grown in about 

1
6 minutes to thicknesses of less than 2 μm. At the same time, the emissivity and thermal conductivity of SS is vastly 

different from that of glass, and the reduced growth time poses restrictions on the substrate temperature ramp rates 

and diffusion of species (reaction kinetics). Material compatibility in the highly corrosive Se environment places 

limitations on the substrate heaters; i.e., substrate temperatures. Finally, one key advantage of a RTR deposition 

approach (compact equipment) restricts post CIGS Se exposure and cool down rates to be vastly different than those 

practiced in the laboratory. 

To form a complete picture of conditions in the production systems, metals flux profiles as a function of Se 

pressure were documented once the Se impingement rates were derived from in-situ sensor data. Time-temperature 

profiles for the substrate were measured using substrate equipped with temperature sensors processed through a 

production coater. 

Utilizing the stationary deposition in the bell-jar, the following process variations on device performance 

were quantified: CIGS cool-down rate, cool-down Se flux, venting temperature, maximum Cu ratio during film 

growth and final Cu-ratio. Related to the production systems, the following topics were investigated: process 

robustness and device performance as a function of maximum and final Cu ratio and real-time sensing of maximum 

Cu ration. 

In order to minimize losses due to reduced absorber thickness, GSE worked closely with the substrate 

vendor to improve the surface finish of the metal foil. Reductions in surface roughness minimized shunting and 

impurity outdiffusion via spikes not covered with the back contact layer. At the same time, different back contact 

layer thicknesses as well as alternate diffusion barrier materials were investigated as to their effectiveness against Fe 

outdiffusion. 

As for the amount of Na present in the film. Stainless steel, as opposed to soda lime glass, does not provide 

intrinsic Na doping and Na needs to be added during film growth. GSE choose to accomplish this via in-situ 

evaporation of a thin Na precursor preceding the 1st stage of the absorber formation. However, the amount of Na 

added impacts CIGS to Mo adhesion. The interactions of Na, Mo and Se with In and Ga are complex and it is 

critical that the degree of Mo selenization is optimal for both good adhesion and ohmic contact. Using tape peel 

adhesion, different Na precursor thicknesses impacts on CIGS to Mo adhesion and device performance were 

investigated, while the more complex interactions of Na with Mo, In, Ga and Se as a function of substrate 

temperature are still under investigation. 

Feedstock costs, most prominently those for In, are of concern with respect to reduced manufacturing costs. 

To a varying degree, the total feedstock cost for any given element (Cu, In, Ga, Se) is a function of the material as 

well as processing, including purification. The less pure, the more economical the feedstock becomes. However, 

solid-state CIGS-based devices are sensitive to certain impurities. Hence, if electrically active impurities are added 

via feedstock contamination, device efficiency would degrade offsetting the cost benefits associated with less pure 

feedstock. To this end, GSE procured the metals at three different purity levels and investigated the impact on 

device performance at the R&D level. It was found that GSE utilizes metal feedstock in the optimum range. 

In addition to aspects of the CIGS deposition, challenges exist in the post-CIGS treatment steps. For 

example, while certain in-situ monitoring capabilities have been developed at GSE, a more detailed post-CIGS 

characterization is still desired and beneficial. However, this results in exposure of the CIGS to ambient for 

extended periods of time, leading to surface oxidation. Time resolved studies of ambient exposure as well as dry N2

storage controls prior to CdS buffer deposition revealed the effect magnitude of ambient exposure on device 

performance. The penalty suffered from prolonged exposure was found to be minimal. 

CdS absorbs photons that could otherwise be utilized for charged carrier generation within the absorber. 

Thinning the CdS layer to a level where blue light absorption is minimized was found to have far less of an impact 

than theoretically predicted. On the other hand, too thick a CdS layer was found to adversely impact short circuit 

current densities. The challenge, in particular on a rough substrate as opposed to the smooth surface of glass 

substrates, is that a thicker CdS buffer layer reduces shunting in the device. The latter aspect was circumvented via 

optimizing the CdS thickness in combination with the wider band gap intrinsic ZnO layer thickness. 

Improved device performance has been reported to be attainable via surface sulfurization. GSE executed 

several experimental matrices, but was unable to reproduce the beneficial effects reported in the literature. Although 

2
only minute amounts of Cd are contained in the device stack, significant reductions or even replacement may be 

possible via a partial electrolyte treatment using Cd or Zn. Exploring a wide parameter space, GSE was once again 

unable to achieve the benefits reported in the literature. Hence, efforts were focused on optimizing the chemistry 

and kinetics of the CdS process. 

1.2 Technical Work Plan 

The research effort was structured to progress through three phases. The key elements of each phase were 

as follows: 

Phase One 

• Establish Three-Stage Bell-Jar Process. Establish the NREL-developed three-stage co-evaporation 

process in a bell jar at ITN; demonstrate satisfactory reproducibility and control on both glass and steel 

substrates. 

• Characterize Metals Flux. Characterization of the shape of the metal profiles from the production 

evaporation sources. Assess the magnitude of effects of Se background pressure and deposition rate 

variations on the shape of the metal plume from the sources. 

• Temperature and Time Process Tolerance. Utilizing the three-stage bell-jar process explore the 

effect of decreased processing time on CIGS film quality for multiple temperatures both on glass and 

steel substrates. 

Phase Two 

• Selenium and Temperature Profiles. Characterization of the shape of the Se distribution in the 

production evaporation sources. Characterize the flexible substrate temperature as a function of source 

temperature, heater temperatures, and web speed. 

• Process Tolerance for Deposition Species Fluxes and Temperatures. Using the three-stage bell-jar 

process examine the effect of momentary variations in Se/metals fluxes, division of In and Ga between 

first and third stages, Cu-rich excursion of stage two, and processing temperature variations. 

• Identification of Critical Roll-to-Roll Conditions. Identify areas where process improvements are 

possible, based on the sensitivities and characterization from previous tasks. Design deposition 

condition changes to increase yield and efficiency in the production roll-coaters. 

Phase Three 

• Process Tolerance for Impurities and Device Finishing. Via the three-stage bell-jar process 

examine the effect of chamber conditions during CIGS cool-down, the effect of impurities from source 

material and hot chamber surfaces, and the effect of handling procedures before CdS deposition. 

• Implementation of Process Improvements. Implement process improvements in the production rollcoaters based on the results from the previous tasks. Verify the predicted dependencies via depositions 

in the roll-coaters. 

All bell-jar related tasks were performed at ITN Energy Systems under supervision of Dr. Ingrid L. Repins. 

In order to optimize the amount of information in a given experiment under consideration of resources spend, GSE 

realizes the benefits inherent to the design of experiment approach in its studies. Prior to executing any given test, 

the list of variables and levels are considered and matched to the design deemed most appropriate. While typically 

several levels and variables are examined, it may be prudent to conduct screening experiments or even resort to onevariable at the time tests prior to launching a more complex design. Due to the number of inextricably linked 

variables more complex designs need to account for limitations such as response time (e.g., number of conditions 

obtainable on a 1000 ft. web) or equipment capabilities (e.g., maximum T setpoint) and it is not always possible to 

eliminate confounding effects. Replicas within the experiment as well as complete repetitions of an experiment 

further improve the quality of the statistical analysis. 

3
1.3 Technical Approach 

In the approach pioneered by GSE, continuous rolls of stainless steel foil substrate as long as 1000-1200 

feet are deposited with thin film PV layers, as opposed to individual small glass plates. Flexible, lightweight CIGSbased PV modules are fabricated by a novel interconnect method that avoids the use of wires or foils and soldered 

connections. Roll-to-roll vacuum deposition has significant advantages that translate directly into reduced capital 

costs, greater productivity, improved yield, greater reliability, lower maintenance, and a much larger throughput of 

PV material as compared to rigid plate processing. 

However, historically very little effort has been directed toward the deposition of CIGS onto alternate 

substrates, such as metal foils. Only recently has there been some interest in understanding the aspects and 

challenges of the latter on a fundamental level and in comparing the parameter space to that of the traditional 

formation of CIGS on glass substrates. As such, GSE could not draw on previously and independently established 

fundamental studies in this area. Although not part of this contract, GSE developed manufacturing capabilities 

enabling the RTR process for CIGS on polymer and metal foils in a pioneering role. Under the prior TFPPP 

subcontract – “Process Development of Large Area Thin Film CIGS”, ZAK-8-17619-04, 2/98 - 12/01 – GSE was 

able to establish the parameter space for successful CIGS deposition on stainless steel foil. However, lack of 

sufficiently well resolved process control precluded work addressing process sensitivities to variations in the 

numerous process variables. 

Concurrent with developing improved process control capabilities under the PVMaT subcontract – 

“Photovoltaic Manufacturing Cost and Throughput Improvements for Thin-Film Based CIGS Modules”, ZAX-8-

17647-11, 7/98 - 11/01 –, the approach under this TFPPP subcontract centered around first establishing fundamental 

process sensitivities of CIGS depositions onto stationary substrates. This included metal and Se flux profile 

characterization and the interactions of the species in the plume. Process conditions encountered during the 

accelerated RTR deposition rates (web speed up to 12 in/min) in GSE’s production scale equipment were mapped 

into the laboratory equipment. After establishing a bell-jar baseline process for deposition on glass, conditions were 

altered to reflect conditions representative of the stainless steel foil substrates in the RTR manufacturing equipment 

at GSE, including partial Se pressure, metal flux rates, time-temperature profiles, Cu-rich excursion, group III 

ratios, Na content etc. Process tolerances were explored and lessons learned were transferred to the production 

equipment. Final process optimization was then conducted at the manufacturing scale. 

Besides the focus on the absorber formation process, process tolerances were also explored for the back 

contact sputter deposition, CdS buffer formation, and sputter deposition of the i-ZnO/ITO window layer. 

2 Maximum Cu Ratio During CIGS Growth 

2.1 Bell Jar Studies 

Bell-jar-scale experiments conducted during Phase II found the maximum Cu ratio during CIGS growth to 

have a large effect on device performance. Similar studies in the roll-coaters to reproduce these observations were 

ambiguous. Thus, the bell jar experiments were extended to include both, a more precise reproduction of the Ga 

profile in the production devices, and an experimental matrix allowing determination of statistical uncertainties. 

Maximum Cu ratio was again found to have a significant effect on device performance. The new data, analysis, and 

implications for production are described below. 

Several studies have examined the impact of a Cu-rich growth period during three-stage CIGS coevaporation.2,3.7,8,9 Some of these studies have linked the Cu-rich growth period to larger grain growth and 

beneficial effects on device performance, while others have defined these benefits as limited to depositions at 

reduced temperatures or times. In general, conclusions in these studies are based on several pair-wise comparisons 

of depositions (e.g., comparisons of a sample with Cu-rich growth and another without for several deposition 

conditions) and have not included a statistical analysis of uncertainties. In this study, a designed8

 experiment 

utilizing 12 substrates and 144 devices was performed. For these films deposited on glass at 575°C over 

approximately 20 minutes, it was found that a Cu-rich growth period yields a statistically significant benefit for 

device performance through open-circuit voltage. By varying film thickness, the number of atoms deposited in 

stage 3 was also included as a variable in the experiment. The data indicated that device efficiency does not depend 

significantly on the number of moles deposited in stage 3. 

4
CIGS films were deposited by three-stage co-evaporation onto 3” × 3” Mo/glass substrates in the ITN bell 

jar. A thermopile was used to monitor film emissivity and thereby deduce Cu-ratio (i.e., the atomic ratio 

Cu/[In+Ga]) in real time. Electron impact emission spectroscopy rate monitoring was used to control the number of 

moles deposited in stage 3. Devices were finished utilizing standard bath CdS, sputtered resistive ZnO, and 

sputtered ITO. Ni/Al grids and mechanical scribes were applied to form 1.16 cm2

 devices. All quoted device 

parameters are based on AM1.5, total-area measurements. No anti-reflective coating was applied to the devices in 

this study. 

A summary of deposition conditions, CIGS properties, and device results for the samples in this study is 

given in Table 1. The samples form a three-level factorial experiment design with two factors (maximum Cu ratio, 

and moles in third stage) and several replicas. Final Ga ratio was controlled to 0.45 ± 0.05, while the final Cu ratio 

was controlled to 0.8 ± 0.7 and film thickness was kept between 2.1 and 3.4 μm. Some variations in thickness and 

final Cu ratio are necessary to achieve the desired combinations of maximum Cu ratio and third-stage atoms. The 

order of sample fabrication was randomized. In Table 1, maximum Cu ratio is abbreviated as “R2”. Each row of 

Table 1 represents one CIGS substrate on which 12 devices were measured. The table lists both average and bestdevice parameters for each substrate. Evaluating deposition conditions by either choice of parameter is essentially 

equivalent, as the average and best-device parameter values are highly correlated. 

Results of the factorial experiment were analyzed using Statistica® software.11 The most important outputs 

from this analysis include, for each parameter listed in columns 2 through 9 of Table 1, an estimate of the magnitude 

of the two factors on the parameter, and level of statistical significance for these effects. Both linear and quadratic 

relationships between the factors and device parameters were explored. The level of statistical significance (“plevel”) describes the probability for the particular relationship between the factors and device parameters, with lower 

p-levels indicating higher statistical significances. A p-level of 5% (0.05) is a typical threshold for concluding a 

relationship to be statistically significant at the 95% confidence level. 

Table 1: Sample and device characteristics. 

Sample Best 

device 

η (%) 

Best 

device 

Voc (V) 

Best device 

Jsc

(mA/cm2

) 

Best 

device ff 

(%) 

Avg η

(%) 

Avg 

Voc (V) 

Avg Jsc

(mA/cm2

)

Avg ff 

(%) 

Cu/ 

(In+Ga) 

Ga/ 

(In+Ga) 

thickness 

(μm) 

R2 Atoms 

(1015 /cm2

) 

Low atoms 

- Low R2 

8.7 0.533 24.7 0.66 7.9 0.543 23.3 0.62 0.73 0.39 2.1 0.85 354

Low atoms 

- Ctr R2 

8.5 0.619 21.2 0.64 7.9 0.613 20.4 0.63 0.76 0.49 2.2 1.05 365

Low atoms 

- Ctr R2 

10.3 0.591 26.9 0.65 8.1 0.580 22.9 0.61 0.8 0.44 2.2 1.04 367

Low atoms 

- Hi R2 

10.2 0.622 27.1 0.60 8.6 0.624 27.2 0.51 0.85 0.5 2.1 1.25 369

Ctr atoms - 

Low R2 

8.8 0.525 31.3 0.54 7.9 0.540 25.7 0.58 0.85 0.43 3 0.95 420

Ctr atoms - 

Ctr R2 

9.2 0.545 28.8 0.58 8.7 0.556 28.3 0.55 0.87 0.47 2.4 1.07 424

Ctr atoms - 

Ctr R2 

8.8 0.560 26.7 0.59 7.7 0.547 24.9 0.56 0.85 0.49 3.4 1.03 468

Ctr atoms - 

Hi R2 

10.3 0.598 27.3 0.63 9.5 0.603 25.3 0.62 0.87 0.48 2.4 1.11 466

Hi atoms - 

Low R2 

7.9 0.553 23.7 0.60 6.6 0.587 21.0 0.53 0.74 0.5 3.2 0.94 647

Hi atoms - 

Ctr R2 

9.7 0.566 26.1 0.66 8.6 0.527 27.1 0.60 0.83 0.45 2.1 1.05 591

Hi atoms - 

Ctr R2 

8.4 0.542 27.8 0.56 7.6 0.555 25.4 0.55 0.76 0.41 2.4 1.07 594

Hi atoms - 

Hi R2 

9.9 0.564 27.8 0.63 9.3 0.574 26.7 0.61 0.76 0.48 2.2 1.12 585

5
The statistically significant relationships are listed in Table 2. Effect magnitudes are defined as follows by 

the best fit surface for a parameter j to the data: 

F(j, low k) ≡ the value of the fit to parameter j at the low value of factor k 

Then for linear relationships, 

Effect of factor k on parameter j ≡ F(j, high k) – F (j, low k) 

and for quadratic relationships 

Effect of factor k on parameter j ≡ F(j, center k) – 1⁄2 [F (j, low k)+ F (j, high k)] 

Thus, a positive linear effect means the parameter increases with the factor, and a negative linear effect 

means the parameter increases as the factor decreases. Table 2 identifies a linear dependence of efficiency and Voc

on maximum Cu ratio. A smaller dependence of Voc to decrease linearly with third-stage atoms is also identified. 

However, this dependence does not translate significantly to efficiency. The best fit surfaces for these significant 

dependencies are shown in Figure 1. Some curvature is apparent in the surfaces, however these quadratic terms are 

not statistically significant and therefore are not listed in Table 2. 

Table 2: List of statistically significant relationships from this study’s data. 

Parameter Is a function of: Form Effect 

Magnitude 

p-level 

Average η Maximum Cu ratio Linear 2.11 0.036 

Best device η Maximum Cu ratio Linear 1.67 0.011 

Best device Voc Maximum Cu ratio Linear 0.058 0.009 

Best device Voc Stage 3 atoms Linear -0.035 0.042 

Comparing this study with others in the literature requires consideration of both statistics and film growth 

kinetics. Shafarman et al1

 conclude that the Cu-rich growth period is beneficial only for devices deposited at reduced 

temperatures. However, two-stage, rather than three-stage growth was utilized. The simultaneous deposition of 

group I and III atoms during the two-stage process may provide more time for the necessary reactions and lessen the 

benefit of the Cu-rich growth period, since the benefit of the Cu-rich growth period has been surmised to come from 

a fluxing of the CIGS grains by excess liquid Cu2Se.9

 Other conditions that affect film kinetics, such as the presence 

and amount of Na, are also expected to have an impact on the benefit of the Cu-rich growth period. It also should be 

noted that only six samples in the two-stage study (three at each of two temperatures) were used to draw 

conclusions. Nishiwaki et al3

 present one impressive efficiency (16.6%) formed by three-stage deposition without 

the Cu-rich growth period, but provide neither data from samples with Cu-rich growth nor data from replicas 

without Cu-rich growth. 

a) b) 

Figure 1: Best-fit surfaces for a) efficiency and b) Voc as a function of maximum Cu ratio and atoms in stage 3. 

6
2.2 Implications for Production 

As outlined above, for three-stage devices made in ITN’s bell jar, a Cu-rich growth period was found to 

yield a statistically significant benefit on device performance. Given the sensitivity of bell jar devices to maximum 

Cu ratio, tests of the impact of maximum Cu ratio were also performed in the GSE production roll-coaters. A twolevel screening test of maximum and final Cu ratio was executed. The 2 × 2 matrix was replicated one time for a 

total of eight test conditions. The planned levels for Cu-rich excursion were 1.0 and 1.1, as measured by in-situ 

XRF. The planned levels for final composition (Cu/(Ga+In)) were 0.81 and 0.91. The web was processed 

according to baseline manufacturing process conditions through production cell (i.e., large area devices, total area 78 

cm2

) fabrication and measurement. Three thirty-cell sample panels were extracted from each condition. Deletion of 

outliers well outside the normal distribution was performed prior to analysis. 

The mean efficiency of each condition are plotted on the interaction chart in Figure 2. For films processed 

without a Cu-rich excursion (in process Cu/(Ga+In) ~ 1.0), the final composition had a significant effect on final 

efficiency; a final Cu/(Ga+In) of 0.91 was superior to 0.81. All IV parameters (Voc, Jsc, and fill factor) improved. 

For films that experienced a Cu-rich excursion (in process Cu/(Ga+In) ~ 1.1), the efficiency was much less 

dependent on the final Cu/(Ga+In). The latter process was more robust, although the mean efficiency under the best 

conditions may be slightly lower than the case where the film did not go Cu-rich. 

Final Cu/(In+Ga)

0.80 0.82 0.84 0.86 0.88 0.90 0.92

Efficiency (%)

9.0

9.5

10.0

10.5

Maximum Cu ratio = 1

Maximum Cu ratio = 1.1

Figure 2: Interaction chart summarizing device efficiency from roll-coaters as a function of maximum and final Cu 

ratio. 

As somewhat different conclusions were reached from the bell jar and roll-coater experiments, further 

examination of conditions in the roll-coater were performed. In these follow-up experiments, deposition 

temperature and film thickness (as varied either by source temperature or deposition time) were included as factors. 

Interpretation is more complex than for the earlier experiments, as – even for a constant maximum Cu ratio – 

thickness and resultant Ga profile impact performance. Substrate temperature is also a factor. These results are 

summarized in Figure 3, showing efficiency as a function of the newly-introduced factors, for constant maximum 

Cu ratio. The legend lists the process conditions for each symbol. Analysis of the designed experiment and 

resulting error bars were generated using Statistica®11 software. 

Thus, despite the demonstrated benefit of a Cu-rich growth period for bell jar devices, designed 

experiments performed in production roll-coaters determined that the effect of maximum Cu ratio is convoluted with 

film thickness, temperature, and time. Future efforts are to be directed toward fully optimizing conditions and 

assigning the inter-dependencies to physical mechanisms such as the Ga profile. 

Figure 3: Results from experimental design varying deposition temperature and CIGS thickness (by source 

temperature or web thickness) in roll-coaters, at constant Cu ratio. 

9.5

10.0

CIGS Thickness (nm)

1200 1400 1600 1800 2000

Efficiency (%)

8.5

9.0

Experiment 1

Experiments 2 & 3

7
3 Film Growth 

3.1 Bell Jar Studies 

Process sensitivities related to film growth kinetics (e.g., as shown in the previous chapter for the extent of 

Cu-rich excursion) might be expected to exhibit significant inter-dependencies. Hence, traditional stationary bell-jar 

depositions cannot be compared to dynamic RTR production conditions unless the latter can be reproduced in a 

stationary system. As the associated costs and inherent sluggish response of large production systems to parameter 

changes inhibits fast and inexpensive exploration of the vast parameter space of multi-source co-evaporation of 

CIGS, a small scale, low-cost R&D approach is highly desirable. Once the main interactions and most significant 

process variables have been identified, process optimization can then proceed at the production scale in a more 

economical fashion. 

Depositions were conducted in order to develop a procedure to mimic the GSE roll coater time-temperature 

(t-T) and flux profiles in the ITN bell jar. Initial depositions employing very fast deposition rates onto steel 

substrates, which simulate the high throughput in the production roll-coaters, indicated a possible sensitivity of 

device results to temperature ramp rate, which can be much faster for thin steel substrates than the typically-used 

higher thermal mass glass. Subsequently 4 factor, 2 level (one complete replica) experiments were performed to 

mimic the GSE process in the ITN bell jar and to determine the effect of selective process variables – stage 1-2 

temperature ramp time, ramp end time of 2nd stage, stage 2 and 3 temperature (treated as 1 variable), and deposition 

rate – on device performance. 

Initial attempts to control the deposition on GSE provided substrate were unsuccessful, yielding wide 

fluctuations in composition. The main difficulty seemed to originate from an abnormal IR signal precluding 

endpoint detection after the 2nd stage. The samples in this set displayed emissivity increases that began at very low 

Cu ratio at the beginning of stage 2. Apparently some high-emissivity compound, other than the usual excess 

Cu2Se, formed in the film. Figure 4 compares a normal IR signal for stage 2 and 3 to the abnormal signal returned 

in the initial deposition series. 

Figure 4: Desired (left) and undesired (right) IR profile for a GSE mimic deposition at ITN.

This unexpected complication necessitated that we identify possible causes. We proceeded by compiling a 

trouble-shooting list and tackling each subsequent item one by one. While some minor corrections to sensors 

resulted, none of the other items yielded out-of spec parameters nor did the IR signal improve. Subsequently, the tT-flux profile was broken down into smaller segments with unchanged components based on the ITN baseline 

process. This approach restored the normal IR signal and yielded devices on SS in the 8.4 to 8.6% range with up to 

75% of the t-T-flux profile matched to the GSE condition. Subsequent attempts at increased rates and decreased 

times to match 87.5% of the GSE profile once again yielded the abnormal IR signal, while repeats at the 75% match 

level resulted in normal sensor signals. 

At this point it is not clear why IR signal endpoint detection fails to work if process times are reduced and 

fluxes increased to simulate GSE’s production process in a stationary, fixed source-substrate geometry bell-jar 

environment. In the interest of cost and time, all future process tolerance work was to be conducted on the actual 

production equipment. 

3.2 Production Ga/(Ga+In) Profile 

Although considerable progress had been made in achieving reproducible production yields and mean cell 

efficiency in the roll coaters, further improvements were desired. All coating processes were under investigation to 

8
understand their effect on reproducibility, but the CIGS process received the most attention. The CIGS process has 

historically been the largest contributor to production output noise. Process drift during the course of a single CIGS 

run and XRF calibration error lead to measurable inter- and intra-lot composition variation. Tests were conducted to 

understand the tolerance of the CIGS process for composition variations and to identify hardware and process 

setpoint modifications to improve the output tolerance for these variations. 

The focus of the tests conducted was the Ga/(Ga+In) profile through the film thickness. In three-stage 

depositions conducted in bell jars, virtually all Ga/(Ga+In) profiles possible can be achieved through independent 

control of the Ga and In fluxes to the fixed substrate. In the production roll coaters, however, limitations in 

achievable profiles are imposed by the nature of the continuous roll coating process. Discrete effusion sources for 

each element at fixed locations are specifically responsible. 

Modifications were made to the standard effusion sources for the tests that provide better mixing of the 

elemental fluxes. The location of these modified effusion sources and their respective elemental fluxes were the test 

variables. Six tests were conducted on webs each 800 feet and containing 20 test conditions. The standard test 

condition was forty feet in length. Tests were designed using standard matrices for 2 variables, 3 levels each (3 × 3) 

with single or double replicates. Within the entire test series approximately the same test parameters (besides 

location) were applied to each lot. Besides the CIGS test conditions, webs were processed under standard conditions 

in all remaining thin film coating steps. Three panels with 12 cells each (68.8 cm2

) were selected from each test 

condition for measurement. 

A summary of the six test lots is shown in Table 3. The mean maximum efficiency and best uniformity 

between test conditions (tolerance) was obtained for configurations B and E. Voc and Isc had excellent model fits 

within each lot. Fill factor was fit poorly, indicating that fill factor was not strongly affected by the test parameters. 

A comparison between Isc and Voc for each test lot confirmed the superiority of configurations B and repeat of C for 

the Isc × Voc product (Figure 5). While configuration B appears to offer the best compromise, all of the non-standard 

four configurations explored are capable of achieving maximum efficiencies in the 9.6 to 10.2% range. Tests to 

further down-select between the more process tolerant configurations B and E as opposed to the condition C, 

resulting in the highest efficiencies, are planed for the future. 

Table 3: Cell performance summary for test lots. 

Lot Config. Maximum η (%) Voc at Max. η (mV) Isc at Max. η (mA) FF at Max. η (%) Average η (all Tests) 

1786SA A 9.15 531 2090 56.7 8.48 

1793SA B 9.78 559 2167 55.5 9.53 

1807SA C 8.73 540 2058 54.0 7.65 

1826SA D 9.61 574 1997 57.7 9.09 

1839SA E 9.85 556 2177 56.0 9.49 

1841SA C 10.20 544 2223 58.0 9.57 

9
Voc

Isc

Lot: 1786SA

Lot: 1793SA

Lot: 1807SA

Lot: 1826SA

Lot: 1841SA

Lot: 1839SA 480 500 520 540 560 580 600 620 1800

1900

2000

2100

2200

2300

2400

Lot: 1786SA Isc = 3887.669-3.4532*x

Lot: 1793SA Isc = 4082.4718-3.5111*x

Lot: 1807SA Isc = 4191.7557-4.0895*x

Lot: 1826SA Isc = 3674.7672-3.014*x

Lot: 1841SA Isc = 3843.1446-3.195*x

Lot: 1839SA Isc = 4092.0705-3.5766*x

Figure 5: Isc,/Voc characteristics of In/Ga flux test lots. 

3.3 Production Tsub and Na Precursor Sensitivity 

Improvements in efficiency and yield due to enhanced adhesion of the absorber to the back contact were 

targeted via a 4 factor, 2 level experiment including center points. Evaluation of the parameter space was conducted 

in two independent depositions spread over two CIGS roll coaters. The experimental portion of each deposition was 

800 ft. containing 18 conditions. Following device completion 5 panels yielding 12 cells each were removed from 

each of the 18 conditions. Statistical analysis under removal of outliers showed the strongest impact to be the 

substrate temperature during Na precursor deposition. As illustrated in Figures 6 and 7 a significant improvement in 

CIGS adhesion as well as efficiency as a function of Na precursor deposition conditions is evident. Furthermore, 

optimization of the Na precursor deposition step resulted in a more robust process. 

Figure 6: Fitted surface of CIGS to back contact adhesion as a function of Tsub during precursor deposition and 

rate.

10
Figure 7: Pmax as a function of Tsub during Na precursor deposition and rate. 

3.4 Production Se Delivery Rate Sensitivity 

In addition to the already explored process sensitivities, statistical analysis of all thin film coating (TFC) 

processes traced inter-lot variations to the specific CIGS coaters. In section 3.2 efforts investigating the tolerance of 

the CIGS process to composition variation of the group III elements throughout the absorber layer have been 

discussed. With two of the four CIGS coaters configured to the best set resulting from this test series, screening 

experiments were conducted to identify the key – not directly composition driven – parameters responsible for the 

coater-based deviation. Experiments confirm that the process is well centered in the optimal parameter space for the 

variables tested. As an example, Figure 8 demonstrates the response to a change in Se delivery rate with the 

medium level corresponding to the current baseline process. Due to the nature of screening experiments, the width 

of the plateau cannot be obtained, while the design chosen still allowed for confirmation of curvature and 

computation of effect estimates. 

Figure 8: Average production cell power as a function of Se rate delivery.

11
4 Post-Deposition Treatments 

Post-deposition treatments of production CIGS have been examined for a boost to efficiency and process 

robustness in two forms: surface sulfurization via thioacetamide and, post-deposition Na treatments following 

recent work by Rudmann et al.12

Over the past several years, two CIGS groups have reported relative device efficiency increases of as much 

as 20% due to an additional chemical treatment involving solutions containing thioacetamide.13,14 The efficiency 

improvement has been attributed to the formation of a thin sulfide layer and/or surface passivation by sulfur atoms. 

Thioacetamide treatments were evaluated on GSE production material by designed experiment. Treatment time, 

temperature, and concentrations were varied. Although optimum conditions were found to be consistent with those 

in the literature, no statistically significant performance benefit was realized compared to untreated samples. Figure 

9 shows a box and whisker plot of the efficiency for thioacetamide treated samples (0) and untreated devices (1). 

Although not statistically significant, the mean efficiency of the untreated specimens is slightly higher than for the 

treated samples. Furthermore, a narrower distribution for the untreated samples is evident from the standard 

deviation (SD), indicating poor reproducibility of the thioacetamide process. Due to the larger number of treated 

devices the standard error (SE) is narrower as compared to the untreated absorbers. Representative IV plots further 

illustrate that no significant difference can be observed between the two device groups (Figure 10: ). It was 

concluded that the benefit of the thioacetamide treatment is dependent either on some property of the CIGS surface 

not present in the GSE material, or on a procedural detail not reproduced in our experiments. 

Figure 9: Box and whisker plot of efficiency for thioacetamide treated samples and control devices. 

-30

-20

-10

0

10

20

30

-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8

V [V]

J [mA/cm2

Treated ]

Untreated

Figure 10: Representative current-voltage trace for a treated and an untreated device. 

Passivation of CIGS on flexible substrates by treatment with NaF has also been reported.12 Post absorber 

formation Na treatment was applied to production-line CIGS at GSE for absorbers prepared on steel under various 

deposition conditions. The two types of material were subsequently sent to ITN for post-absorber treatment. 

Herein, a portion of each coupon set was treated with a Na compound and finished into devices, while another 

portion was finished into devices without post-absorber Na treatment. Treatment time and temperature were 

12
examined as variables in the designed experiment. Optimum conditions were found to be consistent with those in 

the literature. Results for coupons 15 and 55, treated under the conditions reported by Rudmann, are shown by the 

blue bars in Figure 11. For both coupons sets – particularly for the lower efficiency material – the post-deposition 

Na passivation increases efficiency. GSE is investigating concepts to better implement and test passivation via Na 

on the production scale level. 

coupon 15 coupon 55

Device Efficiency (%)

0

2

4

6

8

10

12

14

Untreated

Treated

Figure 11: CIGS device efficiencies with and without exposure to post-deposition treatment. 

5 Feedstock Purity 

High-efficiency CIGS devices made in R&D laboratories are based on absorber depositions employing the 

highest purity source materials available. The option to utilize lower purity feedstock would benefit industry in 

terms of lower materials cost and better availability. However, as the impact of increasing impurity content in the 

source materials on device performance has not been explored, experiments to this effect are necessary to exclude 

potential shortfalls in device quality – e.g., due to the introduction of electronic defects. The ultimate goal was to 

find the most economic compromise between materials cost (purity) and resulting device performance. 

Prior to the actual experimentation, a survey was conducted to obtain information on (a) the source purity 

of Cu, In, Ga, and Se employed at NREL, ITN, and GSE; (b) the commercially available lower and upper end 

purities for these 4 elements; and (c) the respective unit costs per element for these categories. Based on up to 4 

vendors per element, Table 4 summarizes average expenses or savings when moving to higher or lower feedstock 

purities by one ninth. For example, almost no savings result in switching to lower purity Se, compared to significant 

cost impacts for higher or lower purity Cu and In. Thus, investigating the effect of changing Cu and In purity was 

assigned a higher priority than changes in Se purity. 

Table 4: Expenses or savings expected from increasing or decreasing source purity by one ninth. 

Element Increase by one 9: Savings [$/g] Decrease by one 9: Savings [$/g] 

Cu -1.05 1.35 

In -1.04 0.60 

Ga -0.53 Not available 

Se Not available 0.03 

Subsequent to the above, a single-factor (metals purity), three-level experiment was designed; the 

characteristics of each level are summarized in Table 5. A few aspects of Table 5 merit further explanation. 

- Se was excluded from the experiment, as ITN, GSE, and NREL utilize the same purity feedstock and 

higher purity Se is not readily available, while lower purity Se offers negligible cost savings. 

- The “low” level of Ga purity is the same as the “medium” level, as lower purity Ga was not available 

from any of the vendors surveyed. 

- The “high” levels of purity for Cu and Ga exceed the “medium” level by 2, rather than 1, ninth. The 

goal of the study was to screen for maximum effects, hence the widest possible purity range was 

explored starting from the most pure material down. 

13
Table 5: Metals purity levels. 

Level Cu purity 

(#9’s) 

In purity 

(#9’s) 

Ga purity 

(#9’s) 

Se purity 

(#9’s) 

Low 3 4 4 N/A 

Medium 4 5 4 N/A 

High 6 6 6 N/A 

In order to exclude substrate or process based convoluting factors, depositions were on Mo-coated glass 

substrates with three-stage CIGS deposited over approximately 20 minutes, using film emissivity endpoint detection 

for stages 2 and 3. The atomic Ga/(Ga+In) ratio was kept constant ± 2.5%. Each condition included one replica and 

the resulting device parameters are summarized in Table 6. Statistical analysis of the complete device data set, as 

well as QE analysis, revealed the majority of the efficiency loss in the lower purity samples to be due to a shortfall 

in Jsc (mostly in the red portion of the spectrum) while Voc and FF seem unaffected by source purity (Figure 12). 

Significant differences were only obtained for the low purity device set, while no statistically significant gain was 

evident when switching from medium quality metals to the highest purity level. 

Table 6: Best device parameters. 

purity Best device η

[%] 

Best device Voc

[mV] 

Best device Jsc

[mA/cm2

] 

Best device FF 

[%] 

Low 7.12 513 22.76 61 

Low 8.83 570 23.35 66 

Medium 11.18 612 26.31 70 

Medium 10.78 582 28.62 67 

High 10.82 534 32.83 64 

High 10.00 572 28.71 63 

Figure 12: Box and Whisker plots of efficiency (left) and Jsc (right) versus source purity.

Building on past efforts to realize further improvements in production yield and increased device 

efficienc

hile the CIGS process has historically been found to be the most significant contributor to production 

output n

Box & Whisker Plot: Best Device n

 Mean 

 Mean±SD 

 Mean±1.96*SD 123

Purity Number

5

6

7

8

9

10

11

12

Best Device n

Box & Whisker Plot: Jsc w/o Ga dep.

 Mean 

 Mean±SD 

 Mean±1.96*SD 123

Purity Number

20

22

24

26

28

30

32

34

36

38

Jsc w/o Ga dep.

6 Further Production Sensitivities 

y, all thin film coating (TFC) steps were further scrutinized. Statistical evaluation of production data as a 

function of process and TFC system combination revealed minor variations despite nominally identical hardware 

and setpoint values per TFC process. 

W

oise, the above analysis warranted a closer look at the first process step, the back contact deposition. Via 

the design of experiment (DOE) approach sensitivities have been confirmed and traced to physical properties of the 

14
back contact. Further work lead to a practical solution to address the process variability, subsequently narrowing the 

device efficiency distribution and increasing yield (Figure 13) due to improved intra-run uniformity. 

Further back contact related work was directed at improving CIGS to back contact adhesion beyond the 

optimization obtained via modifications to the CIGS depositon process – in particular the Na precursor deposition 

step as discussed under section 3.3. In addition, device improvements due to enhanced diffusion barrier properties 

of alternate back contact schemes were targeted. Various back-contact film structures were evaluated in 

combination with process parameter changes for the more promissing material layer sequences and compared to the 

optimized standard back contact. 

SIMS depth profilies were generated on the standard back contact as well as an altrernate layer sequence at 

two different thicknesses. Figure 14 illustrates that Fe diffusion from the SS into the CIGS is effectively prevented 

by all three back contacts. On the other hand, as the bright green line (Cr 400) in Figure 14 demonstrates, Cr 

diffuses into the CIGS for the standard back contact structure. Employing the alternate back contact under 

investigatrion Cr diffusion into the CIGS can be effectively blocked. In addition, marginal improvements in CIGS 

to back contact adhesion over the standard layer could be achieved with this new structure. Unfortunately, the 

resulting devices showed a significantly reduced performance. 

In subsequent tests the Cr diffusion supressing layer position in the stack was altered. Two new layer 

sequences were investigated and the resulting device performance compared to the standard back contact. Analysis 

of the impact of each back contact film stack on cell efficiency is summarized in Figure 15 – #1 denotes the standard 

GSE back contact. The only statistically significant difference was a slight decrease for the alternate constructions. 

The difference, however, is small (only ≈ about 0.6%) and may be partially attributable to any number of unrelated 

factors encountered during cell fabrication. Alternatively, the thickness of the diffusion barrier layer may not be 

optimized, nor may the actual layer sequence. 

Figure 13: Distribution and average efficiency before and after Mo process optimization.

15
1.00E+00

1.00E+01

1.00E+02

1.00E+03

1.00E+04

0 500 1000 1500 2000 2500 3000 3500 4000

sputter time

counts

Cr 277 Fe 277 Cu 277 Mo 277

Cr 339 Fe 339 Cu 339 Mo 339

Cr 400 Fe 400 Cu 400 Mo 400

Figure 14: SIMS depth profile through standard back contact (400), and an alternate back contact sequence of two 

different thicknesses (277 and 339).

Figure 15: CIGS device efficiency as function of back contact type – #1 denotes the standard GSE back contact.

7 Technical Summary 

Work during Phase III progressed in several key areas, primarily focused on the production scale processes: 

- process sensitivities to the degree of Cu-rich excursion, 

- Ga/(In+Ga) distribution throughout the absorber, 

- Na precursor deposition step, 

16
- Se delivery, 

- Back contact optimization, 

- Feedstock purity impacts, and 

- Surface passivation. 

The following conclusions were drawn related to production: 

- A maximum Cu ratio of 1.1 is more robust than a maximum Cu ratio of 1.0. 

- Various Ga/(In+Ga) distributions throughout the absorber yield maximum efficiencies, but a robust 

process can be achieved for a narrow group III distribution only. 

- Na precursor deposition conditions are instrumental to absorber adhesion as well as device performance. 

- Insufficient as well as excessive Se delivery negatively impacts device performance. 

- Cr diffusion into the absorber can effectively be blocked while simultaneously enhancing CIGS 

adhesion. 

- No gains in efficiency can be expected from increased feedstock purity while reduced feedstock purity 

would result in significant losses. 

- For the present GSE absorber surface sulfurization is not a viable option to replace CdS. 

- Stationary bell jar experiments cannot adequately simulate the dynamics in RTR film growth. 

8 Team Activities 

GSE participated in National CIS R&D Team activities. Recent contributions have included participation 

in and presentations at team meetings, submission of samples for comparative absorber studies, and review and 

discussion of related data. 

9 Phase III Publications, Presentations, and Reports 

The following publications, presentations, and reports were generated related to this contract during Phase 

III. They are listed in chronological order: 

1. Phase III, First Quarterly Report, August 19, (2004). 

2. M.E. Beck, I.L. Repins, J.S. Britt, “Sensitivities in Roll-to-Roll Processing of CIGS-Based 

Photovoltaics on Flexible Metal Foils”, DOE Solar Program Review Meeting, October 25-28, (2004). 

3. W.K. Batchelor, I.L. Repins, J. Schaefer, and M.E. Beck, “Impact of substrate roughness on CuInxGa1-

xSe2 device properties”, Solar Energy Mater. Sol. Cells, 83 (2004) 67-80. 

4. Phase III, Second Quarterly Report, November, 15, (2004). 

5. M.E. Beck, S. Wiedeman, R. Huntington, J. VanAlsburg, E. Kanto, R. Butcher, and J.S. Britt, 

“Advancements in Flexible CIGS Module Manufacturing”, 31st IEEE PVSEC, (2005). 

6. I.L. Repins, D.C. Fisher, M.E. Beck, and J.S. Britt, “Effect of Maximum Cu Ratio During Three-Stage 

CIGS Growth Documented by Design of Experiment”, 31st IEEE PVSEC, (2005). 

7. D.C. Fisher, I.L. Repins, J. Schaefer, M.E. Beck, W.K. Batchelor, M. Young, and S. Asher, “The

Effect of Mo Morphology on the Performance of Cu(In,Ga)Se2 Thin Films”, 31st IEEE PVSEC, (2005). 

8. W.K. Batchelor, M.E. Beck, and I.L. Repins, “Variations of Thioacetamide Treatments on CIGS Solar 

Cells on Stainless Steel Substrates – Correlations to Device Performance”, 31st IEEE PVSEC, (2005). 

9. Phase III, Third Quarterly Report, February 28, (2005). 

17
10. I.L. Repins, D. Fisher, W.K. Batchelor, L. Woods, and M.E. Beck, “A Non-Contact Low-Cost Sensor 

for Improved Repeatability in Co-Evaporated CIGS”, Prog. Photovolt. Res. Appl., 13 (2005) 311-323. 

11. Phase III, Fourth Quarterly Report, May 23, (2005). 

10 References 

 

1

 W.N. Shafarman, R.W. Birkmire, S. Marsillac, M. Marudachalam, N. Orbey, T.W.F Russell, “Effect of 

Reduced Deposition Temperature, Time, and Thickness, on Cu(In,Ga)Se2 Films and Devices”, Conference Record 

of the 26th IEEE Photovoltaic Specialists Conference, pp.331-334, (1997). 

2

 W.N. Shafarman, J. Zhu, “Effect of Substrate Temperature and Deposition Profile on Evaporated 

Cu(In,Ga)Se2 films and devices”, Thin Solid Films 361-362, pp. 473-477, (2000). 

3

 S. Nishiwaki, T. Satoh, S. Hayashi, Y. Hashimoto, T. Negami, T. Wada, “Preparation of Cu(In,Ga)Se2

thin films from In-Ga-Se Precursors for high-efficiency solar cells”, Journal of Materials Research 14 (12), pp. 

4514-4520, (1999). 

4

 J.R. Tuttle, T.A. Berens, J. Keane, K.R. Ramanathan, J. Granata, R.N. Bhattacharya, H. Wiesner, M.A. 

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Cu(In,Ge)Se2 – Based Solar Cells”, Conference Record of the 25th IEEE Photovoltaic Specialists Conference, 

pp.797-800, (1996). 

5

 J.E. Granata, “The Impact of Deliberate Sodium Incorporation on CuInSe2-Based Solar Cells”, 

Unpublished Ph.D. Thesis, Colorado State University, (1999). 

6

 M. Bodegard, J. Kessler, O. Lundberg, J. Scholdstrom, L Stolt, “Growth of Co-Evaporated Cu(In,Ga)Se2

– The Influence of Rate Profiles on Film Morphology,” Materials Research Society Symposium Proceedings, 668, 

(2001), pp. H2.2.1-H2.2.12. 

7

 A.M. Gabor, J.R. Tuttle, D.S. Albin, M.A. Contreras, R. Noufi, A.M. Herman, “High-efficiency 

CuInxGa1-xSe2 solar cells made from (Inx,Ga1-x)2Se3 precursor films”, Applied Physics Letters, 65(2), pp. 198-200, 

(1994). 

8

 D. S. Albin, G.D. Mooney, A. Duda, J. Tuttle, R. Matson, R. Noufi, Solar Cells 30, 47, (1991). 

9

 B. M. Keyes, P. Dippo, W. Metzger, J. AbuShama, R. Noufi, “Cu(In,Ga)Se2 Thin Film Evolution During 

Growth – A Photoluminescence Study”, Conference Record of the Twenty-Ninth IEEE Photovoltaics Specialists 

Conference, (2002). 

10 See, for example, G.E.P. Box, W.G. Hunter, J.S. Hunter, Statistics for Experimenters, John Wiley & 

Sons, (1978), pp. 289 ff. 

11 http://www.statsoft.com/textbook/stathome.html

12 D. Rudmann, D. Bremaud, H. Zogg, A.N. Tiwari, “Na Incorporation for Low Temperature Cu(In,Ga)Se2

Growth,” Proceedings of the 19th European PVSEC, (2004). 

13 T. Nakada, K. Matsumoto and M. Okumura. “Improved Efficiency of Cu(In,Ga)Se2 Thin Film Solar 

Cells by Surface Sulfurization Using Wet Process”, Proc. of the 28th IEEE PVSC, (2002), p. 527. 

14 T. Wada, Y. Hashimoto, S. Nishiwaki, T. Satoh, S. Hayashi, T. Negami and H. Miyake. “Highefficiency CIGS Solar Cells with Modified CIGS Surface”, Solar Energy Materials and Solar Cells, 67 (2001) p. 

305. 

18
F1146-E(05/2004) 

REPORT DOCUMENTATION PAGE Form Approved 

OMB No. 0704-0188

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1. REPORT DATE (DD-MM-YYYY)

January 2006 

2. REPORT TYPE

Subcontract Report 

3. DATES COVERED (From - To)

May 2003 – September 2005 

5a. CONTRACT NUMBER

DE-AC36-99-GO10337 

5b. GRANT NUMBER

4. TITLE AND SUBTITLE

Tolerance of Three-Stage CIGS Deposition to Variations Imposed 

by Roll-to-Roll Processing: Final Technical Report, May 2003 – 

September 2005 

5c. PROGRAM ELEMENT NUMBER

5d. PROJECT NUMBER

NREL/SR-520-39119 

5e. TASK NUMBER

PVB65105 

6. AUTHOR(S)

 M.E. Beck and J.S. Britt 

5f. WORK UNIT NUMBER

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

Global Solar Energy, Inc. 

5575 South Houghton Road 

 Tucson, Arizona 85747 

8. PERFORMING ORGANIZATION 

REPORT NUMBER

ZDJ-2-30630-14 

10. SPONSOR/MONITOR'S ACRONYM(S)

NREL 

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

National Renewable Energy Laboratory 

1617 Cole Blvd. 

Golden, CO 80401-3393 

11. SPONSORING/MONITORING 

AGENCY REPORT NUMBER

NREL/SR-520-39119 

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National Technical Information Service 

U.S. Department of Commerce 

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Springfield, VA 22161 

13. SUPPLEMENTARY NOTES

NREL Technical Monitor: H.S. Ullal 

14. ABSTRACT (Maximum 200 Words)

Three-stage co-evaporation of CIGS imposes stringent limits on the parameter space if high-efficient devices are to 

result. Substrate temperatures during the 1st stage (as well as during the 2nd and 3rd stage), Se partial pressure, and 

amount of Na supplied are critical for good nucleation, proper In-Ga-selenide precursor phase, and diffusion of Cu 

into the precursor, as well as diffusion of Ga through the film. In addition, the degree of Cu-rich excursion impacts 

maximum performance and process tolerance. Enveloping the above is the basic time-temperature profile 

inextricably linked to the metals delivery rates. Although high-efficiency, three-stage deposited CIGS devices on the 

R&D scale are grown at about 20-45 minutes to thicknesses of 2 to 2.5 μm, the latter is not a viable approach for an 

economic manufacturing process. At Global Solar Energy, Inc., CIGS films are typically grown in about 6 minutes to 

thicknesses of less than 2 μm. At the same time, the emissivity and thermal conductivity of stainless steel is vastly 

different from that of glass, and the reduced growth time poses restrictions on the substrate temperature ramp rates 

and diffusion of species (reaction kinetics). Material compatibility in the highly corrosive Se environment places 

limitations on the substrate heaters; i.e., substrate temperatures. Finally, one key advantage of a RTR deposition 

approach (compact equipment) restricts post CIGS Se exposure and cool-down rates to be vastly different than those 

practiced in the laboratory. 

15. SUBJECT TERMS

PV; three-stage co-evaporation; roll-to-roll (RTR) processing; CIGS; high-efficient devices; module; 

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