Phys. Status Solidi A, 1–8 (2011) / DOI 10.1002/pssa.201083994 p s sa

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Contactless electrical defectcharacterization in semiconductorsby microwave detected photo inducedcurrent transient spectroscopy (MD-PICTS)and microwave detected photoconductivity (MDP)

Bastian Berger1, Nadine Schuler2, Sabrina Anger2, Bianca Grundig-Wendrock3, Jurgen R. Niklas2,and Kay Dornich*,2

applications and materials sciencewww.pss-a.comp

1 Institute of Theoretical Physics, TU Bergakademie Freiberg, Leipziger Straße, 09596 Freiberg, Germany2 Freiberg Instruments GmbH, Am St. Niclas Schacht 13, 09599 Freiberg, Germany3 SolarWorld Innovations GmbH, Berthelsdorfer Straße 111a, 09599 Freiberg, Germany

Received 5 July 2010, revised 24 August 2010, accepted 21 December 2010

Published online 00 Month 2011

Keywords defects, electrical characterization, lifetime, MDP

* Corresponding author: e-mail dornich@freiberginstruments.com, Phone: þ49 3731 41 95 410, Fax: þ49 3731 41 95 414

The contactless electrical characterization techniques MDP and

MD-PICTS will be presented in this paper. Both methods are

predestined for defect investigation in a variety of semi-

conductors. Due to a so far not reached sensitivity, major

advantages of MDP are its high spatial resolution and its

measurement speed, which allows for two dimensional inline

measurements at production speed. Furthermore a versatile

numerical tool for simulations of electrical properties of a

semiconductor as a function of defect parameters was

developed. MD-PICTS is a contactless temperature dependent

measurement which allows the determination of activation

energies of trap levels in the material. To demonstrate the

abilities of both methods, measurements conducted at different

semiconductor materials, e.g. silicon, silicon carbide, gallium

arsenide and indium phosphide, will be presented exemplarily.

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1 Introduction and motivation In photovoltaic aswell as in microelectronic industry the goal is to drive costsdown by bringing yields up at the same time. To reach thisgoal it is important to analyze the defects existing in the usedsemiconductor materials and their impact on the latter deviceperformance. Therefore the two contactless electricalcharacterization methods MDP and MD-PICTS for defectinvestigation are presented and results at different semi-conductor materials are reviewed.

Due to the advanced microwave detection techniqueboth methods have an advantage of sensitivity. As aconsequence a high measurement speed is enabled.Mapping of 156 mm mc-Si wafer takes under a second [1].The wide measurable injection range from 1010 to 1017 cm�3

is another benefit. Extraction of several defect parameterslike the activation energy of the main recombination centerfrom injection dependent investigations is possible. The high

sensitivity is also used for measurements on lowerqualitative materials or thin epitaxial layers on varioussubstrates [2]. Using the varying penetration depth of lightfrom different wavelength reveals even information aboutinterface defects.

As one example the influence of metal contaminations asiron and chromium in silicon, diffusing into the materialduring the melting process and reducing the efficiency ofsolar cells and causing breakdowns of devices, is widelydiscussed in literature [3], as well as lifetime degradationcaused by BO2 [4]. MDP is a suitable tool for high resolutionmappings of the density of iron as well as chromium andboron–oxygen complexes. Furthermore due to high sensi-tivity and steady state measurements iron mapping inmulticrystalline silicon bricks is even possible as inlinemeasurement, revealing the concentration of all electricallyactive Fe.

� 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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MD-PICTS is an advancement of conventional photoinduced current transient spectroscopy (PICTS) without thenecessity of contacting the samples and with a highersensitivity, opening new fields of applications on a variety ofsemiconductors revealing so far not accessible defectinformation. The technique is sensitive to defects acting ascarrier traps while the DLTS method gives more informationabout the dominating recombination center in the material.

To achieve a better understanding of measured results aversatile numerical simulation tool was developed. It strictlystarts from first principles rather than relying, e.g. on SRHformalism and similar approximations. Application of thistool makes it possible to determine the impact of certaindefect properties on important material parameters asminority carrier lifetime, photoconductivity or diffusionlength. Thus it is used to simulate MD-PICTS and MDPmeasurements by taking different defects into account.

2 Experimental details2.1 Microwave detected photoconductivity The

novel method MDP is well suited for both, defectinvestigation by, e.g. injection dependent minority carrierlifetime measurements, as well as mapping of wafers or evenbricks for inline metrology. Its major advantage is thecombination of sensitivity, resolution and speed, givingMDP the flexibility for a wide variety of differentapplications.

The photoconductivity, which is closely related to thediffusion length, is measured by microwave absorption in aresonant microwave cavity, during and after the excitationwith a rectangular laser pulse. Figure 1 shows the layout ofthe MDP and MD-PICTS measurement setup. The sample issituated just outside the microwave cavity and is part of themeasurement system. Thus, the complex dielectric constantof the sample influences the resonant frequency and the lossproperties of the cavity. The microwave absorption by excesscharge carriers is detected. The sample is placed on an x–y

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Figure 1 (online color at: www.pss-a.com) Scheme of MDPmeasurement setup.

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table, allowing theoretically every sample size and to movethe sample in the x–y plane.

The high detection sensitivity enabled by this techniqueallows for injection dependent measurement over more thaneight orders of magnitude depending on material underinvestigation with unlimited duration facilitating exper-iments in a non-equilibrium or steady state regime. Anothermajor advantage of MDP is the ability to measurephotoconductivity and minority carrier lifetime simul-taneously. The minority carrier lifetime t can be extractedfrom the semi logarithmic decay and the photoconductivityequals the signal height at steady state. Accordingly a varietyof information can be gained from each measurement, likediffusion length, mobility, and even trapping dynamics.

2.2 Microwave detected photo induced currenttransient spectroscopy For defect investigation onsemiconductors deep level transient spectroscopy (DLTS)[5] and the photo induced current transient spectroscopy(PICTS) [6] are established techniques for more than20 years. Both differ in their excitation mechanism anddetection. While DLTS uses capacitive determination ofexcite charge reversal of defects caused by voltage pulses,PICTS measures the photoconductivity due to localirradiation with laser light. Therefore contacting of samplesis required for both methods. Microwave detected PICTS isan advancement of the conventional method, workingcontactless and therefore non-destructive.

To measure temperature dependent MD-PICTS, theMDP equipment shown in Fig. 1 is applied, with anadditional cryostat for the sample. The setup allows forspatially resolved measurements.

The method [7, 8] is based on the non-destructiveinvestigation of photoconductivity signals by microwaveabsorption. Through pulsed light excitation provided bya laser excess carriers are generated in the material.According to intended investigation, wavelengths fromUV- until the IR-range are applied, allowing for depthprofiling as well as defect specific excitation with sub-band-gap wavelength. The light excitation causes a local rise ofconductivity to a level dependent on the generation andrecombination processes as well as on trapping andreemission dynamics (time interval 1 in Fig. 2). After thelaser pulse is turned off the signal decreases rapidly causedby the fast recombination of the generated excess carriers(time interval 2). The slope of the so-called transient dependson the recombination rate. This initial fast decay is followedby a slower decreasing part due to the reemission oftrapped carriers into the associated band (time interval 3).Appropriate analysis leads to the extraction of defectparameters, e.g. the activation energy. After the photoexcita-tion, recombination and trapping of charge carriers thetypical photoconductivity transient based on the thermalexcited emission follows:

DsTransient ¼ qmDn ¼ qmnT0tn � e�etnT

t; (1)

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Figure 2 (online color at: www.pss-a.com) Physical processes andtheir corresponding signal parts in MD-PICTS: (1) generation andtrapping of carriers, (2) fast recombination process, (3) thermalreemission of trapped carriers [8].

nT0corresponds to the initial density of carriers trapped by a

distinct defect, etnT symbolizes the thermal excited emissionrate of this trap and t is the time after the termination of thephoto pulse. From etnT the activation energy of a trap can becalculated using the relation

www

etnT ¼ AT2 � e�EAkT ; (2)

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where A is a material constant.For analysis the so-called two-gate technique according

to DLTS is used leading to a similar defect spectra. MD-PICTS can be applied from semi-insulating samples toconductive ones. This opens characterization possibilitieseven on silicon which has not been possible with conven-tional PICTS. With the used cooling system the temperaturerange for MD- PICTS measurements is 80 to 500 K. Coolingdown to 4 K is possible, but investigations suggest that liquidnitrogen temperature is sufficient for most defects. Thefilling pulse differs depending on the sample’s propertiesbetween 10 and 1000ms.

2.3 Materials and samples To show the potential ofthe contactless electrical characterization methods MDP andMD-PICTS, results from analysis of several semiconductormaterials will be reviewed.

Shown MDP measurements for defect investigation areon passivated mc- and Cz-Si samples. For defect investi-gation by MDP-PICTS following samples were available:high quality 6 inch electronic grade p-doped mono-crystal-line silicon with a specific resistivity around 12V cm;solar grade multi-crystalline p-type silicon from differentparts of a brick; single-crystalline GaAs wafer from differentpreparations [vertical gradient freeze (VGF) and liquidencapsulated Czochralski (LEC)]; InP samples from Fe-doped crystals with a resistivity between 0.01 and2� 108V cm and semi-insulating 6H-SiC wafer grown byHTCVD with resistivities exceeding 2� 109V cm.

3 Simulations During the development and appli-cation of MDP and MD-PICTS it became clear that theobtained results are often not describable by simple defectmodels. The widely used SRH-Theory is only applicable ifno trap influence is assumed, which is invalid especially for

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low injection measurements at e.g., mc-Si and MD-PICTSmeasurements in general, where this trap influence isinvestigated. This leads to the necessity of a new simulationtool without any approximations that is able to simulateinjection and temperature dependent lifetimes as well as thetrapping dynamics.

The numerical tool is based on a generalized rateequation system. The rate equations are used to describe thetime dependent change of the carrier occupation of the bands( _n; _p) and defects ( _nTj). All possible transitions between thedefect levels in the forbidden gap and the bands of asemiconductor are described by transition rates.

A rate equation system is used, in which the onlyapproximation is, that no direct interactions between defectlevels are included [9].

_n ¼ GoBB þ Gth

BB þXj

Cj�Dj

� ��UBB�UAug; (3)

X� �

_p ¼ Go

BB þ GthBB þ

j

Fj�Ej �UBB�UAug; (4)

_nTj ¼ Dj þ Ej�Cj�Fj: (5)

Based on the simulated time dependent carrier concen-trations, the photoconductivity can be calculated using themobility model of Dorkel and Leturcq [10]. The minoritycarrier lifetime finally can be extracted from the simulatedtransient decay of the photoconductivity after Gopt is set tozero or can be determined from the photoconductivity value,if a quasi steady state approach is used. Consequently, thetechnique which is used to evaluate the lifetime values fromthe simulated data is strictly based on the used measurementtechnique and thus is correlated to the lifetime evaluationtechnique which is experimentally applied. Therefore a verygood agreement between simulated values and measurementresults is guaranteed. More details and a demonstration of theabilities of this simulation tool can be found in Ref. [11].

4 Experimental results and discussion4.1 Microwave detected photoconductivity

Some of the most detrimental defects in silicon are traps ingeneral, iron, boron–oxygen complexes and chromium. Allthese defects have been investigated extensively in the lastdecades. With MDP it is possible to investigate these defectswith a high resolution and by injection dependent lifetimemeasurements over a wide range of injections. Examples atpassivated crystalline silicon wafers are presented.

With the ability of MDP to measure the lifetime andphotoconductivity simultaneously, it is possible to estimatethe trap density in mc-Si by the slightly modified model ofHornbeck and Haynes [12]. This model includes only onetrap level, so that the determined trap density is only anestimation. By fitting the photoconductivity as a function ofthe optical generation rate, the trap density and activationenergy can be determined. The following formula is used for

� 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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the fitting:

D

Figu(a);NT¼

� 20

s ¼ e Dn mn þ mp

� �þ mp

Dn � NT

Dnþ NC � exp �Ea

kT

� �T

" #(6)

Figure 4 (online color at: www.pss-a.com) Exemplary iron map ofa SiNx passivated mc-Si wafer with a resolution of 0.5 mm.

Figure 3 shows an exemplary photoconductivitymeasurement at a mc-Si wafer, the fit-curve and thecorresponding measured apparent lifetime.

By MD-PICTS measurements it is possible to separatedifferent trap levels, but no information about the trapdensity is provided. By applying both methods a compre-hensive study about traps in a sample can be conducted.

The iron detection by lifetime measurements is widelyspread in the photovoltaic industry. The FeB pairs aredissociated by irradiating the sample with light and from thedeviation between the measured lifetime before and afterthe dissociation the iron concentration can be determined viathe following formula:

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½Fe� ¼ CFe

1

tafter� 1

tbefore

� �: (7)

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The accuracy of this determination depends strongly onthe use of an accurate calibration factor CFe, which dependson the injection, doping and trap density. By using the rateequation simulations it is possible to simulate the correctcalibration factor for every possible measurement condition[13]. Figure 4 shows an exemplary iron map of a mc-Si waferwith a resolution of 0.5 mm.

One difficulty of the iron detection is the separation fromother defects, which also react on the irradiation with light,e.g. BO2. With several annealing steps and repeatedirradiation, it is possible to separate FeB and BO2, sinceboth defects differ in their association time constants andresponse to elevated temperatures. For the BO2 determi-nation Eq. (7) is also used, only with the calibration factor forBO2 (CBO2), which is simulated with the according defectparameters [14]. Since especially the carrier cross sectionsare not known exactly for BO2, only a relative concentrationcan be measured. Figure 5 displays the maps of the relative

re 3 Measured photoconductivity and fit curve versus Gopt

apparent lifetime versus Gopt (b); determined trap parameter:8� 1014 cm�3, EA¼ 0.387 eV [13].

11 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

BO2 and Fe concentration of an oxide passivated Cz-Siwafer. With these measurements typical differences in thedistribution of both defects become obvious. Iron isconcentrated at the edge of the sample, whereas BO2 is

Figure 5 (online color at: www.pss-a.com) Relative BO2 concen-tration (a) and Fe concentration (b) of an oxide passivated Cz-Siwafer.

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Figure 6 (online color at: www.pss-a.com) Exemplary map of therelative chromium concentration of an intentionally doped Cz-wafer.

Figure 7 Spectra of temperature treated electronic grade p-dopedsilicon [16].

distributed in high concentrated regions in the middle of thewafer. As mentioned above chromium is also an effectiverecombination center in silicon. Similar to iron it occurs asCrB in boron doped silicon and can be dissociated to Cri andB by annealing the sample for 30 min at 250 8C. For thechromium determination Eq. (7) is also applied with acalibration factor CCr. To determine the injection dependentcalibration factor CCr the defect parameters from [15] wereused. Note that similar to BO2 defect parameters of CrB andCri are not well known so far. That is why only the relativedensity is determined. An exemplary map of the relativechromium concentration of an intentionally chromiumdoped Cz-wafer is shown in Fig. 6.

By spatially resolved MD-PICTS measurements, it ispossible to investigate the defect distribution of differentregions of the here presented samples, in order to learn moreabout the correlation of e.g., BO2 and thermal donors (TDs).An example of an investigation of TDs in silicon by MD-PICTS is presented in the next section.

4.2 Microwave detected photo-induced currenttransient spectroscopy In contrast to DLTS a directdetection of metal contaminations like iron and chromium insilicon with PICTS is so far not successful because thesedefects are mostly acting as the main recombination centers.But by improving the sensitivity of a microwave detectionsystem by several orders of magnitude the visualization of sofar non-detectable defects in electronic grade silicon wasachieved. One example is the electrical investigation of thewell-known TD in electronic grade p-doped silicon [16]. It isnot detectable with DLTS because of the position of theFermi level. The MD-PICTS spectra in Fig. 7 shows twodefect levels called PTD and PD. Following their evolutionduring thermal treatment suggests that the PTD peak refers tothe TDs in silicon. After annealing for 40 min at 650 8C theemission maximum shifts more than 40 K to lower

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temperatures and is now located at 96 K (previously 133 Kin the as-grown state and 140 K in the 450 8C treated sample).This is due to the change in capture cross section froms¼ 2� 10�18 cm�2 in the as-grown material tos¼ 2� 10�15 cm�2 in the 650 8C treated sample. Theactivation energy shifts only slightly from EA¼ 0.13 toEA¼ 0.11 eV. The change of position is believed to becaused by the transformation of an electrically active TDstate into an electrically inactive trap state at temperaturesabove 600 8C [17]. At higher temperatures above 900 8C theintensity of the defect peak drops rapidly suggesting thedissociation of this defect level. A second defect level withEA¼ 0.26 eV in as-grown samples at 242 K can be observed.It is caused by defects in the vicinity of dislocations.Correlations with PL measurements carry this assumption.

With MDP and MD-PICTS it is possible to obtain adeeper understanding of the observed sharp transition in theelectrical properties of wafers prepared from different partsof a silicon brick [18]. The PTD and PD peaks known fromelectronic grade p-doped silicon and additional peaks arefound by investigations of solar grade silicon samples(Fig. 8). P4 with an activation energy of 0.09 eV is onlyobservable in the bottom part. Because of this low activationenergy, the large width of the peak and the position of thecorresponding wafer in the silicon brick it may be ascribed toa defect cluster containing nitrogen. P3, whose activationenergy cannot be deduced, may have its origin in a cluster ofbulk defects, because different surface treatments do notinfluence the peak. The appearance of all defect peaks differsfrom the associated brick position. Mapping the sampleswith MDP shows corresponding changes in lifetime,diffusion length, and photoconductivity.

Beside investigations on silicon the new method forcontactless electrical defect characterization was applied ongallium arsenide. MD-PICTS spectra show that a highdensity of the so-called EL5-defect in cell interior regions isresponsible for dark areas of smaller lifetimes in MDPmappings [7]. In contrast to other techniques MD-PICTS candetect signals even from thin surface regions (0.3mm) of SIGaAs samples and is therefore able to analyze, e.g.

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Figure 8 (online color at: www.pss-a.com) MD-PICTS spectraof solar grade p-doped silicon samples from different brickheights [18].

influences of surface treatments. Figure 9 shows the defectpeak of the well-known EL2 defect in samples with differentacceptor concentrations [19]. The activation energy variesbetween 0.55 and 0.73 eV which is in agreement with datafrom other groups [20, 21]. Conspicuous is the occurrence ofthe defect peak in positive and negative form.

The explanation of the negative PICTS peak effect isbased on the system of rate equations from Section 3, whichcalculates the carrier concentration of the involved energylevels by taking all participating generation and recombina-tion processes as well as trapping and emission events duringand after the photo excitation into account. Thereforephotoconductivity signals, as they are measured as a resultof the photo generation of carriers, can be simulated fordifferent temperatures, if an appropriate mobility is takeninto account. The consideration of the relevant donor andacceptor concentrations along with the concentration of theEL2 defect finally allows for the theoretical reproduction of

Figure 9 (online color at: www.pss-a.com) Detection of the EL2d-efect in SI GaAs samples with different acceptor concentrations byHT-MD-PICTS. Peak height and sign correlate to the acceptorconcentrations [19]. Samples from series D were undoped, acceptorconcentration rising from A to C.

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experimental results. The latter show a dependence of theheight of the EL2-related PICTS peak on the acceptorconcentration in the material thus being associated with theFermi level position. To briefly summarize the theoreticalinvestigations it can be said that the fast recombination andtrapping dynamics in the III-V-compound semiconductorGaAs lead to a drop of the electron concentration below theequilibrium value after the excitation is switched off, whilethe hole concentration shows a positive decay behavior. Theamount of electrons that can be trapped and thus the ratio ofthe concentrations of the two types of excess carriersremaining in the bands (Dn/Dp) are determined by the initialoccupation of the electron trap (EL2) and therefore by theposition of the Fermi level. The resulting photoconductivitysignal

Figudopediffeistic

Ds ¼ e � mnDnþ mpDpð Þ (8)

is consequently controlled by the behavior of the dominantcurrent fraction, thus also considering the large difference ofthe carrier mobility values for GaAs (mn/mp� 20). Thatmeans a positive decay behavior of the photoconductivitysignal is only observable, if the excess hole concentrationremarkably exceeds the excess electron concentrationleading to signal

mnDn < mpDp: (9)

This is the case for a Fermi level leaving most of the EL2defect levels unoccupied [9].

Investigations on indium phosphide show that the defectcontent changes during annealing processes, which may alsohave an impact on the distribution of electrical properties.Whereas the defect content of as-grown samples depends ontheir position in the crystal, an equivalent set of defect levelsis prominent in wafer-annealed samples [22]. Figure 10shows a comparison of Fe-doped SI-InP samples fromdifferent crystal positions. They differ in their characteristic

re 10 Comparison of MD-PICTS spectra of as-grown Fe-d SI-InP samples from different crystal positions and thusrent Fe-concentrations. The samples differ in their character-defect levels [22].

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Figure 11 Comparison of MD-PICTS spectra of different SI-6H-SiC samples in different temperature ranges. Samples I–III weregrown under same process conditions [8].

defect levels. Additional negative peaks occur in somesamples for temperatures above 350 K with the amplitudeincreasing with the crystal length. The occurrence of peakswith different magnitude and sign in this temperature rangeis Fe-related. The negative peak is assigned to a transition ofa hole leaving the Fe3þ level toward the valence band [23].The observation of MD-PICTS signals of both signs in Fe-doped InP provided the first direct proof of iron acting as arecombination center in InP.

Analyses of semi-insulating 6H-SiC grown with astandard process and same process parameters show severaldiffering shallow defect levels occurring in the lowtemperature range (Fig. 11). Additionally in samples grownunder different C/Si-ratios different trap emission dynamicsare obtained for higher temperatures, which are supposed tobe due to different compensation effects [8]. The activationenergies and capture cross sections of the defect peakscalculated from the spectra from Fig. 11 lie in the same rangeknown from the literature [24–26]. They are traced back toomnipresent donor- and acceptor-like impurities and intrin-sic defects.

5 Conclusion The presented experimental resultsshow the potential of the new methods MDP and MD-PICTS for contactless electrical characterization of defectsin several semiconducting materials. Both techniques use thesensitivity benefit of microwave detection leading to a highspatial resolution and measurement speed as well as thepossibility to recognize defects which were not investigatedyet. A cooperation of MDP and MC-PICTS, e.g. mapping ofa sample and analysis of several areas differing in reportedlifetime with MD-PICTS for defect recognition, leads toinsights of the cause of different measurable effects. Theintroduced simulation tool helps to get a deeper under-standing of the experimental data. To demonstrate theabilities of both methods, a range of previous results ondefect characterization were reviewed in this paper.

By determination of a calibration factor depending oninjection level, doping and trap density MDP is a usefultechnique to map the local iron concentration with a high

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spatial resolution. Investigations on Cz-Si wafers show thetypical differences in distribution of Fei and BO2. While ironis concentrated at the edge of the sample, BO2 is moredistributed in the middle of the wafer.

With MD-PICTS experiments the visualization of so farnon-detectable defects was achieved. One example is theinvestigation of the TD defect level in electronic grade p-doped silicon. This defect cannot be obtained with DLTSbecause of the position of the Fermi level. Samples fromsolar grade mc-Si show different defect levels due to theirbrick height. Comparison between MD-PICTS spectra andlifetime mappings with MDP on gallium arsenide waferslead to the assumption that lifetime degradation of severalareas is caused by the EL5 defect. The EL2 defect was alsoanalyzed. The differentiation between the single ionizedstate EL2þ from the EL20 is possible with the help of thesignal sign. Investigations on Fe-doped indium phosphidegave the first direct proof that iron acts as recombinationcenter in this material. In SI 6H-SiC the defect levels knownfrom the literature were detected with similar activationenergies and capture cross-sections. A deeper understandingabout the appearance of PICTS-signals of different signswith simulations basing on a rate equation system has beenaccomplished.

Acknowledgements The support of our research partnerwith the supply of samples and helpful discussions and also financialbenefit is gratefully acknowledged. This work was also financiallysupported by the European Funds for Regional Development(EFRE) 2007-2013, the European Social Funds (ESF) 2007–2013with the project number 080940489 and the State Saxony.

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