science lifetime 2

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Solar Energy Materials & Solar Cells 0 (2002) ]]]]]]

Defect and impurity diagnostics and process

monitoring

Wilhelm Warta*

Fraunhofer Institute for Solar Energy Systems (ISE), Oltmannsstr. 5, 79100 Freiburg, Germany

Abstract

The review focuses on four areas of defect and impurity diagnostics: (i) the determination of

parasitic resistances, (ii) quantum efficiency analysis including light-beam-induced current

measurement systems which use spectrally resolved currents to determine local recombination

in solar cells, (iii) methods to determine the recombination properties in solar cell precursors

and (iv) techniques suitable for the recognition of the type of impurity or defect, which is

responsible for increased recombination. In general, emphasis on those methods, which are

capable of delivering spatially resolved information. The use of the specific metastability

features of a defect for its identification is exemplified. In addition, carrier lifetime

spectroscopy methods utilising the temperature or the injection dependence of defect

recombination are outlined.r 2002 Published by Elsevier Science B.V.

Keywords: Silicon solar cells; Defects; Impurities; Process monitoring; Carrier lifetime

1. Introduction

Process monitoring for the recognition of defects and impurities in silicon solar

cells is beneficial in several aspects: The main and immediate use is the detection of

the origin of failures or faults in the cells. The knowledge of the factors limiting the

performance of a production solar cell is, on the one hand, also the basis for

improvements in the present processing scheme and for the design of new cell

technologies. Design of future high throughput process lines will rely more and more

on the detailed knowledge gained in the analysis of actually manufactured cells.

Presently silicon solar cell production process monitoring is mainly restricted to

optical inspections and IV performance tests on the final cells. Frequently used tests

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3B2v7:51cGML4:3:1 SOLMAT : 2486

Prod:Type:com

pp:1213col:fig::NILED:Ravi=BG

PAGN: indira SCAN: Bindu

*Tel.: +49-761-4588-192; fax: +49-761-4588-250.

E-mail address: [email protected] (W. Warta).

0927-0248/02/$ - see front matter r 2002 Published by Elsevier Science B.V.

PII: S 0 9 2 7 - 0 2 4 8 ( 0 1 ) 0 0 1 8 7 - 8


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are off-line measurements of emitter sheet resistance, and technological parameters

like metal thickness and optical inspection of AR coatings. Recombination, i.e.

carrier lifetime monitoring is not yet used widely, partly because of uncertainty

concerning the relevance of the measured numbers for the final cell. Here, oneimportant step forward may come with the application of quasi-steady-state

techniques for in-line monitoring. These techniques are summarised in a recent

review [1] and will be mentioned only briefly.

The inclution of spatially resolved data in comprehensive performance and

technology monitoring and modelling is a rewarding future field, since the potential

value for the detection of failure origins is high. Emphasis is, therefore, on those

methods, which are capable of delivering spatially resolved information.

Defects and impurities are taken into account, which may be originating from

the starting material or could be introduced by the solar cell process and include

also defective emitter, space charge region, passivation layers or metallisation.

In the first part, an overview will be given of methods to determine and image

parasitic resistance losses. In the second part, quantum efficiency (QE) analysis is

addressed. Also, light-beam-induced current (LBIC) techniques which include a

certain degree of spectral analysis are reported. The third part reviews methods for

determining recombination properties in starting wafers and solar cell precursors.

Emphasis is on new achievements like the imaging of the carrier density by infrared

transmission. The fourth part then focuses on methods to recognise the type of

impurity responsible for increased recombination. The use of the fingerprints of

metastable defects and recently investigated carrier lifetime spectroscopy methodsare presented.

2. Determination of parasitic resistance in solar cells

Reduced fill-factors as revealed by illuminated IV measurements are usually

attributed to parasitic resistance-like series or contact resistance due to insufficient

metallisation or excessive emitter sheet resistance or parallel (shunt) resistance losses.

This is a common, but not the only origin: Fill-factor losses may also arise from

injection-dependent recombination processes, which lead from a decreased excesscarrier density at lower forward voltage to an increased recombinative dark current.

This was demonstrated for the strongly injection-dependent surface-recombination

velocity at the oxide-passivated rear surface of PERC cells [2] and for injection

dependent volume lifetimes in mc-silicon [3].

The global shunt resistance as well as the dark series resistance may be deduced

from a fit to the dark IV curve. The lighted Rs; which is the relevant value foroperating conditions, may differ from the dark one due to the different current paths

for injection at the junction for dark forward bias compared to the collection of the

light-generated current in the illuminated case [4]. Lighted Rs is accessible from the

irradiation dependence of Jsc and Voc (JscVoc curves, see e.g. [5]) and from thedifference between the illuminated IV-curve and the illuminationVoc curve [6]:

An IV curve without series resistance loss may be obtained even before front

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W. Warta / Solar Energy Materials & Solar Cells 0 (2002) ]]]]]]2

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metallisation by probing the n+ layer, measuring the irradiance-dependent Voc and

constructing an IV curve by application of the superposition principle.

A newly developed commercially available instrument allows measurements of the

local contact resistance, i.e., problems in contact formation on a finished solar cell.The cell surface is scanned with a probe tip under illumination and the local potential

drop is monitored [7]. Recently, contactless thermography for monitoring defects in

solar cells [8] has been brought forward, closer, to the step from research to

application level. The decisive advance consisted of the pulsed application of a

forward bias and the use of lock-in technique for the detection of the heat dissipated

in shunted areas. This boosted the sensitivity to better than 10mK. Lock-in

thermography may be applied for the localisation of dominating shunts or the

characterisation of shunt distributions. The correlation with production peculiarities

like the edge treatment, wafer handling or printing defects often directly point at the

origin of the problem. A quantitative evaluation of the relevance of the observed

resistive loss patterns for the total performance of the solar cell is presently not

available.

Four-point probe resistivity mapping is important for the qualification of starting

material, the detection of faults in the dopant distribution, as well as for the

monitoring of homogeneity and reproducibility of n+ or p+ diffusions. Stepping

systems are available as commercial equipment; high-resolution apparatus applying

sophisticated evaluation techniques in order to identify grain boundary effects have

been developed [9]. Progress towards fast measurement speed with coarse spatial

resolution has recently been made at Fraunhofer ISE with a system, which does notprobe step by step, but instead uses an array of 100 4 needles to contact 100

measurement points on a 15 15cm2 area in one step. Individual measurements are

taken using a relay box. The present set-up reduces the measurement time by about a

factor of 8 compared to commercial equipment; further improvements by applying

e.g. electronic switching are straightforward.

3. Quantum efficiency (QE) analysis and spectrally resolved LBIC

QE analysis is a powerful tool, which gives local information about the emitter inthe short wavelength, bulk lifetime, rear surface recombination and light trapping in

the long wavelength region. The possibility to measure currents with high local

resolution allows to attribute reduced performance to defective cell regions.

Crucial for the current modelling, which is necessary for the extraction of cell

parameters, is the optical cell model. Accurate ray tracing approaches are available

[1012], but they are usually too time-consuming for direct application in QE

evaluation used for process monitoring. For a specific manufacturing line, it might,

however, be beneficial to establish a series of standard generation profiles calculated

once using ray tracing. A simplified analytical approach including surface texture

and wavelength-independent reflection coefficients and angles for the front and rearinternal reflectivity was established and analysed in detail by Basore [13]. For

analytical electrical modelling of the internal quantum efficiency (IQE) Basore [13]

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also introduced a convenient scheme: Linear approximations of the inverse IQE

versus light penetration depth were derived for the wavelength range in which no

appreciable fraction of the incident light reaches the rear surface (characterised by

the effective diffusion length Leff), and for the long wavelength range, where lighttrapping fully equalises the generation distribution (characterised by the collection

length Lc). By condensing the optical model to the rear surface reflectivity Rb as the

main decisive parameter, an evaluation of these two linear regimes allows the

determination of base diffusion length Lb; rear surface recombination velocity Sband the optical rear reflectivity Rb: The limits imposed by the significance of theinfluence of the parameters on the measured IQE are also discussed. For this control,

a confidence plot in the Lb; Sb-plane was found to be very useful [14]. Withreduced cell thickness, improved material and improved rear surface passivation

quality production cells come closer to the limits of Basores analytical approach.

This was recently noted by Spiegel et al. [15], who proposed to extend the linear Leff-

approximation allowing curvature of IQE1(a1) by introducing Sb as a second

parameter. Provided a sufficiently high measurement accuracy can be realised,

separation of base and rear surface recombination may be deduced from the degree

of curvature. The extended approximation is especially interesting for fast (e.g.

LBIC) applications.

The next degree of approximation is the fit with a numerical electrical model, e.g.

PC1D [16]. Thus, the full information contained in the IQE-curve is utilised. The

generation function may either be taken from the optical model integrated in PC1D or

provided externally e.g. from a ray tracing simulation. It is important to note that thepossible range of the fit parameters, i.e., the sensitivity, must be checked by comparing

the effect of a variation in the respective parameter to the measurement error.

Quite often, the shape of the IQE-curve already gives a clear indication of the

dominating mechanism. For the reduced QE on a thin PERC cell with rear

passivation processed on a caustic etched surface (within the THIMOCE project),

this is demonstrated in Fig. 1. In contrast to the assumption of a well-passivated rear

surface with bad optical reflection (left), the case, Fig. 1 (right), where increased

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400 600 800 1000 12000.0

0.2

0.4

0.6

0.8

1.0

Rrear[%]

97

90

70

30

0

measured:

NaOH etched rear

IQE

Wavelength (nm)

400 600 800 1000 12000.0

0.2

0.4

0.6

0.8

1.0

Sback [cm/s]

100

1000

3500

1e6

measured

NaOH etched rear

IQE

Wavelength (nm)(b)(a)

Fig. 1. Comparison of a measured QE curve (symbols) to PC1D simulations assuming (left) reduced light

trapping (parameter internal reflectivity of rear surface Rrear) or (right) increased rear surface

recombination velocity Sback:


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surface recombination velocity and very high internal reflectivity is assumed, is

clearly the appropriate one.

Special care must be taken, when attempting a QE analysis for a cell with strongly

injection-dependent recombination properties. Since the measurement is usuallydone with chopped low-intensity monochromatic light and the injection density is

adjusted by additional white bias light (small signal measurement), a differential

QE is obtained [17,18]. Depending on the degree of the non-linearity of the

recombination, for an accurate analysis, the actual QE must be obtained by

measuring and integrating the full bias-light dependence. Since this is, in general,

impractical for process diagnostics, often a good approximation for the 1-sun

behaviour of the cell is a QE measurement taken with reduced bias intensity of e.g.

700 W/m2. As an example for the strong impact of non-linear rear surface

recombination on the result of QE measurements in Fig. 2, two measured spectral

response (SR) curves (Fig. 2, left) for illumination with two different bias light

spectra (Fig. 2, right) are shown. Although, in both cases, the bias light is adjusted to

give the same current, the increased carrier density due to the shift of the generation

profile into the depth of the cell reduces rear surface recombination and results in a

strongly increased spectral response.

Light-beam-induced current (LBIC) measurements allow high spatial resolution in

the tenth of mm range. Several differently focussed laboratory set-ups have been

developed. At the University of Marseilles [19], the full spectral capability was

integrated into an LBIC system by using a monochromator. The additional

availability of measurements at low temperature makes this a very versatile tool fordefect recognition on the research lab level. Apparatus which includes illumination

at several wavelengths using laser diodes have been established at TUBA Freiberg

[20] and the University of Konstanz [21]. The Spectrally Resolved (SR) LBIC system

developed at Fraunhofer ISE [22] is specially tuned to fast measurement speed. The

system uses at present 5 different wavelengths in the regime, where the quantum

efficiency is sensitive to base recombination. High measurement speed is achieved by

sine-modulating the five laser diodes with different frequencies, retrieving one

superimposed signal for short circuit current, reflectivity as well as light intensity and

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300 400 500 600 700 800 900 1000 1100 12000.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

wavelength [nm] wavelength [nm]

diff.spectralresponse[A/W]

bias R3, jbias

= 43.5 mA/cm2

bias B, jbias

= 43.5 mA/cm2

300 400 500 600 700 800 900 1000 1100 12000

400

800

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2400

2800

3200

spectralirradiance[W/(m

2m)]

AM 1.5 global

bias spectrum R2

bias spectrum B

(b)(a)

Fig. 2. Measured SR for an RP-PERC cell (left) illuminated with two different bias light spectra (right);

the bias spectrum R3 used for the SR-measurement differs from R2 only by minor details.


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decomposing it to the contribution generated by the respective wavelength by digital

filtering. In addition, the measurement is not done step by step, but while the light

spot is continuously travelling across the cell.

4. Contactless methods for measuring recombination properties

In this section, a brief review of available contactless methods to measure

recombination properties will be given, followed by two more recent applications.

The determination of local diffusion lengths by the surface photo-voltage (SPV)

technique is available commercially as a mapping instrument [23]. A Fe test modus

using the metastability of the FeB pair was integrated (see Section 5), a feature which

was extensively used for process monitoring.

In the quasi-steady-state photo-conductivity (QSSPC) method [24] the recombina-

tion properties are determined from the excess carrier density following quasi-

statically the generation light of a flash. The method is fast and thus has a high

potential for process monitoring. For a review of the application to process

monitoring, the reader is referred to Ref. [1]. The special strength of the method lies

in the easy access to the full injection dependence of the carrier lifetime. This is used

in the IDLS technique for injection-dependent lifetime spectroscopy (see Section 5).

The determination of emitter recombination is discussed in Ref. [25]. Usually, at low

injection densities, trapping effects dominate the results. An analysis of this part of

the QSSPC curve, which allows to determine the trapping features of defects, wasgiven in Ref. [26]. The introduction of spectrally confined illumination allows, in

principle, the separation of volume and surface [27] or emitter effects [28]. Due to the

measurement of the photoconductivity with an inductive coil, the spatial resolution

is presently limited to several cm2.

In small-signal-measurement techniques, either the decay of the additional excess

carrier density generated by a light pulse [29] or the phase shift of the carrier

response to a sine-modulated generation [30] is used to determine the carrier lifetime.

The injection level is fixed by additional bias light. In contrast to QSSPC, for

injection-dependent recombination processes, differential results are obtained. On

the other hand, small signal techniques use averaging methods and are thus able tohandle the low-signal amplitudes from the small detection volumes necessary for

high spatial resolution. The microwave-detected photoconductivity decay (MW-

PCD) method is available as well-developed commercial instrumentation. Optical

detection, on the other hand, as used in the modulated free carrier absorption

(MFCA) technique [30] allows a wider application range. This holds true also for the

latest version of free carrier absorption techniques discussed in Section 4.2, which

uses an IR camera.

4.1. Carrier lifetime measurements on a highly doped material

It is well known that standard microwave PCD equipment becomes insensitive for

highly doped material. In the MFCA technique, the excess carriers are detected

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optically by the attenuation of an IR probe beam. It was found that this technique is

well suited for carrier lifetime measurements in a range, which is not accessible by

other methods. Fig. 3 gives examples of MFCA carrier lifetime maps on 0.15O cm

wafers from upgraded metallurgical (UMG) silicon.

The material quality is strongly increased by the purification step from carrier

lifetimes below 0.3 ms to about 1.5 ms. The higher impurity content of the unpurified

material is also indicated by the impurity segregation effects around the grain

boundaries observed, on the left, in Fig. 3.

4.2. Infrared carrier density imaging

A new branch of applications of IR absorption on free carriers uses an IR

camera to obtain an image in one step instead of the scanning mode applied

in the MFCA measurements. An IR camera technique was presented first by Bail

et al. [31]. We have recently developed an improved version of this Infrared

lifetime mapping (ILM) technique. Infrared light radiated from a black body at a

specified temperature is transmitted through the wafer. In the present set-up,

a chopped generation laser (l 915 nm) excites minority carriers in the sample.The local attenuation of the transmitted IR light is proportional to the local

free carrier density. Using a CCD-camera, sensitive in the mid-infrared, an image

of the sample is taken with and without excitation light illumination. The difference

between both images represents the spatial carrier density distribution. With

known generation light intensity, local parameters such as bulk lifetime can be

calculated.

The main innovative feature in the method developed at Fraunhofer ISE is the

lock-in thermography approach. The excitation light is chopped with a frequency

between 1 and 20 Hz such that for one half of every period, free carriers are excited in

steady-state condition. The camera images are continuously read out and weightedwith a set of correlation functions synchronised to the excitation light. By increasing

the number of evaluated periods, this lock-in technique reduces the noise and

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Fig. 3. MFCA lifetime maps of wafers from UMG silicon prior to (left) and after (right) an additional

plasma purification step.


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increases the sensitivity of our method significantly. Thus, it is possible to measure

the typical lifetime range relevant for industrial solar cell material. The optical

spatial resolution of the lifetime map depends only on the chosen optical lens system

and the CCD-array, and not on the total measurement time.

Fig. 4 (left) shows a lifetime map based on the carrier density image of a region ofa block cast multicrystalline silicon wafer with silicon nitride surface passivation

(excitation wavelength 990 nm), in comparison to an MW-PCD map (right). The

spatial resolution is 110mm. The structures observed in the IR image after just 1 min

measurement time are excellent. The carrier density measurement by lock-in

thermography allows to obtain a lifetime map in steady-state condition with

288 288 data points in 1 min. This corresponds to a measurement time of 0.7 ms

per point compared to measurement times of about 0.1 s per point in standard

scanning methods.

5. Defect recognition

For the identification of structural defects, various methods based on metallo-

graphical techniques, optical or electron microscopy are available. Dislocation (etch

pit density) maps, for which commercially available equipment was developed in the

recent years are of interest in process monitoring. An important tool for the

assessment of the electrical activity is the electron beam-induced current (EBIC)

contrast. A good starting point may be found in a recent paper presenting a

comprehensive model for the EBIC contrast of decorated dislocations (temperature

and injection dependence) [32].For the recognition of impurities, the classical elemental analysis (e.g. chemical

analysis, mass spectroscopy, etc.) is usually limited to concentrations above 1014

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Fig. 4. Carrier lifetime obtained with the improved ILM technique (left) in comparison to an MW-PCD

lifetime map (right).


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1015 cm3. Lower concentrations are accessible with the well-known deep level

transient spectroscopy (DLTS), which determines the defect parameters from the

capacitance spectroscopy of the carrier reemitted from the defect. We will

concentrate, in the next paragraph, on three techniques which use a carrier lifetimemeasurement and thus, directly look at those defects which are active in

recombination: Defect recognition by metastability and carrier lifetime spectroscopy

by IDLS and TDLS.

5.1. Defect recognition using metastability

The metastability of defects like the well-characterised pairs of transition metals

with boron [23] or the Cz-specific defect [33] open up the opportunity to use the

typical metastable behaviour for impurity identification. The Cz-specific defect (mostlikely a complex involving boron and oxygen) is chosen as the first example.

Comparing details of the behaviour of an unknown defect to the phenomenology of

the Cz-specific defect is a valuable identification tool. In recent work on highly doped

multicrystalline silicon, a metastability of the solar cell performance had been

observed [34]. This metastability was further characterised at Fraunhofer ISE in the

frame of the ARTIST project. Among other properties the reformation of the

recombination active state of the defect under illumination was investigated. For the

Cz-specific defect, for this process, a recombination-enhanced defect reaction was

proven [33]. The transformation from the passive to the active state is induced by the

(weak) recombination at the passive state and followed by an exponential law withthe defect generation time tgen as time constant. A plot of the defect generation rates

1=tgen observed for differently doped Cz material versus doping concentrationfollows a linear dependence in a loglog plot (Fig. 5).

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1015

1016

1017

10-6

10-5

10-4

10-3

10-2

Measured Cz

Fit

Measured ARTIST material

DefectGenerationRate

1/gen

[s-1]

Doping Concentration [cm-3

]

Fig. 5. Dependence of the defect generation rate for the Cz-specific defect on doping concentration. The

value for the unknown defect found in highly doped mc-silicon is included.


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By determining tgen for the highly doped mc-silicon and including it into this

dependence (Fig. 5, star symbol), the excellent compatibility becomes a strong case

for the unknown defect to be identical to the Cz-specific defect.

As a second example, the observation of a strong change of carrier lifetime in the

bottom part of directionally solidified silicon is presented. When measured at low

injection density the lifetime decreases, while for high injection density it increases by

illumination (Fig. 6, left).

Since the change recovers completely during storage at room temperature, anexplanation based exclusively on the Cz-specific defect is clearly excluded, since the

latter is stable in the active state at low temperature. On the other hand, the low

injection lifetime is observed to recover from the degraded state by an annealing

treatment at 2001C and fast cooling. This is not compatible with the FeB pair, which

should be dissociated by the anneal (just like light soaking), while the resulting Fe ishould have the higher recombination activity at low injection. This example

illustrates how the metastability can be used to exclude certain defects. In this case,

the identification of the nature of the defect is left for future work.

5.2. Temperature-dependent lifetime spectroscopy (TDLS)

Injection-dependent lifetime spectroscopy (IDLS) appears thanks to the simple

quasi-steady-state measurement which is quite interesting in process monitoring.

Nevertheless, we will first discuss the experimentally more demanding TDLS

technique, since IDLS is shown later to have quite stringent restrictions. Describing

recombination via a discrete energy level in the upper half of the band gap at a depth

Et below the conduction band edge by the well accepted SRH (Shockley Read Hall)

statistics, we obtain for the temperature dependent excess carrier lifetime at low level

injection, tSRHLLI [35]

lnt

LLISRHT>

T>

const

EC Et

kT>

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0 100 200

2

4

6

8

10

12

14

16before light soakingafter light soaking

laser intensity [1012 photons/cm2]

0 50 100 150 200 250 300 3504.0

4.5

5.0

5.5

6.0

Low injection

+ 10 hourlight soakingAnneal at 200

Lifetime[

s]

Lifetime[

s]

Time [min]

Fig. 6. Degradation and annealing behaviour (left) and injection dependence (right) of the metastable

defect observed in the bottom of an mc-silicon block before and after light soaking.


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above a temperature T>: An example for an Arrhenius plot of tLLISRH=T for

intentionally Molybdenum contaminated p-Si with two different doping concentra-

tions is given in Fig. 7.

The energy level is determined with high accuracy, the expected dopingdependence is experimentally verified.

5.3. Injection-dependent lifetime spectroscopy (IDLS)

Since with the QSSPC technique the injection dependence of the carrier lifetime is

accessible readily, the possibility to use this information for defect recognition has

found increasing interest [36]. In Fig. 8, an example is given, where the SRH

recombination model was fit to a measured injection dependence for a Mo-

contaminated sample characterised with TDLS (see Section 5.2). With the energy

level (DE1 0:330 eV) obtained from TDLS, a good fit is only obtained, if anadditional level at DE2 0:247 eV is assumed. What is even more important is thefact that fitting curves may be obtained for a wide range of parameters

(DE1 0:25y0.55 eV, DE2 0:17:..0.25 eV). The method is able to deliverconclusive results only if it is possible to investigate the defect in several differently

doped wafers. This was used for determining the energy level of the active species of

the Cz-defect [36].

6. Summary

In the present overview, a wide range of techniques were presented, which are

partly already available and partly under development at the research lab level.

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2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.010-3

10-2

10-1

ETDLS

= 0.329 +/- 0.003 eV

EDLTS

= 0.34 eV (literature)

NA= 9.9. .1014cm-3, [Mo]=3.71012cm-3

NA

= 1.7.1015

cm-3, [Mo]=1.1.10

12cm

-3

eff

low/

(T.

eff,

300K

low)[1/K]

1000/T [1/K]

250C

200C

150C

100C

50C

0C

-50C

C

-100

ETDLS

= 0.332 +/- 0.003 eV

Fig. 7. TDLS measurements on intentionally Mo-contaminated p-type silicon.


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OOFTools for the characterisation of spatially distributed parasitic resistances are alreadyavailable as first commercial versions. On the basis of the quasi-steady-state

technique, a variety of new applications have been introduced. QE analysis is a

mature technique, which is being transferred in part to LBIC tools. With infrared

absorption techniques new promising instruments for fast steady-state carrier

lifetime maps are under development. Several tools based on lifetime measurements

(metastability analysis, carrier lifetime spectroscopy) are well-suited to identifyspecific defects. In any case, the main challenge will be the transfer of these methods

to a widespread application in industrial solar cell production.

References

[1] R.A. Sinton, Proceedings of the Ninth Workshop on Crystalline Silicon Solar Cells and Materials,

NREL/BK-52026941, 1999.

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Glasgow, 2000, p. 1438.

[8] M. Langenkamp, O. Breitenstein, M.E. Nell, A. Braun, H.G. Wagemann, L. Elstner, Proceedings of

the 16th EU-PVSEC, Glasgow, 2000, p. 1643.

[9] W. Koch, W. Krumbe, I.A. Schwirtlich, Proceedings of the 11th EU-PVSEC, Montreux, 1992, p. 518.

[10] R. Brendel, Proceedings of the 14th EU-PVSEC, Amsterdam, 1994, p. 1339.

[11] J.O. Schumacher, S. Sterk, B. Wagner, W. Warta, Proceedings of the 13th EU-PVSEC, Nice, 1995,

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[12] C. Zechner, P. Fath, G. Willeke, E. Bucher, Sol. Energy Mater. Sol. Cells 51 (1998) 255267.

[13] P.A. Basore, Proceedings of the 23rd IEEE PVSC, Louisville, 1993, p. 147.

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Mo-contaminated

p-type Cz-Si

eff

SRH

SRH,1

SRH,2

Lifetime[s]

Injection Density [cm-3]

Fig. 8. Fit of an SRH recombination model to a measured injection dependence of the carrier lifetime.


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[14] R. Brendel, M. Hirsch, R. Plieninger, J.H. Werner, IEEE Trans. ED 43 (1996) 1104.

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[26] D. Macdonald, A. Cuevas, Appl. Phys. Lett. 74 (1999) 1710.[27] M. Bail, R. Brendel, Proceedings of the 16th EU-PVSEC, Glasgow, 2000, p. 98.

[28] A. Cuevas, M. Kerr, D. Macdonald, R.A. Sinton, Proceedings of the 26th IEEE PVSC, Anchorage,

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