Solid State Phenomena Vols (2014) pp (2014) Trans Tech Publications, Switzerland doi: /
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1 Solid State Phenomena Vols (2014) pp (2014) Trans Tech Publications Switzerland doi: / '(')"(!*&$+*$-./#(0$$(1*$ %$!'!' /$ *)"( /2&34 5&2// /52& /2 2& #//!/ Photoluminescence imaging techniques have recently been extended to silicon bricks for early production quality control and electronic characterisation in photovoltaics and microelectronics. This contribution reviews the state of the art of this new method which is fundamentally based on spectral luminescence analyses. We present highly resolved bulk lifetime images that can be rapidly extracted from the side faces of directionally solidified or Czochralski grown silicon bricks. It is discussed how detailed physical modelling and experimental verification give good confidence of the best practice measurement errors. It is also demonstrated that bulk lifetime imaging can further be used for doping and interstitial iron concentration imaging. Additionally we show that full spectrum measurements allow verification of the luminescence modelling and are when fitted to the theory another accurate method of extracting the absolute bulk lifetime. Crystalline Si (c-si) is and has been the work horse of the photovoltaic (PV) industry for many years. In 2012 almost 90% of the fabricated solar cells worldwide were made from crystalline silicon [1]. The crystalline silicon technology has been able to reduce the production costs dramatically while slowly but constantly improving the efficiency of the devices. Thus it remained the most competitive PV technology with state of the art module conversion efficiencies of 16-22%. The device structure for the most common industrial solar cells has remained largely the same and is based on a structure first published in the 1970s. The industry tends to behave conservatively by only advancing the technology incrementally to ensure the product quality is maintained at the highest level to fulfil warranty requirements of 25 years or more. A large proportion of the cost reduction that has been achieved is due to improved Si purification and crystallization techniques. It seems that in particular increased throughputs and energy efficiency measures have allowed this to occur [2]. Seeded and grain size controlled crystal growths allow higher efficiencies to be achieved on directionally solidified multicrystalline Si (mc-si). Ingot sizes of typically 450 kg and in tests up to 1000 kg are currently used leading to large ingots that are cut into 6x6 bricks each six-inch squared in area and cm in height prior to wafer slicing. High efficiency cell concepts can be expected to gain a larger market share in the midterm future due to the rising proportion of the balance of system (BOS) cost in PV systems. Device architectures beyond 20% efficiency are likely to be based on monocrystalline wafers and n-doped bulk material is expected to gain market share. Oxygen complexes and interstitial iron do not limit the performance of phosphorus doped silicon to the same extent as they do in boron doped Czochralski-grown material [34]. However the lower segregation coefficient of phosphorous
2 Solid State Phenomena Vols typically yields greater resistivity variation throughout the ingot thus increases the need for electrical characterisation and cell architectures that are more tolerant to variations in bulk doping. It becomes evident that quality electrical characterisation of photovoltaic silicon bricks after crystallization is of high and rising importance as it can increase not only the productivity of the directional solidification but also permits selective cutting and specialised processing. In an industrial environment the desired characterisation method would allow non-destructive measurements (i) with high spatial resolution (ii) at inline speed (iii) with high bulk lifetime sensitivity and (iv) with reliable accuracy. A number of techniques have been used for the electrical characterisation of silicon bricks prior to wafer slicing such as microwave detected photoconductance decay (µ-pcd) [56] and inductively coupled quasi-steady-state photoconductance (QSSPC) [78]. More recently steady state PCD measurements were introduced enabled by improved laser technology [910]. All of these techniques are based on photoconductance measurement principles and generate spatially resolved data by raster scanning the brick surface. With the introduction of luminescence imaging [1112] a purely optical technique is now available for spatially resolved electrical characterisation. Numerous qualitative and quantitative methods based on photo- and electroluminescence imaging have recently been developed. The initial measurement principle was a simple qualitative steady-state measurement but later also spectral [13 16] time dependent [1718] and polarization [19] dependent measurements were introduced all of which are adaptations of the basic PL imaging principle and setup [20]. In the last few years the use of photoluminescence (PL) imaging has been further extended to allow quantitative electrical characterisation of silicon bricks. This work will be reviewed in this article. In 2009 the application of PL imaging on silicon brick side faces was explored firstly by Trupke et al. [21]. It was shown that PL images can be measured on the side faces of cast boron doped mc-si bricks with high spatial resolution and short measurement times. Fig. 1a illustrates such a raw PL image measured with a resolution of 1.5 megapixel and a 10 s exposure time. #0(67!/6µ7 (a) (b) Fig. 1: (a) Qualitative raw PL image of a directionally solidified mc-si brick. The image contrast is given in digital count rates. (b) Calculated relative PL intensity as a function of bulk lifetime for bare silicon brick at 880 nm monochromatic illumination
3 120 Gettering and Defect Engineering in Semiconductor Technology XV The luminescence emitted by the brick is determined by the spontaneous emission inside the sample resulting from the radiative recombination of excess minority electrons and holes. PL images are typically taken at a photon flux equivalent to one sun (0.1 Wcm - 1) and thus provide the electronic properties that are representative for the operation conditions of typical industrial solar cells. The minority carrier densities of a bare silicon brick remain in low injection ( n«n) during a steady-state one sun illumination. For this case the spontaneous emission is defined simply by the product of the excess minority carrier density n and the background doping density N i.e. r sp nn. The image contrast of Fig. 1 therefore represents the convoluted effect of variations in both effective minority carrier lifetime and background doping. The excess carrier density on the illuminated side of the silicon brick in difference to a standard silicon wafer is not influenced by the rear surface. This enables an analytical solution of the carrier density with dependence on depth diffusion length and front surface recombination velocity following Bowden and Sinton [22]. Since the diffusion length of both directionally solidified and Czochralski grown ingots are small compared to the sample thickness there is no saturation of the measured effective lifetime with increasing bulk lifetime. Fig. 1b plots the PL intensity as a function of bulk lifetime on double logarithmic scale using the analytical solution of the excess carrier density with assuming a constant doping density a Si CCD detector camera and no additional filtering. The graph reveals that the bulk lifetime contrast in the PL signal decreases towards higher lifetimes but does not saturate. A calibration constant and the local doping need to be measured separately to extract absolute bulk lifetime information from a single PL image such as the one shown in Fig. 1a. This can for example be realised via an additional QSSPC measurement as specified in [21] and [15]. The analysis of just the luminescence intensity from a single image as discussed above is somewhat limited in terms of converting the PL intensity into quantitative information. Fundamentally this is related to difficulties in accurately measuring absolute photon fluxes in PL measurements. However quantitative data extraction is facilitated if additional information is available e.g. spectral information or time dependent data. In the last few years the use of spectral luminescence intensity ratio imaging was initially introduced to cell [13] and wafer measurements [14] and has more recently been extended to silicon bricks. These are well suited samples for spectral photoluminescence analyses given that measurements can be performed on polished surfaces. This allows for a one-dimensional analytical analysis. Thus it has been possible to demonstrate the spectral photoluminescence intensity ratio (PLIR) analysis as an independent quantitative measure for minority carrier bulk lifetimes on bare bricks [1523]. A spectral PLIR analysis eliminates the need for absolute luminescence intensities to be known since pure spectral variations define the bulk lifetime signature of the luminescence response. Spectral changes occur due to luminescence reabsorption on the optical path from the origin to the surface of the brick. Given that the rate of spontaneous emission r sp at low injection is defined by the excess carrier density n(xτ b ) we calculate the bulk lifetime (τ b ) dependent PL intensity following d λ α( λ) x ( λ) n( x τ ) e Θ( λ) PL( τ ) r dλdx (1) b 0 λ 0 sp0 where r sp0 is the spontaneous emission rate at equilibrium θ(λ) the spectral sensitivity of the experimental apparatus and α(λ) the absorption coefficient of crystalline silicon. The analytical solution of this integral is given by Green [24]. A simple rating of the spectral dependence can be realised by a two-filter approach in which two measurements of the luminescence signal are performed with different spectral filters. It is crucial in this context to choose the band pass filters in such a way that the impact of bulk lifetime on the b
4 Solid State Phenomena Vols PL intensity ratio is maximised (see Fig. 2). Furthermore experimental conditions need to be selected to most optimse for a maximal bulk lifetime signal. One-dimensional modelling of the luminescence response of the specific experimental setup allows for an optimisation and definition of a PLIR to bulk lifetime transfer function as illustrated in Fig. 2b. Note that the background doping does not affect the spectral dependence of the luminescence response and consequently cancels out in the PL ratio used for the bulk lifetime assessment. 0/( µ µ µ µ µ µ µ µ λ 6/7 #0(.9:$#;8:0#< $ :$#:0#-!/6µ7 (a) (b) Fig. 2: (a) Dependence of the short (1000 nm blue) and long (>1050 nm red) pass filtered PL intensities on bulk lifetime shown as a function of wavelength; (b) Calculated PL intensity ratio to bulk lifetime transfer function for different camera and filter combinations. Silicon CCD camera are widely used for PL imaging. Their strengths include extremely low read and dark noise [23]. The relatively low price of scientific CCD chips and cameras allows for industrial applications of PL (and EL) imaging. The use of silicon CCDs for PLIR measurements needs to be considered with care since the low quantum efficiency in the wavelength range of the measured luminescence emission causes a spreading of luminescence light within the CCD thus resulting in significant errors if not corrected [2325]. Two strategies were successfully demonstrated to largely overcome this limitation. One consists of image deconvolution using an experimentally determined point spread function which is measured specifically for the experimental set up and separately for each spectral filter. The other approach is to employ an InGaAs camera which does not suffer of light spreading and also improves the absolute accuracy for medium to high bulk lifetimes (see Fig. 2b) due to its fairly constant quantum efficiency throughout the Si luminescence spectrum. However the InGaAs camera cannot deliver the same pixel resolution and accuracy for low (1-100 µs) bulk lifetimes with currently available camera technology. Fig. 3 presents PLIR detected bulk lifetime images using both camera types in direct comparison. The signal to noise ratio (SNR) of the Si CCD detected images is superior. However the InGaAs camera resolves smaller grain structures with better contrast. In the InGaAs image the bulk lifetime contrast is almost entirely limited by lateral minority carrier diffusion into the grain boundaries and dislocations and not by optical image blur which dominates the Si CCD detected image [26]. The uncertainty of the PLIR detected bulk lifetime has been estimated to be between 20-30% relative when measured with the current Si CCD based technology a laser illumination at 880 nm and using a deconvolution correction [23]. In principle an InGaAs camera provides better accuracy the relatively high dark and read noise of current InGaAs cameras limits the applicability in practice. It has been found necessary to apply a short pass filter with a band pass at 1075 nm to achieve sufficient SNR in the short pass filtered image. Thus only limited low bulk lifetime sensitivity can be achieved since a wide gap between the short and long pass filtered images
5 122 Gettering and Defect Engineering in Semiconductor Technology XV maximises the bulk lifetime sensitivity of the two filter method. Nonetheless we believe that bulk lifetimes exceeding 100 µs can be detected with an uncertainty of below 15% [23]. A round robin experiment comparing PLIR with other measurement techniques such as QSSPC MDP and RCPCD [27] could provide more information about systematic errors of brick measurement techniques. (a) Fig. 3: PLIR detected bulk lifetime image of a directionally solidified mc-si brick employing (a) a Si CCD camera with subsequent deconvolution and (b) an InGaAs camera. The scale gives bulk lifetimes values in µs. The very top and bottom of the brick which appears white in (b) could not be evaluated due to a too low SNR of the InGaAs camera in this region. A single PL image contains both bulk lifetime and doping information. A doping image can also be extracted with the calculation of the PLIR bulk lifetime image (Fig. 3) since the bulk lifetime can be used to calculate a normalised PL image PL norm. The latter represents the PL image that would be expected for constant background doping concentration. A simple ratio of this PL norm image and the measured PL image thus provides a background doping density image. An example is shown in Fig. 4. A single calibration point is sufficient to transfer the resulting relative data into an absolute doping image. This can be achieved for example by an eddy current point measurement. (b)
6 Solid State Phenomena Vols Fig. 4: Relative doping image of the same directionally solidified mc-si brick derived from PLIR detected bulk lifetime image and a short pass filtered image. Influence of the surface polish is visible which indicates a current measurement artefact. Preliminary data is shown and uncertainties prevail in the top and bottom due to residual impact of image blur. A recent extension to the analysis has enabled the extraction of interstitial iron concentration images by employing the reversibility between the paired iron-boron and the dissociated interstitial state of iron in boron doped silicon [28 30]. We show preliminary quantitative data for PL based images of the Fe i concentration (see Fig. 5) that might extend the application of the PLIR and which are expected to be relevant for predictive models that correlate material properties with final device performance [31]. Fig. 5 shows that central areas of the brick contain the lowest interstitial iron concentration which is known to be one of the most detrimental impurities in silicon solar cells. A slowly increasing Fe i concentration level towards the top and sharp edges towards the bottom and top are observed. This information is obtained from a procedure that takes less than 5 min and includes the use of a strong xenon flash lamp for dissociation of the FeB pairs. A complete analysis and detailed description of PL based iron imaging of silicon bricks will be presented in an upcoming publication.
7 124 Gettering and Defect Engineering in Semiconductor Technology XV > 6/? 7 (a) = < ; %"!// Fig. 5: (a) PLIR detected interstitial iron concentration image of a directional solidified mc-si brick shown as log([fe i ]). (b) Corresponding cross-sectional average concentration as a function of brick height. No reliable data could be extracted in the bottom 10% and top 5% of the brick. The central dashed curve is given as a guide to the eye. Note that values are absolute but as yet not calibrated. (b) The analysis of the full PL spectrum can add to the PLIR analysis and extend its capabilities while providing a different seemingly more direct access to bulk lifetime information. We have been able to experimentally verify the physical modelling of the luminescence emission on silicon bricks [32]. The theoretical description of luminescence emission from an indirect semiconductor such as silicon was provided by Würfel et al. [33]. Spectral PL data on silicon samples have been used in a number of applications for example as a sensitive measure to determine the silicon absorption coefficient at very low values and for different types of doping concentrations as shown by Daub et al. [3435]. Green demonstrated that the full PL emission of a monochromatically illuminated silicon brick can be described analytically [24]. We have been able to show that PL spectra measured on silicon bricks can be fitted by the formula and bulk lifetime information can be extracted if measured with a calibrated detector [32]. Fig. 6 displays the measured spectra of four measurement spots taken on a directionally solidified (spot 4 and 5) and on a Cz-grown brick (spot 2 and 3) and their best curve fits according to the expression given by Green. We show that absolute bulk lifetime can be assessed with a statistical error of less than 14% with a confidence of 99% (11% with confidence of 95%) using the full spectral PL description by Green (see Fig. 6b). Note that the doping concentration does not have to be known for this procedure. However the fitting procedure is found to be sensitive to the source of absorption coefficient data (see [32]).
8 Solid State Phenomena Vols #0/ ; < = '@ <=µ '@ =;Aµ '@= µ '@- Aµ "6/7 $$% [7 - =- = - - = -< - = = < <- A!/6µ7 (a) (b) Fig. 6: (a) Non-linear full spectrum fits of experimental spectra covering a wide lifetime range with theoretical local bulk lifetime values listed; (b) Sum of the least square residuals for spot 3 with minimum and 95 and 99% confidence intervals A PL imaging based calibrated lifetime measurement for silicon bricks has been developed that is based on the PL intensity ratio method. It can be applied to silicon bricks directly after solidification and polishing i.e. prior to wafer slicing and enables important early stage electronic characterisation of silicon bricks. It combines the strengths of photoluminescence imaging specifically the short measurement times and high spatial resolution with excellent bulk lifetime sensitivity and accuracy. Proof of concept data for Fe images were shown in this paper. This research has been supported by the Australian Government through the Australian Renewable Energy Agency (ARENA). The authors thank J. Nyhus from Norner AS for the supply of silicon bricks. [1] Fraunhofer ISE Photovoltaics Report. (2012). [2] SEMI International Technology Roadmap for Photovoltaic (ITRPV) Results [3] D. Macdonald The emergence of n-type silicon for solar cell manufacture in: Proceedings of the 50th Annual AuSES Conference (Solar 2012) Melbourne Australia [4] J. Schmidt B. Lim D. Walter K. Bothe S. Gatz T. Dullweber et al. Impurity-Related Limitations of Next-Generation Industrial Silicon Solar Cells IEEE Journal of Photovoltaics. (2012) 1 5. [5] M. Kunst G. Beck The study of charge carrier kinetics in semiconductors by microwave conductivity measurements Journal of Applied Physics. 60 (1986) [6] M. Kunst G. Beck The study of charge carrier kinetics in semiconductors by microwave conductivity measurements. II. Journal of Applied Physics. 63 (1988) 1093.
9 126 Gettering and Defect Engineering in Semiconductor Technology XV [7] R.A. Sinton Predicting multi-crystalline solar cell efficiency from life-time measured during cell fabrication in: 3rd World Conference on Photovoltaic Energy Conversion Osaka 2003: pp [8] J.S. Swirhun R.A. Sinton M.K. Forsyth T. Mankad Contactless measurement of minority carrier lifetime in silicon ingots and bricks Progress in Photovoltaics: Research and Applications. 19 (2011) [9] M. Wilson P. Edelman J. Lagowski S. Olibet V. Mihailetchi Improved QSS-µPCD measurement with quality of decay control: Correlation with steady-state carrier lifetime Solar Energy Materials and Solar Cells. 106 (2012) [10] K. Dornich N. Schüler B. Berger J.R. Niklas Fast high resolution inline contactless electrical semiconductor characterization for photovoltaic applications by microwave detected photoconductivity Materials Science and Engineering: B. 178 (2013) [11] T. Trupke R.A. Bardos M.C. Schubert W. Warta Photoluminescence imaging of silicon wafers Applied Physics Letters. 89 (2006) [12] T. Fuyuki H. Kondo T. Yamazaki Y. Takahashi Y. Uraoka Photographic surveying of minority carrier diffusion length in polycrystalline silicon solar cells by electroluminescence Applied Physics Letters. 86 (2005) [13] P. Würfel T. Trupke T. Puzzer E. Schäffer W. Warta Diffusion lengths of silicon solar cells from luminescence images Journal of Applied Physics. 101 (2007) [14] J.A. Giesecke M. Kasemann M.C. Schubert P. Würfel W. Warta Separation of local bulk and surface recombination in crystalline silicon from luminescence reabsorption Progress in Photovoltaics: Research and Applications. 18 (2010) [15] B. Mitchell T. Trupke J.W. Weber J. Nyhus Bulk minority carrier lifetimes and doping of silicon bricks from photoluminescence intensity ratios Journal of Applied Physics. 109 (2011) [16] E. Olsen A.S. Flo Spectral and spatially resolved imaging of photoluminescence in multicrystalline silicon wafers Applied Physics Letters. 99 (2011) [17] S. Herlufsen K. Ramspeck D. Hinken A. Schmidt J. Müller K. Bothe et al. Dynamic photoluminescence lifetime imaging for the characterisation of silicon wafers Physica Status Solidi (RRL) - Rapid Research Letters. 5 (2011) [18] D. Kiliani G. Micard B. Steuer B. Raabe A. Herguth G. Hahn Minority charge carrier lifetime mapping of crystalline silicon wafers by time-resolved photoluminescence imaging Journal of Applied Physics. 110 (2011) [19] M.P. Peloso B. Hoex A.G. Aberle Polarization analysis of luminescence for the characterization of silicon wafer solar cells Applied Physics Letters. 98 (2011) [20] D. Hinken C. Schinke S. Herlufsen A. Schmidt K. Bothe R. Brendel Experimental setup for camera-based measurements of electrically and optically stimulated luminescence of silicon solar cells and wafers. The Review of Scientific Instruments. 82 (2011)
10 Solid State Phenomena Vols [21] T. Trupke J. Nyhus R.A. Sinton J.W. Weber Photoluminescence Imaging on Silicon Bricks in: Proceedings of the 24th European Photovoltaic Conference Hamburg [22] S. Bowden A. Sinton Determining lifetime in silicon blocks and wafers with accurate expressions for carrier density Journal of Applied Physics. 102 (2007) [23] B. Mitchell J.W. Weber D. Walter D. Macdonald T. Trupke On the method of photoluminescence spectral intensity ratio imaging of silicon bricks : advances and limitations Journal of Applied Physics. 112 (2012) [24] M.A. Green Analytical expressions for spectral composition of band photoluminescence from silicon wafers and bricks Applied Physics Letters. 99 (2011) [25] D. Walter A. Liu E. Franklin D. Macdonald B. Mitchell T. Trupke Contrast Enhancement of Luminescence Images via Point-Spread Deconvolution in: IEEE 38th Photovoltaic Specialists Conference [26] B. Mitchell J. Greulich T. Trupke Quantifying the effect of minority carrier diffusion and free carrier absorption on photoluminescence bulk lifetime imaging of silicon bricks Solar Energy Materials and Solar Cells. 107 (2012) [27] S. Johnston F. Yan M. Al-Jassim Quality Characterization of Silicon Bricks using Photoluminescence Imaging and Photoconductive Decay 38th IEEE Photovoltaic Specialists Conference. (2012) 2 6. [28] G. Zoth W. Bergholz A fast preparation-free method to detect iron in silicon Journal of Applied Physics. 67 (1990) [29] L. Kimerling Electronically controlled reactions of interstitial iron in silicon Physica B+ C. 116 (1983) [30] D. Macdonald J. Tan T. Trupke Imaging interstitial iron concentrations in boron-doped crystalline silicon using photoluminescence Journal of Applied Physics. 103 (2008). [31] B. Mitchell H. Wagner P.P. Altermatt T. Trupke Predicting Solar Cell Efficiencies from Bulk Lifetime Images of Multicrystalline Silicon Bricks in: Proceedings of the 3rd SiliconPV Conference Hamelin Germany [32] B. Mitchell M. Juhl M.A. Green T. Trupke Full Spectrum Photoluminescence Lifetime Analyses on Silicon Bricks IEEE Journal of Photovoltaics. (in press) (2013). [33] P. Würfel S. Finkbeiner E. Daub Generalized Planck s radiation law for luminescence via indirect transitions Applied Physics A: Materials Science & Processing. 60 (1995) [34] E. Daub P. Würfel Ultralow values of the absorption coefficient of Si obtained from luminescence Physical Review Letters. 74 (1995) [35] E. Daub P. Würfel Ultra-low values of the absorption coefficient for band band transitions in moderately doped Si obtained from luminescence Journal of Applied Physics. 80 (1996)
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