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.

Contract No. DE-AC36-08GO28308

Imaging Study of 

Multi-Crystalline Silicon Wafers 

Throughout the Manufacturing 

Process

Preprint

Steve Johnston, Fei Yan, 

and Mowafak Al-Jassim

National Renewable Energy Laboratory

Katherine Zaunbrecher 

National Renewable Energy Laboratory and Colorado 

State University

Omar Sidelkheir and Alain Blosse 

Calisolar

Presented at the 37th IEEE Photovoltaic Specialists Conference 

(PVSC 37)

Seattle, Washington

June 19-24, 2011

Conference Paper

NREL/CP-5200-50724

July 2011
NOTICE

The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC 

(Alliance), a contractor of the US Government under Contract No. DE-AC36-08GO28308. Accordingly, the US 

Government and Alliance retain a nonexclusive royalty-free license to publish or reproduce the published form of 

this contribution, or allow others to do so, for US Government purposes.

This report was prepared as an account of work sponsored by an agency of the United States government. 

Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, 

express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of 

any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately 

owned rights. Reference herein to any specific commercial product, process, or service by trade name, 

trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, 

or favoring by the United States government or any agency thereof. The views and opinions of authors 

expressed herein do not necessarily state or reflect those of the United States government or any agency thereof.

Available electronically at http://www.osti.gov/bridge

Available for a processing fee to U.S. Department of Energy

and its contractors, in paper, from:

U.S. Department of Energy

Office of Scientific and Technical Information

P.O. Box 62

Oak Ridge, TN 37831-0062

phone: 865.576.8401

fax: 865.576.5728

email: mailto:reports@adonis.osti.gov

Available for sale to the public, in paper, from:

U.S. Department of Commerce

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

phone: 800.553.6847

fax: 703.605.6900

email: orders@ntis.fedworld.gov

online ordering: http://www.ntis.gov/help/ordermethods.aspx

Cover Photos: (left to right) PIX 16416, PIX 17423, PIX 16560, PIX 17613, PIX 17436, PIX 17721

Printed on paper containing at least 50% wastepaper, including 10% post consumer waste.
1 

IMAGING STUDY OF MULTI-CRYSTALLINE SILICON WAFERS THROUGHOUT THE 

MANUFACTURING PROCESS

Steve Johnston1, Fei Yan1, Katherine Zaunbrecher1,2, Mowafak Al-Jassim1, Omar Sidelkheir3, and Alain Blosse3 

1

National Renewable Energy Laboratory, Golden, CO, USA 2

Colorado State University, Fort Collins, CO, USA 3

Calisolar, Sunnyvale, CA, USA

ABSTRACT

Imaging techniques are applied to multi-crystalline silicon 

bricks, wafers at various process steps, and finished solar 

cells. Photoluminescence (PL) imaging is used to 

characterize defects and material quality on bricks and 

wafers. Defect regions within the wafers are influenced by 

brick position within an ingot and height within the brick. 

The defect areas in as-cut wafers are compared to 

imaging results from reverse-bias electroluminescence 

and dark lock-in thermography and cell parameters of 

near-neighbor finished cells. Defect areas are also 

characterized by defect band emissions. The defect areas 

measured by these techniques on as-cut wafers are 

shown to correlate to finished cell performance.

INTRODUCTION

Imaging techniques can rapidly characterize material 

quality and defect density. Photoluminescence (PL) 

imaging can be applied to silicon from the brick level to all 

wafer process steps. [1-8] At the brick level, material 

thickness allows for measurement and correlation to 

lifetime where surface recombination effects are 

minimized. [6,7] At the as-cut wafer level where thin 

unpassivated wafers prevent accurate lifetime assessment 

due to surfaces, defects can still be categorized and 

quantified to predict finished cell performance. [3-5] Defect 

regions can be identified by recombination-limited band-toband PL or by defect-band emission. [9,10]

EXPERIMENT 

Band-to-band PL imaging is collected using a Princeton 

Instruments Pixis 1024BR Si CCD camera cooled to about 

-50°C. The light source is composed of four 810-nm laser 

diodes with engineered diffusers to spread out the light 

over the sample. The intensity is near that of one sun, or 

~100 mW/cm2

. As shown in Fig. 1, we have collected PL 

images on multi-crystalline silicon bricks. The bricks are 

156 mm wide and about 28 cm tall, and we have taken 

two one-megapixel images and stitched them together. 

These images of the front and back faces show some nonuniformities in the excitation and camera lens that lead to 

artifacts of bright areas in the center of each half and 

some bright streaks from the corners toward the center. A 

line scan of each image is shown in the plots of Fig. 1, 

where PL intensity is seen to decrease at the bottom and 

top regions.

Figure 1 Top images are PL images of the front and 

back sides of a brick. The plots show a line scan down 

the center of each face comparing PL intensity to 

lifetime.
2 

Resonant-coupled photoconductive decay (RCPCD) is a 

transient-decay minority-carrier lifetime measurement 

technique. [11] Using ~12-mm-diameter spot size of 1150-

nm excitation laser pulses (5 ns pulsewidth), we have 

measured lifetimes along the same center line of each 

side. In Fig. 1, the circles on the PL images show the 

relative spot size and how the spot is stepped along the 

entire length of the brick. The lifetimes are then plotted on 

the right axis in comparison with the PL intensity to show a 

correlation. This correlation could then transform the PL 

image into a high-resolution lifetime map. [6,7]

For cast multi-crystalline silicon ingots, the defect structure 

in the form of grain boundaries and dislocation clusters 

typically increases with brick height from bottom to top. 

The PL images on as-cut wafers from various heights 

within a corner brick and interior brick are shown in Fig. 2. 

The image position corresponds with brick position, i.e., 

the bottom images are from the bottom of the bricks, and 

top images are from the top of the bricks.

Figure 2 Examples of defect density increasing with 

brick height for a corner brick (left) and interior brick 

(right). The bottom images are from the bottom of the 

bricks, while the middle and top images are of wafers 

from the middle and top of the bricks.

PL imaging can be measured on wafers at all steps of the 

solar cell manufacturing process. Thin wafers with 

unpassivated surfaces do not allow for accurate 

measurement of bulk minority-carrier lifetime. [4,5,7] At the 

early process steps, such as after wire sawing and sawdamage removal and texturing, the lifetime is dominated 

by surface recombination. Long lifetime regions are limited 

by surface recombination such that average material 

quality cannot be distinguished from very good material 

quality. However, defect areas appear dark in PL images 

due to their short lifetime and high recombination, and 

these defect areas often are the cell’s limiting performance 

regions as seen by quantum efficiency and light beam 

induced current maps on finished cells. Consequently, 

even though PL imaging on as-cut wafers may not give 

quantitative values of lifetime and an accurate assessment 

of bulk material quality, it can still be used to detect and 

characterize defect areas that do correlate to finished cell 

performance. [3-5] 

Neighboring wafers have been processed through a 

manufacturing line with removal of wafers at each step to 

show how PL imaging varies by process. These steps 

include wafer sawing, cleaning and texturing, emitter 

diffusion, edge isolation and phosphosilicate glass (PSG) 

removal, anti-reflective coating (ARC) and passivation, 

and metallization of finished cells. Figure 3 shows 

examples of PL imaging on neighboring wafers from the 

middle regions of both a corner brick (left column) and an 

interior brick (right column).

As-cut wafers are challenging to image due to high 

surface recombination, but identifying highly defective 

wafers at this early process step may have the largest 

savings impact if such wafers are determined to be too 

poor and not worth processing. Wafers could also be 

categorized by defect level so that high-quality wafers 

could be processed on a manufacturing line to take full 

advantage of their potential efficiency, while defectcontaining wafers may benefit from modified processing to 

enhance cell performance. [3,5] Examples of defects seen 

by PL imaging on as-cut wafers are shown in the top 

images of Fig. 3.

While texturing doesn’t appear to affect the PL image, the 

diffusion process of forming the junction does significantly 

alter the PL image. Contrast between defect-containing 

and relatively defect-free regions is greatly enhanced. 

When the thermally-grown PSG is removed in the 

subsequent etch step, the image contrast is slightly 

reduced, suggesting that some additional surface 

passivation was provided by the PSG. Also in the prediffusion images for the corner wafer, the crucible-related 

impurities dominate the dark defect regions of these 

wafers, but after diffusion, impurity gettering appears to 

have effectively reduced the relative defect level of the 

edges compared to grain boundaries and dislocation 

clusters within the wafer. The ARC processing doesn’t 

appear to significantly alter the PL image when compared 

to the etching step after diffusion.
3 

Figure 3 PL imaging of near neighbor wafers at all 

process steps for a corner brick and interior brick.

Metallization and the associated firing that can release 

defect-passivating hydrogen from the silicon-nitride ARC 

layer may lead to subtle improvements in reduced defect 

contrast, but overall, the defect areas in the finished cells 

appear quite similar to those in the etched step and even 

in the as-cut wafer, away from the crucible edges. With the 

knowledge that defects in as-cut wafers persist through to 

completed cells, we can attempt to form a correlation of 

defect regions on as-cut wafers to final cell performance. 

[3-5] Corner and edge wafers contain cruciblecontaminated borders that have less impact on cell 

performance than they appear to at the as-cut stage. 

These areas are thus highlighted and counted separately 

as shown in Fig. 4.

Figure 4 PL images of corner-brick and interior-brick 

wafers are shown in the top row. Below each PL 

image is a defect-highlighted image for that wafer.

For the corner wafer, an image threshold level is defined 

that highlights the dark impurity region, which is shown in 

green. For the remaining area, and for the entire wafer for 

those from interior bricks, another threshold is defined to 

highlight grain boundaries and dislocation/defect clusters, 

which are shown in red. Each is then summed to give a 

defect area fraction of the wafer.

Weighting factors are assigned so that the red-colored 

defects due to dislocations and grain boundaries are 

weighed more heavily than the green-colored impurity 

areas at the wafer edges. A linear combination of these 

defect area fractions forms a total defect parameter. This 

defect parameter from as-cut wafers is plotted in Fig. 5 to 

compare to near-neighbor finished cell efficiency, opencircuit voltage (VOC), and short-circuit current (JSC). The 

blue and purple markers correspond to wafers and cells 

from corner bricks, while the orange markers represent 

wafers and cells from an interior brick. Correlations 
4 

between the as-cut wafers’ defect parameter and the 

finished cells’ efficiency, VOC, and JSC are evident.

Figure 5 Defect parameter of as-cut wafers compared 

to finished cell performance. Blue and purple markers 

represent wafers and cells from corner bricks, and 

orange markers represent an interior brick.

Imaging techniques requiring contacts can be applied to 

finished cells. These techniques include electroluminescence (EL) and dark lock-in thermography (DLIT). 

[12-16] Examples of these techniques applied to the 

finished cells of Fig. 3 are shown in Fig. 6. Forward bias 

EL images are shown in the top row, and they appear 

quite similar to the PL images of Fig. 3. Resistance issues 

such as firing non-uniformities or broken grid lines can 

often show up as differences between EL and PL images, 

but none appear obvious in this case.

Figure 6 EL images of the finished cells of Fig. 3. The 

top row shows forward bias, while the second row 

shows ReBEL imaging with a reverse bias of 12 V. 

The third row shows DLIT also using 12 Vrev. The 

bottom row shows defect band emission on 

corresponding near-neighbor as-cut wafers.

The second row of images in Fig. 6 shows Reverse-Bias 

EL (ReBEL) images at 12 Vrev. [17-19] Visible light emits 

from regions where diode breakdown is occurring. The 

pattern of breakdown occurring at defect areas compares 
5 

well to the DLIT images shown in the third row of Fig. 6. 

The DLIT images are also collected using a reverse bias 

of 12 V.

Defect states in silicon can emit radiative sub-bandgap 

photons. [9,10] We have used a FLIR SC2500 InGaAs 

camera with sensitivity to detect photons with wavelengths 

from 0.9 to 1.7 μm. This spectrum covers both the silicon 

band-to-band emission at ~1.1 eV (1150 nm) and defectrelated emission at ~0.8–1.0 eV (1250–1550 nm). For

defect band emission imaging, a long-pass filter with a cutoff wavelength at 1350 nm is used to block band-to-band 

PL. The camera contains a lock-in detection option to 

improve the signal-to-noise ratio. Defect band PL is 

collected when pulsing the 810-nm laser diode excitation 

at about 7 Hz. Examples of the resulting defect band PL 

are shown in the bottom row of Fig. 6, where bright 

regions correspond to strong defect band emission. These 

defect band areas compare well to those where diode 

breakdown occurs in reverse bias and those where PL 

and EL images are dark due to high recombination. Defect 

band emission is suppressed in the areas of high impurity 

contamination from the ingot crucible, as seen for the 

corner as-cut wafer in the bottom left image of Fig. 6. [10] 

As shown with the band-to-band PL images, this edge 

area improves with processing, so defect characterization 

with this sub-bandgap PL can still correlate to finished cell 

device performance. The defect band emission is 

quantified for each as-cut wafer by setting a threshold 

value. Then, the area fraction of intensities above this 

threshold is plotted against finished cell efficiency, VOC, 

and JSC in Fig. 7. Similar to Fig. 5, the blue and purple 

markers represent wafers and cells from corner bricks, 

and orange markers represent an interior brick. Also 

similar to the band-to-band PL image analysis, 

correlations between the as-cut wafers’ defect band 

emissions and the finished cells’ efficiency, VOC, and JSC

are evident.

SUMMARY

We have shown that PL imaging can be measured on 

silicon bricks and at every step of processing into solar 

cells. PL images on silicon bricks can be correlated to 

lifetime and could be used for high-resolution analysis and 

characterization. PL images at process steps show defect 

areas and how some evolve with processing while many 

detrimental areas remain from as-cut to finished cells. 

Such defect areas can be quantified and correlated to cell 

performance so that as-cut wafers could be classified to 

their potential for cell efficiency before processing. 

Reverse-bias breakdown imaging was collected using 

both reverse-bias EL and dark lock-in thermography. 

These techniques were shown to also highlight defect 

areas similar to the high recombination areas seen by PL. 

Lastly, defect band imaging using an InGaAs camera was 

shown, and correlations of these defect areas seen on ascut wafers also correlated to finished cell parameters. 

Figure 7 Defect band emission PL of as-cut wafers 

correlated to near-neighbor finished cell performance. 

Blue and purple markers represent wafers and cells 

from corner bricks, and orange markers represent an 

interior brick.

ACKNOWLEDGEMENT

This work was supported by the U.S. Department of 

Energy under Contract No. DE-AC36-08GO28308 with the 

National Renewable Energy Laboratory and with support 

from the American Recovery and Reinvestment Act.
6 

REFERENCES

[1] T. Trupke, R. A. Bardos, M. C. Schubert, and W. 

Warta, “Photoluminescence Imaging of Silicon Wafers”, 

Appl. Phys. Lett. 89, 2006, 044107.

[2] T. Trupke, R. A. Bardos, M. D. Abbott, F. W. Chen, 

J. E. Cotter, and A. Lorenz, “Fast Photoluminescence 

Imaging of Silicon Wafers”, 32nd IEEE PVSC and WCPEC4, 2006, pp. 928-931.

[3] W. McMillan, T. Trupke, J. W. Weber, M. Wagner, U. 

Mareck, Y. C. Chou, and J. Wong, “In-line Monitoring of 

Electrical Wafer Quality Using Photoluminescence 

Imaging”, 25th EPVSEC/5th WCPEC, Valencia, Spain, 

2010, pp. 1346-1351.

[4] J. Haunschild, M. Glatthaar, M. Demant, J. 

Nievendick, M. Motzko, S. Rein, and E. R. Weber, “Quality 

control of as-cut multicrystalline silicon wafers using 

photoluminescence imaging for solar cell production”, Sol. 

Ener. Mat. & Sol. Cells 94, 2010, pp. 2007-2012.

[5] T. Trupke, J. Nyhus, and J. Haunschild, 

“Luminescence imaging for inline characterization in 

silicon photovoltaics”, Phys. Status Solidi RRL 5, 2011, pp. 

131-137.

[6] T. Trupke, J. Nyhus, R. A. Sinton, and J. W. Weber, 

“Photoluminescence imaging on silicon bricks”, 

Proceedings of the 24th European Photovoltaic Solar 

Energy Conference, Hamburg, Germany, 2009, pp. 1029-

1033.

[7] B. Mitchell, T. Trupke, J. W. Weber, and J. Nyhus, 

“Bulk minority carrier lifetimes and doping of silicon bricks 

from photoluminescence intensity ratios”, J. Appl. Phys. 

109, 2011, 083111.

[8] J. Haunschild, M. Glatthaar, S. Riepe, and S. Rein, 

“Quality control using luminescence imaging in production 

of mc-silicon solar cells from UMG feedstock”, 35th IEEE 

PVSC, 2010, pp. 812-816.

[9] I. Tarasov, S. Ostapenko, C. Haessler, and E. U. 

Reisner, "Spatially resolved defect diagnostics in 

multicrystalline silicon for solar cells," Mat. Sci. & Engr. B 

71 (1-3), 51-55 (2000).

[10] M. Kittler, W. Seifert, T. Arguirov, I. Tarasov, and S. 

Ostapenko, “Room-temperature luminescence and 

electron-beam-induced current (EBIC) recombination 

behaviour of crystal defects in multicrystalline silicon”, Sol. 

Ener. Mat. & Sol. Cells 72, 2002, pp. 465-472.

[11] R. K. Ahrenkiel and S. Johnston, “Contactless 

measurement of recombination lifetime in photovoltaic 

materials”, Sol. Ener. Mat. & Sol. Cells 55, 1998, pp. 59-

73.

[12] T. Fuyuki, H. Kondo, T. Yamazaki, Y. Takahashi, 

and Y. Uraoka, “Photographic Surveying of Minority 

Carrier Diffusion Length in Polycrystalline Silicon Solar 

Cells by Electroluminescence”, Appl. Phys. Lett. 86, 2005, 

262108.

[13] T. Fuyuki, H. Kondo, Y. Kaji, A. Ogane, and Y 

Takahashi, “Analytic Findings in the Electroluminescence 

Characterization of Crystalline Silicon Solar Cells”, J. Appl. 

Phys. 101, 2007, 023711.

[14] O. Breitenstein, M. Langenkamp, O. Lang, and A. 

Schirrmacher, “Shunts Due to Laser Scribing of Solar 

Cells Evaluated by Highly Sensitive Lock-in 

Thermography”, Sol. Ener. Mat. & Sol. Cells 65, 2001, pp. 

55-62.

[15] O. Breitenstein, J. Bauer, J.-M. Wagner, and A. 

Lotnyk, “Imaging Physical Parameters of Pre-Breakdown 

Sites by Lock-in Thermography Techniques”, Prog. 

Photovolt: Res. Appl. 16, 2008, pp. 679-685.

[16] O. Breitenstein, W. Warta, and M. Langenkamp, 

“Lock-in Thermography: Basics and Use for Evaluating 

Electronic Devices and Materials”, 2nd Ed., SpringerVerlag, Berlin, 2010.

[17] A. G. Chynoweth and K. G. McKay, “Photon 

Emission from Avalanche Breakdown in Silicon”, Physical 

Review 102, 1956, pp. 369-376.

[18] M. Morschbach, M. Oehme, and E. Kasper, “Visible 

Light Emission by a Reverse-Biased Integrated Silicon 

Diode”, IEEE Trans. Elec. Dev. 54, 2007, pp. 1091-1094.

[19] D. Lausch, K. Petter, H. von Wenckstern, and M. 

Grundmann, “Correlation of Pre-Breakdown Sites and 

Bulk Defects in Multicrystalline Silicon Solar Cells”, Phys. 

Status Solidi RRL 3, 2009, pp. 70-72.