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Contract No. DE-AC36-08GO28308

Technical Report

NREL/TP-6A20-72103

November 2018

A Techno-Economic Analysis and Cost 

Reduction Roadmap for III-V Solar Cells

Kelsey A. W. Horowitz, Timothy Remo, Brittany Smith, 

and Aaron Ptak

National Renewable Energy Laboratory
NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

National Renewable Energy Laboratory

15013 Denver West Parkway

Golden, CO 80401

303-275-3000 • www.nrel.gov

Technical Report

NREL/TP-6A20-72103

November 2018

A Techno-Economic Analysis and Cost 

Reduction Roadmap for III-V Solar Cells

Kelsey A. W. Horowitz, Timothy Remo, Brittany Smith, 

and Aaron Ptak

National Renewable Energy Laboratory

Suggested Citation

Horowitz, Kelsey A. W., Timothy Remo, Brittany Smith, and Aaron Ptak. 2018.

Techno-Economic Analysis and Cost Reduction Roadmap for III-V Solar Cells. 

Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-72103.

https://www.nrel.gov/docs/fy19osti/72103.pdf.
NOTICE

This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable 

Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding 

provided by ARPA - Advanced Research Projects Agency-Energy (ARPA-E). The views expressed herein do not 

necessarily represent the views of the DOE or the U.S. Government.

This report is available at no cost from the National Renewable 

Energy Laboratory (NREL) at www.nrel.gov/publications.

U.S. Department of Energy (DOE) reports produced after 1991 

and a growing number of pre-1991 documents are available 

free via www.OSTI.gov.

Cover Photos by Dennis Schroeder: (clockwise, left to right) NREL 51934, NREL 45897, NREL 42160, NREL 45891, NREL 48097, 

NREL 46526.

NREL prints on paper that contains recycled content.
iii

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Acknowledgments

This work was authored by Alliance for Sustainable Energy, LLC, the manager and operator of 

the National Renewable Energy Laboratory for the U.S. Department of Energy (DOE) under 

Contract No. DE-AC36-08GO28308. The information, data, or work presented herein was 

funded in part by the Advanced Research Projects Agency – Energy (ARPA-E), U.S. 

Department of Energy. Additional funding provided by the U.S. Department of Energy Office 

of Energy Efficiency and Renewable Energy Solar Energy Technologies Office. The views 

expressed in the article do not necessarily represent the views of the DOE or the U.S. 

Government. The U.S. Government retains and the publisher, by accepting the article for 

publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, 

irrevocable, worldwide license to publish or reproduce the published form of this work, or allow 

others to do so, for U.S. Government purposes. We would also like to acknowledge Michael 

Woodhouse, whose prior work on III-V solar cell cost modeling we built upon; Alfred Hicks, 

who created the graphics used in this report; and Bill Hadley, Alex Wolf, and J.A. Colantonio 

for informative discussions on these topics.
iv

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List of Acronyms

c-Si crystalline silicon

CdTe cadmium telluride

D-HVPE dynamic hydride vapor phase epitaxy

DCF discounted cash flow

GaAs gallium arsenide

GaInAs gallium indium arsenide

GaInP gallium indium phosphide

GaN gallium nitride

HVPE hydride vapor phase epitaxy

kg kilogram

LM lattice-matched (LM)

LCOE levelized cost of energy

MOCVD metal-organic chemical vapor deposition

NREL National Renewable Energy Laboratory

PV photovoltaic

R&D research and development

SG&A sales, general, and administrative

Si silicon

TMG trimethylgallium

TMI trimethylindium

UAV unmanned aerial vehicle 

W Watts

WACC weighted-average cost of capital

WDC Watts direct current
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Executive Summary

III-V materials have achieved the highest efficiency of any solar cell technology. III-V solar cells

have been commercially available for decades and have been widely used in space applications 

where high performance is required. However, prices of III-V solar cells are currently two to 

three orders of magnitude higher than other technologies, prohibiting their use in mainstream 

photovoltaic (PV) markets outside high-concentration photovoltaic systems.

In this report, we present a bottom-up cost model for III-V solar cell technology and use it to 

model current III-V costs and present a roadmap for potential future cost reductions. These 

include only the costs of the solar cells themselves, and not the cost of any packaging, or 

interconnects and cover glass. We estimate current III-V manufacturing costs from $40/WDC to 

over $100/WDC, with minimum sustainable prices of $70/WDC to over $170/WDC, depending on 

the cell type, process assumptions, and production volume. These do not reflect the costs or 

pricing of any specific company but rather benchmark a range of near-term costs. We show that 

manufacturing yields and the current low production volumes are key drivers of these high costs. 

Additionally, we identify three key components of III-V cell costs:

• The wafer or substrate the III-V solar cell is deposited on (GaAs or Ge) 

• The epitaxial growth costs

• Other cell processing costs.

In addition to exploring the potential cost reductions that may result from increasing production 

volumes and yields, we examine advances that could be made in each of these three areas in an 

attempt to understand how low the costs of III-V solar cells might be able to go in the future, and 

whether these could be competitive in terrestrial solar markets. We find that cell manufacturing 

costs of $0.40/W or below could be achieved in high-volume production, but that this would 

require commercialization and scale-up of a low-cost epitaxial growth technique; implementation 

of alternative, low-cost metallization schemes; and, critically, significant research and 

development to address the high cost of the substrate while achieving high (>90–95%) 

cumulative production yields.
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Table of Contents

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

2 Methodology ......................................................................................................................................... 2

3 Cost Structure of Current III-V Solar Cells......................................................................................... 3

3.1 Triple Junction Solar Cells............................................................................................................ 3

3.2 Single and Dual Junction Solar Cells............................................................................................ 8

4 Pathways to Reduce III-V Solar Cell Costs ...................................................................................... 15

4.1 Production Volume and Yield Improvements............................................................................. 15

4.2 Decreased Epitaxial Growth Costs.............................................................................................. 16

4.3 Lowering Substrate Costs............................................................................................................ 20

4.4 Low-Cost Metallization............................................................................................................... 22

4.5 Putting it Together: A Roadmap to Low-Cost III-Vs.................................................................. 23

5 Discussion........................................................................................................................................... 24

References................................................................................................................................................. 25
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List of Figures

Figure 1. Schematic of the 3J device structure analyzed .............................................................................. 4

Figure 2. Step-by-step manufacturing cost breakdown for the 3J LM III-V solar cell shown in Figure 1... 6

Figure 3. Sensitivity of direct manufacturing costs for the 3J LM III-V solar cell to changes in key input 

parameters................................................................................................................................ 7

Figure 4. Example of a possible total cell cost breakdown by category and MSP for the 3J LM III-V solar 

cell shown in Figure 1.............................................................................................................. 8

Figure 5. Diagram showing (left) single and (right) 2J III-V solar cell designs used in our cost model...... 9

Figure 6. Illustration of the ELO process.................................................................................................... 10

Figure 7. Step-by-step cost breakdown for (top) single junction GaAs solar cells at 28% efficiency and 

(bottom) 2J GaInP/GaAs solar cells at 30% fabricated via MOCVD in the base case .......... 12

Figure 8. Comparison of cell cost breakdown for single- and dual-junction III-V solar cells grown via 

MOCVD................................................................................................................................. 13

Figure 9. Sensitivity of 2J GaInP/GaAs cell costs to key input parameters................................................ 14

Figure 10. 2J GaInP/GaAs cell manufacturing costs as a function of the number of substrate reuses at 

different CMP costs ............................................................................................................... 15

Figure 11. Estimated impact of increased production volume on 2J GaInP/GaAs solar cell costs fabricated 

with MOCVD......................................................................................................................... 16

Figure 12. Impact of increased throughput and material utilization on 2J GaInP/GaAs epi-layer costs with 

MOCVD and D-HVPE .......................................................................................................... 18

Figure 13. Concept drawing of a high-volume, in-line reactor for depositing III-V solar cells ................. 18

Figure 14. Sensitivity of epi-layer costs for a 2J GaInP/GaAs solar cell grown by D-HVPE to Ga and In 

material utilization rate .......................................................................................................... 19

Figure 15. Sensitivity of epi-layer costs for a 2J GaInP/GaAs cell grown via D-HVPE to key 

input parameters..................................................................................................................... 19

Figure 16. Sensitivity of epi-layer costs for a 2J GaInP/GaAs solar cell grown using D-HVPE to GaAs 

and GaInP deposition rates..................................................................................................... 20

Figure 17. Manufacturing cost for a 2J GaInP/GaAs solar cell deposited using D-HVPE as a function of 

number of substrate reuses and polishing cost per reuse ....................................................... 21

Figure 18. A roadmap to lower III-V solar cell costs ................................................................................. 23

List of Tables

Table 1. Key Input Assumptions for the 3J III-V Solar Cell Cost Model..................................................... 4

Table 2. Key ELO and Substrate Assumptions for the Single and 2J Base Cases...................................... 10

Table 3. Assumed Parameters of the Electroplated Contacts ..................................................................... 22
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1 Introduction

The so-called “III-Vs” are a class of materials consisting of elements from group III (group 13) 

and group V (group 15) of the periodic table that have been used to create the world’s mostefficient solar photovoltaic (PV) cells.1 In addition to having excellent optical and electronic 

properties, including a direct bandgap and high electron mobility, III-Vs can also be grown in 

multi-junction structures that allow for the reduction of thermalization losses and a resulting 

increase in efficiency. These solar cells have been used in space applications for decades due to 

their superior radiation resistance and ability to perform well in harsh environments, including 

extreme temperatures, compared to crystalline silicon (c-Si) solar cells (Andreev 2011). III-V 

solar cells themselves are thin-films, typically just a few microns thick, and they can be removed 

from their substrate to create flexible, lightweight devices. This characteristic is also valuable in 

aerospace applications, where weight drives total system cost and the ability to incorporate cells 

onto non-planar surfaces can be valuable. Additionally, the low temperature coefficient and good 

low-light performance of III-V cells can result in higher energy yield (kWh/kW) than c-Si in 

different locations (Silverman et al. 2013).

Despite these advantages, very few III-V solar cells are in use terrestrially because of their high 

cost: current III-V solar module prices often exceed $150/W, which is roughly 400X the current 

prices for mainstream c-Si solar and cadmium telluride (CdTe) modules ($0.30–$0.50/W). Only 

applications that require the performance of III-V solar cells, including some unmanned aerial 

vehicle (UAV) and military applications, can tolerate these prices. These devices have been used 

in many high-concentration photovoltaic systems that concentrate incident sunlight onto a small 

area, such that much less solar cell material is required. However, concentrator photovoltaic 

installations have largely stopped in recent years (Wiesenfarth et al. 2017).

Some analysis is available on the cost of III-V solar cells and potential pathways to reduced 

costs. NREL published a slide deck containing some initial analysis of single and dual junction 

III-V solar cells cost structures and potential cost reductions in 2013 (Woodhouse and Goodrich 

2013). Bottom-up cost modeling and road-mapping for III-Vs on Si tandem devices was

published more recently (Essig et al. 2017). Estimated costs of III-V solar cells fabricated using 

hydride vapor phase epitaxy (HVPE) and epitaxial lift-off (ELO) with substrate reuse are

included in (Simon, Schulte and Horowitz et al. forthcoming), along with a comparison of 

installed PV system costs for this technology and c-Si. Separate work outlining the pathways and 

challenges for reducing III-V substrate costs via different lift-off and reuse approaches has also 

been published (Ward et al. 2016).

However, a comprehensive picture of the potential for III-V solar cells to achieve one-sun costs 

compatible with larger-scale terrestrial deployment in rooftop, ground-mounted, or productintegrated markets has not yet emerged. In this report, we use bottom-up models to estimate the 

current costs of III-V cells. We highlight key cost drivers and map a path to a cost of $0.50/WDC

or below, and we identify the research, development, manufacturing, and scaling challenges 

required to achieve these costs.

 

1 See “Photovoltaic Research,” NREL, https://www.nrel.gov/pv/
2

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This analysis is intended to inform research and development (R&D) directions, as well as to 

understand how III-V costs could evolve given potential cost reduction avenues that the authors 

are currently aware of. It is not intended as a projection of III-V costs, and how costs evolve over 

time will depend significantly on the investment in this area, pricing of input materials along the 

supply chain, and the outcomes of uncertain R&D and scaling efforts.

All cost analysis presented here includes only the costs of the solar cells themselves—and not the 

cost of any packaging, or interconnects and cover glass. The yield losses associated with these 

packaging steps are also not reflected in the cell costs presented here.

2 Methodology

This analysis utilizes NREL’s established bottom-up cost analysis approach, which has been 

previously published in (Woodhouse and Goodrich 2013; Horowitz and Woodhouse 2015; 

Goodrich, et al. 2013; Woodhouse, Goodrich and Margolis et al. 2013; Horowitz, Fu and 

Woodhouse 2016). The general methodology is:

1. Determine a model device structure and manufacturing process flow based on academic 

literature, patents, and expert input, including interviews with current solar cell 

manufacturers.

A. In this case, three device structures are explored: triple junction (3J) 

GaInP/GaInAs/Ge, dual junction (2J) GaInP/GaAs, and single junction GaAs 

solar cells. The designs are intended to be representative of those produced 

commercially by the industry, but do not reflect the exact designs of a specific 

manufacturer, and in practice some design variability exists between different 

manufacturers. 

B. Process flows are tailored to the production volume modeled and the intended 

markets. In some cases, this reflects current prevailing manufacturing practice (to 

the best of our knowledge), and in other cases, in particular when imagining what 

a process for III-V solar cells would look like for much higher production 

volumes than are observed today, this involves some informed speculation. This 

speculation is informed by current technology and comparable manufacturing 

processes in similar industries as well as interviews with industry members along 

the supply chain. Citations for specific assumptions for each case are described in 

Sections 3 and 4. 

2. Create total cost-of-ownership models for each step in the process flow, which include all 

materials, direct labor, electricity, equipment, manufacturing facility, and maintenance 

costs.

3. Collect input data for the cost-of-ownership models for each process step, including, for 

example, deposition rates and other elements of process or cycle time, consumables 

usage, material utilization rates, and pricing. These data are collected from material and 

equipment suppliers, as well as solar cell manufacturers and other experts. Fully 

burdened costs ($/hr) and electricity prices ($/kWh) are taken from Bureau of Labor 

Statistics (Bureau of Labor Statistics 2017) and the U.S. Energy Information 

Administration (EIA 2018) respectively, for each manufacturing location modeled.
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4. Sum the costs for all process steps to calculate the total manufacturing cost.

5. Input results from the manufacturing cost model into a pro forma discounted cash flow 

(DCF) model to calculate a minimum sustainable price (MSP) for the model device. MSP 

assumes all overhead costs (R&D, sales, general, and administrative (SG&A)) costs can 

be covered, and investors can be paid back at the weighted-average cost of capital 

(WACC). This DCF and the meaning of MSP have been described previously in 

(Horowitz and Woodhouse 2015; Powell et al. 2015). MSP, notably, does not represent 

the minimum possible price that can be observed in the market; it is not a market price 

The model device structures and process flows, as well as details of input data or assumptions for 

each cell type and scenario are described in detail in Sections 3 and 4. All costs are modeled, and 

do not represent actual costs or prices of any particular company.

3 Cost Structure of Current III-V Solar Cells

In this section, we benchmark current costs of III-V solar cells, including single-junction, 2J, and 

3J designs and discuss key cost drivers. All these solar cells are currently produced in low 

volumes, typically on the order of 100’s of kW/year to low MW/year, although there have been 

announcements to expand single and/or 2J III-V solar cell production to 40MW/year in China

(Osborne 2018). We assume a production volume of 3,800 6-inch wafers per month (45,600

wafers/year) for our base case models, equivalent to 200kW/year at 33% cell efficiency. We also 

make simplifying assumptions that capacity is fully utilized and that equipment and facilities are 

purchased new (i.e., are not yet depreciated).

3.1 Triple Junction Solar Cells

Multiple 3J solar cell designs exist in the market today. Most of these fall into the following

general categories: lattice-matched (LM) GaInP/GaInAs/Ge cells, lattice-matched

GaInP/Ga(In)As/GaInNAs dilute-nitride cells, inverted metamorphic solar cells, and upright 

metamorphic cells. For purposes of benchmarking in this report, we focus on a LM on Ge 

design, shown in Figure 1, with cell layers deposited via metal-organic chemical vapor 

deposition (MOCVD). We assume the metal contact layers are deposited using electron beam (ebeam) evaporation, with lithography used to define the front contacts. To the best of our 

knowledge, these represent the prevailing techniques used in industry today. In addition to the 

layers shown in Figure 1, we also assume an Al2O3/TiO2 anti-reflective coating (ARC) is 

deposited via sputtering. The composition and fabrication approach of ARC for these solar cells 

varies by company and application, but the difference in costs between different ARC options 

are very low compared to other costs and uncertainties in our model. For the 3J cell, our model 

includes a total of 20 full time equivalent (FTE) direct laborers at 200 kW/year and five full-time 

equivalent (FTE) direct laborers at 50 kW/year. Overhead and other non-direct labor are captured 

in research and development (R&D) and selling, general, and administrative (SG&A) costs 

discussed below. The labor rates ($/hour) assumed and other assumptions are summarized in

Table 1.
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Figure 1. Schematic of the 3J device structure analyzed

Table 1. Key Input Assumptions for the III-V Solar Cell Base Cost Model

Parameter Value Notes

MOCVD tool cost $2.8million/tool Includes installation and auxiliary costs

MOCVD batch size 8 6-inch wafers

MOCVD tool uptime 85%

Heat/cool + pump/vent time for 

MOCVD 30 min

GaAs deposition rate 15 μm/hour

InGaP deposition rate 4 μm/hour

Trimethylgallium (TMG) price $1/g

Prices can vary widely depending on 

the production location and company’s 

leverage and supply chain. Prices as 

low as $0.45/g for Chinese 

manufacturing (of LEDs and other 

devices) have been reported.

Trimethylindium (TMI) price $12/g

Prices can vary widely depending on 

the production location and company’s 

leverage and supply chain. 

TMG, TMI material utilization 

rate 30%

Average V/III ratio 22 Used to calculate AsH3 and PH3 usage

Arsine (AsH3) price $0.44/g

Phosphine (PH3) price $0.35/g

Gold (Au) price $43/g Assume recycling of Au that is utilized

Silver (Ag) price $0.55/g

Ge substrate price $130/6-inch 

substrate

Prices can vary depending on the 

production location and company’s 

leverage and supply chain, with prices 
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Parameter Value Notes

roughly between $120/substrate and 

$150/substrate 

Cell area 133 cm2 Cropped 6-inch (150mm) wafer

Cumulative yield loss 20%

For the 3J cell on Ge only. Higher yield 

loss is assumed for later analysis on liftoff cells and is specified in Table 2.

Equipment depreciation 5-year straight-line

Building depreciation 20-year straight-line

Labor rates

$14/hr for unskilled 

labor, $25/hr for 

skilled labor

Will vary by location; these are meant to 

represent a mid-cost location in the 

United States. 

Figure 2 shows the resulting step-by-step manufacturing cost breakdown for the 3J LM solar cell

for two different production volumes—50kW/year and 200kW/year production. Total direct 

manufacturing costs (including depreciation) are estimated to be $70/WDC at 33% cell efficiency

for 200kW/year production and $100/WDC for 50kW/year production. The significant difference 

in cost between these two volumes is due largely to the fact that fixed equipment and building 

costs are socialized over fewer watts produced; in other words, some of the tools are 

underutilized at 50kW/year, resulting in higher cost. There may also be some difference in 

material costs at these different scales; however, we did not have sufficient data to fully include 

this effect. Costs for each scenario will also depend on the level of automation employed. 

As can be seen from the figure, the largest single cost is the Ge substrate, followed by MOCVD 

of the epi-stack. MOCVD costs are dominated by the equipment depreciation cost and the 

material costs. The high equipment depreciation cost is due both to the high price of each 

MOCVD tool and the long cycle time resulting both from significant heating and cooling time 

(30 min) and slow deposition (38 minutes total growth time), that is only amortized over a 

modest batch size (eight 6-inch wafers). Both the trimethyl- precursors and the arsine and 

phosphine contribute significantly to the material cost, and material costs are driven both by low 

utilization (particularly for the arsine and phosphine) and high material price per gram. The 

lithography equipment costs are also high due to high costs per tool set ($1 million–$2.5million 

installed for all required equipment) and low throughputs arising from to the use of single wafer 

processing on multiple toolsets (leading to a need for multiple tools). However, as previously 

mentioned, our analysis assumes this equipment (and all equipment) is purchased new and has 

not yet been depreciated. In cases where companies purchased used equipment and/or who have 

partially or fully depreciated these assets, these costs will lower.
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Figure 2. Step-by-step manufacturing cost breakdown for the 3J LM III-V solar cell shown 

in Figure 1

33% cell efficiency, U.S. manufacturing for (top) 200kW/year production volumes and (bottom) 50kW/year 

production volumes

200kW/year 

production

50kW/year 

production
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The sensitivity of these manufacturing costs to ±20% changes in key input parameters is shown 

in Figure 3. As can be observed from the figure, the largest lever on cost is the Ge substrate 

price, followed by the manufacturing yield. Factors which affect the MOCVD process time, 

including deposition rates, base layer thicknesses, and the heating and cooling time, have a 

limited impact on costs at this production volume because at least one tool (and a minimum 

amount of staff and electricity to operate it) is required. If Au is not recycled (as assumed here), 

sensitivity to Au prices increases significantly. Similarly, if Ag is recycled (no Ag recycling is 

assumed in our base model), sensitivity to Ag prices decreases, although the decrease is less 

significant. Efficiency (not shown) also significantly influences manufacturing costs: decreasing 

efficiency to from 33% to 32% increases costs by $2.20/WDC, and increasing efficiency to 34% 

decreases costs by $2.07/WDC.

Figure 3. Sensitivity of direct manufacturing costs for the 3J LM III-V solar cell to changes in key 

input parameters

33% cell efficiency, U.S. manufacturing at 200 kW/year 

Looking beyond direct manufacturing costs, overhead costs such as research and development 

(R&D) and selling, general, and administrative (SG&A) costs could contribute significantly to 

overall costs, particularly given the low volume of production and lack of standardization among 

projects/customers for III-V solar cells. Because there are no publicly traded III-V solar cell 

companies, we do not have data on actual R&D and SG&A costs in this industry. However, for 

purposes of illustration, we look at an example of what total costs and MSP may be if R&D 

and SG&A costs are 10% and 20% of revenue, respectively (Figure 4). We assume these same 

percentages for both the 50kW/year and 200kW/year cases, but in practice this will vary 

by company. The MSP in this example would be just over $80/WDC at 200kW/year and 

approximately $145/WDC at 50kW/year. This assumes a 14.8% weighted-average cost of capital 

(WACC), consistent with what has been estimated for other PV manufacturing companies

(Powell et al. 2015) (again, no data on cost of capital for III-V solar cell companies are publicly 

available). A 20-year project life, 2% inflation rate, and a combined state and federal tax rate 

of 25.7%.
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Figure 4. Example of a possible total cell cost breakdown by category and MSP for the 3J LM III-V 

solar cell shown in Figure 1

33% cell efficiency, U.S. manufacturing at 200 kW/year

SG&A and R&D costs, as well as cost of capital (which influences MSP)

vary by company and are not publicly available.

3.2 Single and Dual Junction Solar Cells

In this section, we explore costs associated with single and dual junction (2J) III-V solar cells. 

Figure 5 shows the reference cell designs used in our cost analysis. While these cells share many 

process steps with the typical 3J LM III-V solar cells on Ge analyzed in Section 3.1, there are 

several differences. First, Alta Devices is currently employing epitaxial lift-off (ELO) and 

substrate reuse for their single and 2J solar cells to mitigate the high cost of the GaAs substrate. 

ELO and reuse is also in use by MicroLink Devices for their 3J IMM cells, and this approach has 

also been explored at an R&D scale by a several other companies and research organizations 

(Adams et al. 2013). However, most 3J or 4J III-V solar cells on the market today (and used 

largely in space applications) do not employ ELO and reuse; instead, the substrate is thinned via 

etching as required by the application.

In our base case, we assume five substrate reuses as has been demonstrated in peer-review 

literature (Adams et al. 2013). Data on cell quality with 10 reuses has also been presented at a 

previous workshop (Li and Chaparala 2013), and we also explore the sensitivity of cell costs to 

number of substrate reuses in this section. Here, we assume chemo-mechanical polishing (CMP) 

is required after each lift-off step to re-prepare the surface for growth. However, there has 

been some literature suggesting that CMP may not be required during each lift-off step if a 

combination of buffer and protective etch layers are utilized (Lee et al. 2012). Because of this, 

we evaluate the impact of reduced CMP requirements on substrate and total cell costs in Section 

4.3.
9

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Figure 5. Diagram showing (left) single and (right) 2J III-V solar cell designs used in our 

cost model

While we assume the same production volume as for the 3J cells in our base case (3,800 6-inch 

wafers/month, equal to 170kW/year at 28% efficiency and 182kW/year at 30% efficiency), we 

also consider potential cost reductions associated with scaling up production to 20MW/year 

plants, consistent with the capacity Hanergy plans to install in China to produce single and/or 2J 

solar cells (Osborne 2018). However, we have significant uncertainty in the cost of epitaxial liftoff and reclaim/re-polishing processes at those production volumes because of the proprietary 

and firm-specific nature of these processes and associated difficulty in obtaining data. We make 

assumptions about the process scalability and cost, detailed below, and the sensitivity to different

variables is also discussed in Section 4.3.

As with 3J cells, we assume the epitaxial layers are grown using MOCVD, the prevailing 

industry practice. For our base case, we assume the same growth rates for all layers as for the 

3J case, but we also explore a high growth rate case, where GaAs is deposited at 60 μm/hour. 

Single junction GaAs solar cells have been grown at these rates in the literature with minimal 

degradation in cell performance (Schmeider et al. 2017). The assumptions about labor intensity 

and level of automation are also the same as for the 3J cells.

We use a GaAs substrate price of $100/6-inch wafer, and we assume a CMP cost of $25/wafer. 

This CMP cost can vary by as much as 40%–50%, as there is significant variation in the quality 

of the reclaimed wafers. This leads to differences in the number and type of polishing steps 

required as well as the amount of material that needs to be removed to achieve a satisfactory 

surface for re-growth. For the ELO, we assume the same general process flow as in (Woodhouse 

and Goodrich 2013; Ward et al. 2016), which involves bonding the cell to a handle and then 

dissolving a lift-off layer using a wet process with a mechanism to apply stress to the substrate 

while etching as illustrated in Figure 6. We refer to the tool used to perform the first function as 

the bonding tool and that used to perform the second function as the ELO tool. As in (Ward et al. 
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2016), we use 10 hours for the etch step to dissolve the lift-off layer, and assume 80 cells per 

batch, which results in a requirement for one (fully utilized) ELO tool at this cycle time and our 

base production volume. Our assumptions about ELO and substrate costs are summarized in 

Table 2. As discussed above, these parameters contain significant uncertainty due to the lack of 

available data. In addition to uncertainty about the process parameters and tool costs (tools are 

currently customized and proprietary), companies may be lifting off smaller areas of cells 

(coupons, rather than full 6-inch wafers) that are later arrayed in packaging to create modules. 

This would affect etch times and influence overall throughput. Other assumptions for the single 

and 2J cost models (in the base case) are the same as those made for 3J solar cells (Table 1). We 

use the same financial assumptions (SG&A costs, R&D costs, cost of capital, and inflation rate) 

as for the 3J solar cells.

Figure 6. Illustration of the ELO process

The cell is bonded to a flexible carrier, and then stress is applied to peel the cell off of the parent epi-substrate (GaAs) 

while HF solution etches an aluminum arsenide (AlAs) lift-off layer.

Table 2. Key ELO and Substrate Assumptions for the Single and 2J Base Cases

Other input assumptions not specified here are the same as those in Table 1

(the assumptions used for the 3J solar cell).

Parameter Value Notes

GaAs substrate price $100/6-inch wafer

Prices can vary depending on the production 

location and company’s leverage and supply 

chain, with prices roughly between 

$90/substrate and $150/substrate.

CMP cost $25/polish May vary by up to 40%–50% 

Number of substrate reuses 5

More may be possible in practice today, but 

limited data are available; see discussion 

above.
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Parameter Value Notes

ELO tool installed price $400,000

ELO tool uptime 90%

ELO process yield 80%

ELO tool throughput 8 cells/hour 10 hours of etch time, batch size of 80 cells

Bonding tool installed price $350,000

Bonding throughput 20 cells per hour Includes time for coating with adhesive and 

baking 

Bonding tool uptime 90%

Yield loss

10% additional yield 

loss introduced by 

ELO and reuse

Cumulative yield loss is then 30%. There is very 

little data available on yields currently achieved 

with reuse, or how this varies with the number of 

reuses.

Figure 7 (next page) shows the step-by-step cost breakdown for the single junction GaAs solar 

cells and dual-junction GaInP/GaAs solar cells under these assumptions with a production 

volume of 3,800 cells/month (roughly 200kW/year). The total manufacturing cost for the singlejunction cell at 28% efficiency is calculated to be $41W, with an MSP of $69/W. For a dualjunction cell at 30% efficiency fabricated using the same process as the single-junction, we 

estimate a total manufacturing cost of $41/WDC and MSP of $69/WDC. While the epitaxial 

growth costs are higher for the dual-junction case, the increase in efficiency compared to the 

single-junction case drives reductions in the other cell costs resulting in a very similar cost per 

watt. Figure 8 compares the breakdown of costs for each of these cell types. At higher production 

volumes, equipment, material costs, direct labor, and overhead costs can be reduced

significantly. We will discuss the potential impact of increased production volumes on cell costs 

in detail in Section 4.

As can be seen from Figure 7, the CMP costs are similar to the total cost of the substrate in this 

case, because the substrate cost is amortized over five reuses. The substrate and costs associated 

with reuses—CMP and ELO—are the largest contributor to overall cell costs. The high 

depreciation and labor costs associated with the ELO process are partly due to the low 

production volume, resulting in partially utilized tools and higher labor requirement, and partly 

due to the long cycle times associated with etching away the release layer.

While the epitaxial growth is the next most expensive step, the sum of steps involved in 

metallization exceed the cost of epitaxy. In particular, the high equipment cost associated with 

lithography equipment (due to the use of multi-step, single wafer processes as described above)

is high and the cost of materials for the front contact fingers is high due to very low material 

utilization and the high per gram cost of the contact materials (the front contact includes gold in 

our reference design). Again, our analysis assumes the lithography equipment is purchased new 

and has not yet been depreciated. Some companies may also employ alternative, lower-cost 

metallization schemes for one sun applications (e.g., mobile PV and UAVs), but there is no 

publicly available information on these approaches or the extent to which they are utilized 

in practice.
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Figure 7. Step-by-step cost breakdown for (top) single junction GaAs solar cells at 28% efficiency 

and (bottom) 2J GaInP/GaAs solar cells at 30% fabricated via MOCVD in the base case

Assumes U.S. manufacturing at 3,800 cells/month (170kW/year - 182kW/year, depending on the efficiency);

the CMP bar is gray because we do not have a bottom-up CMP cost model, but rather total costs obtained via 

industry interviews.

2J GaInP/GaAs

(at 30% efficiency)

Single junction 

GaAs 

(at 28% efficiency)
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Figure 8. Comparison of cell cost breakdown for single- and dual-junction III-V solar cells grown 

via MOCVD

Assumes U.S. manufacturing; SG&A and R&D costs, as well as cost of capital (which influences MSP) vary by 

company and are not publicly available, so these are estimates.

Cell costs are also sensitive to a variety of factors that contain uncertain, either due real 

variability in processes and prices between companies and/or data limitations. Figure 9 shows 

how ± 20% changes in key input variables influence total cell manufacturing costs. As with the

3J cells, manufacturing yield and substrate costs are a primary cost drivers. Changes in MOCVD 

tool price are also significant, at the same throughput (note that the sensitivity of cell costs to 

MOCVD tool price is roughly the same as for the 3J III-V cell in Figure 3, but the scale on the xaxis is different). The cost of CMP used to re-prepare the surface after lift-off, is another major

cost driver.
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Figure 9. Sensitivity of 2J GaInP/GaAs cell costs to key input parameters

Assumes 30% cell efficiency and U.S. manufacturing and approximately 200kW/year production volume

The impact of increased deposition rates is limited by several factors. First, the non-linear 

influence on overall cycle time, which is split between growth and heating, cooling, pumping, 

venting, loading, and unloading time (30 minutes total in our model), and GaAs deposition rate 

only influences a portion of the epitaxial growth time (assuming constant GaInP deposition rates, 

which are approximately three times lower than GaAs in our reference case). Second, at these 

production volumes, only one MOCVD tool is required. Increasing the deposition rate, therefore, 

does drive some per Watt reductions in labor and electricity usage, but does not significant affect 

depreciation costs, which are much more significant. Third, epitaxial growth costs only 

constitute a fraction of total cell manufacturing costs in this scenario. However, in certain future 

scenarios where III-Vs are produced at larger scale with modified manufacturing processes, 

deposition rate can have a more significant effect; additionally, in larger or more mainstream PV 

markets, the implications of $1/W lower costs, or even a few cents a Watt lower costs, are the 

difference between a competitive and uncompetitive cell design. These scenarios are explored in 

detail in Section 4.

The sensitivity of 2J cell manufacturing cost to number of substrate reuses at different CMP 

costs is shown in Figure 10. $25/CMP is the reference value (Table 2). $8–$10/CMP may be 

commensurate with scaling-up the current reclaim process to high volume. $1/CMP has not been 

demonstrated yet, to our knowledge. This could be achieved in effect by either reducing the cost 

of CMP per polish to $1, or by decreasing the frequency that CMP is required and lowering cost 

per polish (i.e., reducing CMP costs to $10/reuse and then only performing CMP after 10 reuses, 

possibly by utilizing protective layers as described in Lee et al. (2012). Ward et al. (2016)

provide further discussion on how the cost of the lift-off, reuse, and reclaim processes effect the 

total cost reductions that can be achieved as a function of reuses. We further discuss potential 

avenues to reduced substrate costs in Section 4.3. The degree to which moving to substrate 

reuses beyond 5–10 results in appreciably lower cost depends on the CMP, ELO processing, and 

other reclaim costs, as well as how the manufacturing yield loss changes with the number 

of reuses.
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Figure 10. 2J GaInP/GaAs cell manufacturing costs as a function of the number of substrate 

reuses at different CMP costs

4 Pathways to Reduce III-V Solar Cell Costs

Based on our analysis of current III-V solar cell costs, we can four key areas for cost reduction: 

scaling up production volume, reducing epitaxial growth costs, substrate costs, and metallization 

costs. Production yield improvements will also be critical across all these areas. In this section, 

we explore these pathways to lower cost, emphasizing R&D and manufacturing advancements 

required to achieve costs compatible with different PV markets. We focus on the case of the 2J 

GaInP/GaAs solar cell. 

4.1 Production Volume and Yield Improvements

Increasing production volume can drive cost reductions via economies-of-scale and learning-bydoing. We do not have sufficient information to project potential savings associated with 

learning-by-doing in this report, so this phenomenon is not accounted for here. It is also of note 

that, because III-V solar cells are currently produced at such a small scale, other effects of 

scaling, including potential evolution in supply chains, can be difficult to predict. For example, 

other industries, including the display, c-Si solar, and other industries have seen massive 

reductions in cost with scale, not all of which were fully anticipated (Keshner and Arya 2004; 

Fraunhofer Institute for Solar Energy Systems 2018; Park, Lee and Kim 2003).

However, it is still illustrative to observe the potential cost reductions associated with simply 

scaling-up the reference process flow described in Section 3.2 without modification. The results 

for the 2J solar cell are shown in Figure 11. We assume progressive reductions in CMP costs (to 

$8/CMP at 50MW/year), TMG and TMI precursor prices (to $0.60/g and $8/g, respectively, at 

50MW/year), and substrate costs (to $90/wafer at 50MW/year) as production volumes increase. 

We also assume MOCVD tool costs could be reduced by 10%–15% in high volumes. Other cost 

reductions result from improved tool utilization and increased automation and thus lower labor 

costs.
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Figure 11. Estimated impact of increased production volume on 2J GaInP/GaAs solar cell costs 

fabricated with MOCVD

Assumes five substrate reuses, 30% efficiency, and U.S. manufacturing.

We can see that the potential cost reductions associated with simply increasing production 

volume are significant—approximately $24/W going from 182 kW/year to 50 MW/year—but 

ultimately limited by the costs associated with the substrate, CMP, and device materials,

including III-V precursors and metal costs. Additionally, MOCVD equipment costs are still high, 

due to the high price per tool and the relatively long cycle times. While additional economies-ofscale and learning-by-doing may occur at even high production volumes (these are difficult to 

predict, given the small scale of current production), without process or design improvements 

to address these issues, scaling up production can only get you so far.

Costs on the order of $1/W to $10/W have been tolerable in certain markets, including UAVs, 

man-portable power (e.g., in military or outdoor recreational applications), and other niche 

applications; however, these are not compatible with broad deployment in general PV markets.

The remaining sections will review possible changes that could achieve further cost reductions.

4.2 Decreased Epitaxial Growth Costs

As discussed in Section 3, current MOCVD growth processes are expensive for several reasons: 

high cost per tool, low throughput, high cost precursors, and low material utilization. Significant 

reductions in epitaxy costs will involve improvements on all these fronts. Figure 12 illustrates 

the impact of different potential future improvements on the epitaxial growth costs for a 2J 

GaInP/GaAs solar cell at 50MW/year production volume. This assumes 95% yield for the 

epitaxial growth process in all scenarios (MOCVD and HVPE). The bar on the far left represents 

the reference case analyzed in Section 3.2. The second bar shows the cost reductions obtained 

when GaAs growth rates are increased from 15μm/hour to 60μm/hour, but it leaves the rest of 

the system and process the same, which is commensurate with publicly demonstrated growth 

rates as discussed above (Schmeider et al. 2017). It is of note that Fraunhofer has also publicly 

GaAs deposition rates of 145 μm/hour with lower efficiency cells (Lang et al. 2018). It may be 

possible to eventually deposit GaAs with MOCVD at these higher rates with good quality, 
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increasing throughput. However, cost reductions achieved with these faster deposition rates are 

eventually limited by the fixed heating and cooling time per wafer in current deposition systems.

To reach lower costs, additional throughput increases are required beyond which can be

accomplished with current batch MOCVD systems for III-As/P materials. This could be 

achieved by significantly increasing batch sizes, as has been done with GaN MOCVD reactors 

for LED growth, which can have batch sizes of 48 six-inch wafers (Veeco 2017). Alternatively, 

a continuous, in-line MOCVD reactor could be constructed. There has not been any public 

demonstration of such a system to-date, and, to our knowledge, no such system is used in 

production today. However, this may be feasible in the future, and if such a reactor were 

constructed, it could enable significantly higher throughput, resulting in a reduction in total epigrowth costs by more than half, as shown in the third bar of Figure 12. The potential throughput 

and equipment prices for this scenario are estimated using a bottom-up reactor model described 

in (Simon, Schulte and Horowitz et al. forthcoming). Because of their higher capital cost per 

tool, these large in-line reactors (or large batch reactors) are only relevant to higher production 

volumes. We estimate that volumes of at least several MW/year are required for the capital cost 

of these tools to be justified.

Additional reductions would require lowering material costs. A major lever for doing so is 

increasing the material utilization, for the trimethyl precursors and the arsine and phosphine. As 

we saw in Section 3.2, costs are particularly sensitive to improvements in arsine utilization. The 

fourth and fifth bars in Figure 12 show the potential impact of significantly increased material 

utilization in an in-line type MOCVD tool. Again, to our knowledge, these utilization rates have 

not yet been demonstrated for MOCVD. 50% to 60% utilization of TMG and TMI could be 

possible in commercial MOCVD systems according to our industry interviews and recent reports 

(Lang et al. 2018). Re-design of the gas delivery systems and deposition chamber may enable 

improvements.

Dynamic hydride vapor phase epitaxy (D-HVPE) is one technique which has actually

demonstrated very high growth rates—above to 195μm/hour for GaAs and 54μm/hour for 

GaInP—for full 2J solar cells in a pseudo-in-line reactor at the laboratory scale (Ptak 2018)

(Schulte et al. 2017; Simon, Schulte and Young et al. 2016). D-HVPE is a variation on HVPE, 

which has been previously used for growth of III-V materials, in which the reaction chambers are 

spatially separated, enabling the creation of high-quality interfaces at high throughput. This lab 

reactor design could be extended to a scaled, fully-in-line tool, wherein one chamber is used to 

deposit each cell layer (Young et al. 2018). A concept drawing for this type of in-line system 

is illustrated in Figure 13 (no such reactor has actually been built or demonstrated to-date). If 

implemented, a D-HVPE tool could enable even greater cost reductions, as shown in the last bar 

of Figure 12. This is mostly due to the fact that input material costs are lower – D-HVPE uses 

lower-cost elemental Ga ($0.21/g, 6N) and In ($0.50/g, 6N) in place of TMG and TMI. 

Additionally, high performing GaAs and GaInP solar cells have been grow at with V/III ratios 

of 2:4 using D-HVPE (Schulte et al. 2017; Simon, Schulte and Young, et al. 2016), resulting in 

much higher arsine and phosphine utilization. Additionally, TMG utilization rates of 70% have 

been estimated for the laboratory-scale tool. As with a very large, in-line MOCVD reactor, 

additional R&D is required to validate what utilization rates are possible. These utilization rates 

may not translate to a high-volume production tool, depending on the design, and significant 

uncertainty exists as to the final utilization rate. In this analyses, we deal with this by presenting 

parametric analyses showing costs with D-HVPE as a function of Ga and In utilization rates over 
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a wide range (Figure 14). Increasing the utilization of materials, or reducing the amount of 

material required by thinning the cell, also helps hedge against potential fluctuations in prices 

of the input materials. Ga and In prices have fluctuated significantly in the past.

Figure 12. Impact of increased throughput and material utilization on 2J GaInP/GaAs epi-layer 

costs with MOCVD and D-HVPE

Assumes 30% efficiency and U.S. manufacturing at 50MW/year; the second from the left bar represents a near-term 

MOCVD scenario; bars 3–5 are MOCVD scenarios based on possible future developments that have not been 

proven in practice (in the laboratory or at scale); the D-HVPE bar assumes that the laboratory pseudo in-line D-HVPE 

process described above is successfully scaled-up to 6’’ wafer areas and achieve high yields, which has also not 

been demonstrated.

Figure 13. Concept drawing of a high-volume, in-line reactor for depositing III-V solar cells

Six 6-inch wafers move through the reactor in parallel. There is one deposition chamber for each layer of the solar 

cell, and then length of the chambers are scaled according to the layer thickness and deposition rate.
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Figure 14. Sensitivity of epi-layer costs for a 2J GaInP/GaAs solar cell grown by D-HVPE to Ga and 

In material utilization rate

Figure 15 shows the sensitivity of growth costs for a 2J solar cell to additional key input 

parameters when D-HVPE is used. Figure 16 future illustrates the parametric dependence of epilayer costs on GaAs deposition rate for a range of GaInP deposition rates.

As with MOCVD, the price of the HVPE tool is an important driver; this contains significant 

uncertainty at this point, as no commercial D-HVPE tool has been built. The -20% (low bar) 

value of the HVPE tool price shown in Figure 15 is $7.4 million/tool (installed) and the +20% 

(high bar) value of the HVPE tool price is $11 million/tool, with a reference modeled cost of 

$9.2 million/tool.

Figure 15. Sensitivity of epi-layer costs for a 2J GaInP/GaAs cell grown via D-HVPE to key 

input parameters

Assumes 30% cell efficiency and U.S. manufacturing at 50 MW/year
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Figure 16. Sensitivity of epi-layer costs for a 2J GaInP/GaAs solar cell grown using D-HVPE to 

GaAs and GaInP deposition rates

The discontinuous behavior is due to the fact that tools are discrete units.

While per gram costs of precursor materials may decrease further in the future, they are already 

quite low, with TMG prices in particularly having been reduced dramatically in recent years due to 

scaling and advancements in the LED industry. The TMG price assumed for U.S. manufacturing at 

50MW/year is $0.60/g. Prices as low as $0.45/g have been reported for Chinese manufacturing as 

discussed above. This would result in an additional decrease of $0.01/W to $0.02/W in epi-costs 

compared to the fifth bar in Figure 12. Using elemental Ga and In instead of highly engineered 

trimethyl precursors also presents a fundamental advantage in cost. Any R&D to further reduce the 

cost per gram of input materials is of value to achieving low-cost III-Vs.

If the future, new growth techniques with similarly high throughputs and low materials costs 

(through a combination of increased utilization and lower input material prices) could also be 

developed.

4.3 Lowering Substrate Costs

As we saw in Section Figure 3, when substrate reuses is employed, substrate costs are driven by 

three primary factors: the substrate price, the number of reuses, and the cost of CMP and reclaim. 

There are different permutations of improvements in each of these areas that could be used to 

lower total substrate cost. Figure 17 shows the 2J solar cell manufacturing costs as a function of 

polishing cost per reuse and number of substrate reuses when ELO is used. For this case, we 

assume the ELO process has been improved, with additional parallelization in the process for 

bonding the cell to the handle as well as the use of a large wet etching tool the similar cost and 

batch size as HF wet processing tools used in the fabrication of c-Si solar cells (Woodhouse, 

Feldman et al. 2018). The result is a total ELO cost of approximately $0.10/W. These are 

assumptions for purposes of illustrating potential costs under this scenario; as previously 

discussed, ELO costs in volume contain significant uncertainty and very little data are available.
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Based on our interviews, we expect that reclaim, or polishing or CMP costs, could reach $8–

$10/polish using the current process flows at higher volumes. However, these processes have not 

yet been fully optimized, given the small size of the current market and lack of a need for much 

lower costs given the overall cost structure of current III-V solar cells. Thus, there is potentially 

room to further reduce these costs in the future by modifying the polishing and reclaim processes 

and/or adapting deposition processes to enable epitaxially growth on somewhat rougher surfaces.

Figure 17. Manufacturing cost for a 2J GaInP/GaAs solar cell deposited using D-HVPE as a 

function of number of substrate reuses and polishing cost per reuse

$90/6-inch GaAs substrate; assumes 30% efficiency and U.S. manufacturing at 50 MW/year

Reductions in cost for the ELO process are assumed compared to our baseline case in Section 3.2. 

It is important to note that the ability to achieve low-costs via substrate reuse depends critically 

on the yield of the lift-off and reuse process, on which there is no publicly available data. We 

have assumed a 10% additional yield loss associated with the lift-off and reuse process in this 

analysis. The optimal combination of lift-off, number of reuses, and polishing processes will 

likely be heavily influenced by yield issues.

An alternative path to lowering substrate costs is growing on a cheaper substrate than GaAs 

or Ge. This could be, for example, a virtual or engineered substrate, with a thin layer of latticematched material (e.g., GaAs and Ge) atop a lower-cost substrate. There has been some R&D in 

this area (e.g., Lee et al. 2016), but large-area virtual substrates appropriate for this application 

are not currently fully developed or commercially available. Another option could be to grow 

directly on a cheaper, lattice mismatched substrate. Direct growth of III-Vs on Si has been 

researched for both solar and non-solar applications for many years (Soga et al. 1997; Vaisman, 

et al. 2017; France, et al. 2016), but it has thus far proved challenging to achieve high material 

quality with this approach. However, this option is potentially appealing because Si wafers are so 

cheap ($0.50 to $1/wafer for a 244cm2 wafer) that costs may be competitive in some markets 

without reuse, and the Si could be used to create a bottom cell in a tandem device. Costperformance trade-offs and market needs must ultimately be considered for any process. As with 

reuse, high yield is also important for achieving very low costs. Any issues associated with 
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thermal mismatch of the substrates, either in manufacturing or after deployed in field (i.e.,

potential reliability issues) should also be considered. A reduction in the substrate price will 

result in a proportional reduction in the number of reuses required to achieve the same cost. For 

example, looking at Figure 17, if the substrate price is halved (to $45/6-inch wafer), half the 

number of reuses are required to achieve the same cost for a given polishing cost.

4.4 Low-Cost Metallization

Prevailing metallization approaches for III-V solar cells have often prioritized performance over 

cost, commensurate with the needs of current markets. In some cases, for example with cells for 

high-concentration photovoltaic applications, lithographically-defined contacts and highresolution metal deposition processes are necessary. However, lower cost metallization 

approaches are required for III-Vs to ever achieve low-cost compatible with more widespread 

deployment. Lower cost fabrication techniques could include electroplating and screen printing, 

which have been used for commercial c-Si solar cells. In addition to evaporation, electroplating 

is already widely used in the fabrication of III-V solar cells for R&D, but almost always a thick 

layer of gold is plated to maximize efficiency, and often photolithography is still used to define 

the contacts.

In this section, we explore the potential for using a gold-free electroplating approach to reduce 

metallization costs. Assumptions about the metal stack assumed are listed in Table 3. This results 

in a total metallization cost of $0.06/W at 30% efficiency. This includes full area metallization 

on the back of the cell. Lower costs—below $0.02/W at 30% efficiency—could be obtained if 

Cu-plated or Ag screen-printed contacts similar to those that have been considered for c-Si solar 

cells could be employed. However, these costs assume only partial coverage of the back of the 

cell, and thus the efficiency of III-V solar cells with this metallization would be lower. As with 

everything discussed in this Section, cost-performance trade-offs should be considered to 

determine the best approach. Additional research is required to fully understand how any type 

of modified contact affects efficiency and reliability of the device.

Table 3. Assumed Parameters of the Electroplated Contacts 

Parameter Value

Frontside metal stack Ni (1μm)/Ag(500nm)

Backside metal stack Ag(200nm)/Ni (8μm)

Frontside metal coverage ratio 15%

Backside metal coverage ratio 100%

Ag solution cost ($/kg) $462

Ni solution cost ($/kg) $49

It should be noted that metal prices also fluctuate significantly over time, and any fluctuations 

can affect the overall cost of solar cell contacts. However, for c-Si cells, increases in metal prices 

have tended to drive improvements that result in lower metal utilization or material substitution 

in the contacts that counteract some or all of these price increases.
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4.5 Putting it Together: A Roadmap to Low-Cost III-Vs

Figure 18 includes an illustrative roadmap for how low-cost 2J III-V solar cells might be 

achieved. The first stage involves scaling up current production, implementing D-HVPE, 

increasing the number of substrate reuses, reducing CMP costs, and using low-cost metallization. 

We estimate that these measures would reduce cost from the baseline cost (Section 3.2) of 

$32/W to $2/W. There are multiple pathways, with different permutations of reductions in 

substrate, epitaxy, and metallization costs that can be used to reach similar cost levels.

Figure 18. A roadmap to lower III-V solar cell costs

This illustrative example is for 2J GaInP/GaAs cells with 30% efficiency. It assumes U.S. manufacturing. 

To reach even lower costs that could enable use of these solar cells in a broader set of markets, 

further reductions in substrate costs and increases in production volume would be required. 

We illustrate the potential impact of increasing production to one gigawatt (GW) per year and 

reducing all-in substrate costs (including substrate price and any lift-off, polishing, and reclaim 

costs) to $1/6-inch wafer in Stage 2 of Figure 18. The majority of this cost reduction is achieved 

through lower substrate costs—using our model, we estimate that costs of $0.70/W could be 

achieved at 50MW/year with $1/substrate, $0.04/W higher than the costs at 1GW/year. However, 

as discussed above, there is still significant uncertainty in how manufacturing processes and 

supply chains might evolve if III-Vs were produced at GW-scale, and our model does not 

account for any effects of learning-by-doing, which could further drive down costs as cumulative 

production increases.

A cost of $1/substrate is equivalent approximately 100 reuses of a GaAs substrate (at today’s 

volume prices) with low ELO costs and no CMP. As discussed in Section 4.3, this cost could 

also be obtained via the use of an alternative, low-cost substrate without lift-off, or a 

combination of reduced substrate and CMP costs and a lower number of reuses. Stage 3 in 

Figure 18 shows the additional savings if $1 all-in costs for an 8-inch (244cm2 when cropped 

to a pseudo-square) substrate could be obtained. While 8-inch GaAs substrates have been 

demonstrated (Compound Semiconductor 2002), they are not commercially available today.
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There are also several additional avenues for further cost reduction, including thinning the cell 

layers, increasing manufacturing yield, improving efficiency, and decreasing metal utilization or

using alternative, lower-cost metals. Additionally, optimization of the high-volume D-HVPE tool

and process (e.g., belt speed and number of wafers in parallel) could result in further cost 

reductions. 

5 Discussion

We find that there is significant opportunity to reduce III-V solar cell manufacturing costs from 

current levels of above $50/W to below $0.50/W. However, achieving the cost reductions would 

involve significant R&D as well as a scale-up of manufacturing. A cost of $2/W may be 

achievable in the relatively near term if (1) increased substrate reuse can be implemented with

high yields and reduced polishing or reclaim costs and (2) a commercial D-HVPE can be 

demonstrated and scaled-up. While a cost of $2/W is too high to compete in mainstream PV 

markets, it may be sufficient for certain specialty markets, including portable power for military

or outdoor recreation applications, PV on electric vehicles (cars, buses, RVs, trucks), and certain 

portable small-scale solar systems in developing countries. This would also represent a 

significant reduction of cost for III-Vs in markets where they are already used, including 

unmanned area vehicle (UAV) and space applications. These one-sun cell costs would also 

be tolerable in a low-concentration PV system.

To achieve costs below $0.50/W, either (1) significant increases in number of substrate reuses 

above the current state-of-the-art or (2) the use of an alternative, low-cost substrate is required. 

Additional increases in production volume will also likely be needed. If 8-inch substrates can

be used, costs of $0.40/W may be possible. While $0.40/W is still higher than c-Si cell 

manufacturing costs—typical prices for c-Si cells today are typically between $0.15/W and 

$0.25/W—this could enable III-Vs to compete in certain mainstream PV markets because of

the advantages of III-V materials, which include their higher efficiency, light weight, and high 

energy yield.

High-efficiency c-Si cells currently command price premiums in certain markets, particularly

residential rooftop markets. Analysis has shown that increasing efficiency can drive balance-ofsystem cost savings, with possible savings of $0.26/W, compared to a 19% efficient cell in

residential markets based on 2017 pricing (Fu et al. 2017). And, studies have estimated an 8%

increase in energy yield for a GaAs solar cell compared to a Si solar cell in Boulder, Colorado 

(Silverman et al. 2013) because of the lower temperature coefficient and operating temperature 

of GaAs. These combined factors could allow for a III-V solar cell with a comparable or lower 

levelized cost of energy (LCOE) in certain markets. III-Vs at this cost could also enable 

deployment in areas that are weight- or space-constrained. Additional research is required 

to understand the economic potential for adoption of these solar cells at different costs.
25

This report is available at no cost from the National Renewable Energy Laboratory at www.nrel.gov/publications.

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