Developments in Photoluminescence Characterisation for Silicon PV
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1 Developments in Photoluminescence Characterisation for Silicon PV School of Photovoltaic and Solar Energy Engineering Bernhard Mitchell 1, Thorsten Trupke 1,2, Jürgen W. Weber 2, Johannes Greulich 3, Matthias Juhl 1, Martin A. Green 1, Daniel Walter 4, Daniel Macdonald 4 1 University of New South Wales, Sydney, Australia 2 BT Imaging Pty Ltd, Sydney, Australia 3 Fraunhofer Institute for Solar Energy Systems (ISE), Freiburg, 1Germany 4 College of Engineering and Computer Science, The Australian 1National University, Canberra, Australia
2 Imaging internal properties of humans! X-Ray CT PET-CT 2
3 Imaging internal properties of silicon! TEM lattice structure Imaging material/device properties limited to DLIT, CDI/ILM Scanning with EBIC/XBIC, MDP/μPCD, QSSPC, LBIC 3
4 PL imaging visualises minority carrier properties! Mono-like wafer Mono-like wafer Mostly ambient light reflection! Laser generated band-to-band emission! PL x,y τ x,y (low injection) Optical image PL image 4
5 Outline: Spectral imaging on silicon bricks Proof of concept Overcoming experimental limitations Quantifying physical limitations Inline inspection and sorting Characterisation of next generation cell structures 5
6 Why brick imaging?? Bulk lifetime sufficient? Doping range? Dislocation density? Fe contamination? Where to cut off? Where dead? Which parts suitable for high efficiency devices? What efficiency to expect? What cost/profit to expect? 6
7 PL [a.u.] PL [a.u.] Challenges: Bulk but bare! 10 b =100 s, e =900nm, N A =10 16 cm -3, T=295K 1 Red zone SRV [cm/s] 2.0 b =100 s, N A =10 16 cm -3,T=295K Super low PL! 1.5 Red zone 1.0 Bulk lifetime image Excitation wavelength [nm] 7
8 8 Proof of concept study
9 PLIR: from qualitative to quantitative images PL intensity image Bulk lifetime image 9
10 Modelling spectral PL response of brick Assumptions: 1D model, bare surfaces, infinite depth, monochromatic excitation, thin surface damage layer (after polish), non-injection dependent bulk lifetimes Includes: Temperature dependence (absorption coefficient, mobility), Free carrier absorption, SRV dependence, Excitation and filter selection 10
11 Spectral composition of luminescence Reabsorption Experimental apparatus *M. A. Green, Appl. Phys. Lett. 99, (2011) 11
12 PL intensity normalised [a.u.] normalised Spectral composition of luminescence absorption coeff. silicon 300K 100 s 10 s 1 s b increase Wavelength [nm] 12
13 13 PL spectral intensity ratio
14 Proof of concept images τ b [µs] N A cm 3 14
15 What have we learned so far? PL spectrum contains lifetime information Remaining issues: blur + top/bottom regions + abs accuracy Measure two filtered images Lifetime & doping images Model PLIR(τ) transfer function 15
16 16 Overcoming experimental limitations
17 Optical light spread in detection CCD: Masking experiment SP filtered LP filtered 17
18 Optical light spread of localised illumination SP filtered LP filtered 18
19 Measurement of Point Spread Functions (PSF) SP detection LP detection 19
20 Deconvolution of single images SP filtered LP filtered 20
21 Improved bulk lifetime image Deconvoluted: As measured: 21
22 22 Bottom and top data strongly improved
23 Light spreading effects wafer measurements! Example: Estimate of efficiency potential of mc-si wafers B. Michl, M. Rüdiger, J. A. Giesecke, M. Hermle, W. Warta, and M. C. Schubert, Efficiency limiting bulk recombination in multicrystalline silicon solar cells, Solar Energy Materials and Solar Cells, vol. 98, pp , Mar Low blur images crucial for quantitative evaluation of PL data! As measured SP 1000 filtered D. Walter, A. Liu, E. Franklin, D. Macdonald, B. Mitchell, and T. Trupke, in IEEE 38th Photovoltaic Specialists Conference, Austin, TX, 3 8 June
24 24 Alternative InGaAs detected PLIR?
25 25 Alternative InGaAs detected PLIR?
26 What have we learned more? Optical light spreading found to cause major image blur Remaining issues: Electrical blur Measurement of PSF Correlation with InGaAs detected image good Application of Deconvolution 26
27 27 Quantifying physical limitations
28 Image contrast and minority carrier diffusion SP 1000 nm filtered SP 1025 nm filtered LP 1050 nm filtered 28
29 Study: Grain / Grain boundary interface Measured bulk lifetime contrast at GB [µs] 29
30 30 Electrical simulation: 2D excess carrier densities
31 31 Lateral effect of diffusion on PLIR detected bulk lifetime
32 32 Effect of free carrier absorption
33 Further conclusions Filtering changes lifetime contrast Free carrier absorption mostly negligible Lateral diffusion into GB changes local lifetime Estimate for bulk lifetime as function of distance to GB and grain lifetime 2D Modelling 33
34 Outlook brick characterisation Impurity analyses on brick level Full spectrum analyses Efficiency predictions? Inline measurements 34
35 Inline inspection and sorting of as-cut wafers As cut wafer vary vastly in impurity and dislocation concentration! Inspection and classification at inline speed now possible! 35
36 Dislocation Defect Classification: mc-si & cast mono PL Image Processed Image
37 Correlation between defect metrics and cell performance Strong correlation of IV data with PL defect metric! No lifetime data used for correlation! W. McMillan, T. Trupke, J. Weber, M. Wagner, U. Mareck, Y.C. Chou, and J. Wong, In-line monitoring of electrical wafer quality using photoluminescence imaging, Proceedings of 25th EPVSC, Valencia, Spain, September,
38 38 Defect band imaging
39 Impurity Signatures Ingot Edge Transition Ingot Corner Fully Impure (top/bottom)
40 Impurity Signatures Dependence on dislocation density, weaker than usual. Strong dependence on impurity fraction! Poor gettering! 40 40
41 Characterisation of Advanced Cell Concepts with Sub-Micron Resolution Micro PL spectroscopy Gundel et al. Nanoscale Research Letters 2011, 6:197 41
42 Nickel plated front contacts Contact was tempered at 500C for 10 min Paul Gundel et al. / Energy Procedia 8 (2011)
43 Laser doped back surface field Paul Gundel et al. / Energy Procedia 8 (2011)
44 Conclusions & Outlook PL Imaging with increasing number of quantitative applications Quantitative brick imaging could become a valuable early stage characterisation and prediction tool Qualitative images contain more than just effective lifetime imaging (as-cut sorting, gettering efficiency, efficiency prediction) Microscopic PL candidate for research application (local doping structures, local recombination activity, defects) PL keeps playing a strong role as an ideal characterisation tool for solar cell materials and devices 44
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