Category Advances in Photovoltaics:. Volume

Diffusion length and lifetime of charge carriers

Diffusion length and lifetime of charge carriers are crucial characteristics of crystalline silicon solar cell and their diagnostics (Bullis and Huff, 1995; Guirgis et al., 2009; Pavelka et al., 2007b; Schofthaler and Brendel, 1995; Sinton and Cuevas, 1996; Trupke et al., 2011). Therefore, standardized test methods of lifetime are applied also to specify polysilicon quality (SEMI AUX017, n. d.; SEMI MF1535, n. d.; SEMI MF28, n. d.; SEMI MF391, n. d.; SEMI PV13, n. d.; SEMI PV9, n. d.). However, excellent lifetime and diffusion length values of the feedstock are necessary but not sufficient essentials to high solar efficiency. Loss analyses proved that even perfect crystals can end up at the low end when the solar cell process functions suboptimally (Borchert and Rinio, 2009; Cousins et al...

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FBR granulate

Regarding its energy consumption, granulated silicon could be a promising solar feedstock (Hamilton and Rami, 2010). However, downstream processes react sensitively toward quality anomalies in silicon granules. Consequently, specific bulk analytical methods must be also applied to granule feedstock (Table 7.8; SEMI E46, n. d.).

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Dopant and carbon impurities

Beside dust and metallic impurities, dopants and carbon affect strongly the efficiency of silicon solar cells (Ceccaroli and Lohne, 2006). The substitu­tional carbon contamination can be determined in polysilicon samples (Hwang et al., 1991) and the resistivity of multicrystalline silicon can also be evaluated (Gosh et al., 1982; Seager, 1985; Tyagi and Sen, 1983).[10] However, most of the specified dopants and substitutional carbon are measured on monocrystalline silicon grown from polysilicon samples after FZ crystal growing (ASTM F574, n. d.; Bourbina et al., 1994; SEMI MF1708, n. d.; SEMI MF1723, n. d.; SEMI PV17-0611, n. d.)...

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Metallic impurities in and on polysilicon

Metallic impurities, particularly metallic impurities interacting with crystal defects detrimentally limit the lifetime of charge carriers in silicon solar cells (Breitenstein et al., 2010; Bronsveld et al., 2010; Buonassisi et al., 2005; Ceccaroli and Lohne, 2006; Hashim et al., 2007; Kwapil et al., 2009; Seibt et al., 2009b; Seifert et al., 2009). For metallic contamination, the instrumental neutron activation analysis (INAA) provides a very reliable, however, tedious, method, metal results can be expected with detection limits down to 10_ 16g/g silicon (Huber et al., 1993; Verheijke, 1992). After optimized preparation and g-spectrometry, SEMI PV10 describes the INAA procedure for analytes with atomic numbers beyond silicon (SEMI PV10-1110, n. d.)...

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Particulate contamination on polysilicon feedstock

Analyses of weakly adhered surface contamination and bulk impurities can be applied to polysilicon without phase transition. Testing for particles and dust is particularly important for polysilicon granules (CroBmann and Derzmann, 2006; Ginafranco, 2002; Hashim et al., 2007; Kenji et al., 2005).

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Instrumental analytical methods for polysilicon feedstock

Dimensional, morphological, electrical, and chemical data characterize SG-Si feedstock. Direct measurements and analyses can be applied to as – grown polysilicon, indirect measurements, and analysis require monocrys­talline or dissolved specimens (Table 7.8)

Evaluation technique


Measurement or analytical Method




Direct measurement on as-grown polysilicon


Multifunctional image processing



Surface properties SEM


Direct instrumental analysis on as-grown polysilicon

Si nanostructure




Strain gauge

Dangling bond Si—H bond Crystallinity Residual stress



Gas inclusions Adsorbed gas

SEMI E46 (n. d.); SEMI E108 (n. d.)



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Online process control of the gas phase

Due to the presence of hydrogen chloride, chlorosilanes, metallic and non­metallic chlorides, the atmosphere is corrosive in the silane-route processes. Corrosion and precise analytical control are controversial conditions of process control. Controlling the gaseous components of polysilicon subpro­cesses by process gas chromatography (PGC; Sanji and Toshiyuki, 1988; Tadashi and Tatsuya, 1995; Tellenbach, 2010; Vorotyntsev et al., 2003; Yuji and Osamu, 2000) and FTIR or Raman spectroscopy (Cowles and Kray, 1985; SEMI E46, n. d.) is still feasible. Metallic contamination in the chlorosilane fractions can be analyzed after separating the gaseous components (Cowles and Kray, 1985; Mcremott et al., 2007; Puehl et al., 2010).

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In Section 5.1, we listed relevant properties of polysilicon which affect the performance of solar PV applications and HVM cell processing. SEMI PV17 provides a specification for four different categories of polysilicon feedstock[9] with a list of standardized or generally practiced analytical methods (SEMI PV17-0611, n. d.). The performance of solar cells is limited by the impurities in SG-Si, therefore sensitive trace-analytical methods are applied for controlling the purity of polysilicon (Pizzini et al., 1986). Here we provide an overview ofthe most important analytical methods as applied to process and product control.

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