Capacitance Spectroscopy of Light Induced Trap States in Organic

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Capacitance Spectroscopy of Light Induced Trap States in Organic Solar Cells Robert A. Street, Yang Yang, Barry C. Thompson, and Iain McCulloch J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.6b06561 • Publication Date (Web): 04 Sep 2016 Downloaded from http://pubs.acs.org on September 7, 2016

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The Journal of Physical Chemistry

Capacitance Spectroscopy of Light Induced Trap States in Organic Solar Cells Robert A. Street,#* Yang Yang,§ Barry C. Thompson% and Iain McCulloch‡ #

Palo Alto Research Center, Palo Alto, CA 94304.

§

Dept. of Materials Science and Engineering, UCLA, Los Angeles, California 90095

%

Dept. of Chemistry and Loker Hydrocarbon Research Institute, University of Southern

California, Los Angeles, California 90089 ‡

Imperial College, London, SW7 2AZ, UK

Corresponding Author * E-mail: [email protected]; Tel 650-812-4155 ABSTRACT The light-induced localized trap state density of states in organic bulk heterojunction solar cells is reported, based on capacitance-frequency and photocurrent spectroscopy measurements. Several different cell materials show qualitatively the same behavior. A deep trap is induced by prolonged white light illumination with state density 1016-1017 cm-3, and is observed by both experimental techniques. The trap depth is 0.5-0.7 eV. The light soaking has no measurable effect on the localized band tail density of states. The observation of the effect in many materials is consistent with the model that traps are created by light-induced dissociation of C-H bonds. The data suggests that disorder enhances the trap creation. The data also allow an estimate of the trap capture cross section, which is discussed in terms of local transport anisotropy.

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1 Introduction In the effort to improve the efficiency of bulk heterojunction organic solar cells, it is important to measure, characterize and ultimately reduce the density of recombination centers, because recombination is one of the major limitations of current cells. Organic solar cells also degrade significantly under sunlight, and a component of the degradation arises from the generation of recombination centers in the active layer.1,2,3,4,5 The nature of these induced defects, their energy state distribution, the physical and chemical mechanism of their creation, their creation kinetics and their relation to native defects are important problems. The presence of localized trap states in organic solar cells and other organic devices has been known for many years.6,7,8,9,10 There is considerable evidence for a characteristic separation of these states into band tails states that arise from the material disorder and deeper states that are typically associated with point defects, impurities and perhaps extended defects.6,7,11 The band tail states are well characterized by time-of-flight photoconductivity, photocurrent spectroscopy and transient photoconductivity. An approximately exponential band tail distribution is observed with exponential slope varying from about 25-50 meV in the different materials. Deep trap states are also observed by some of the same techniques. Recently capacitance-frequency C-ω measurements have been added to the techniques applied to measure the density of states in organic solar cells,8,12 and this is the focus of measurements reported here. The C-ω measurement is a common technique for measuring trap density and depth in semiconductors. The aim of this paper is to gain further insight into the use of this technique for BHJ cells, and to measure trap densities and their increase after prolonged illumination. Our approach is to measure a variety of cells fabricated in different laboratories and with different polymer donor materials. The comparison of trap parameters before and after 2 ACS Paragon Plus Environment

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light-soaking will indicate the extent to which trap creation depends on the specific cell materials. Previous work also shows that extended exposure to radiation creates excess deep trap states and detailed studies have been made in P3HT:PCBM and PCDTBT:PCBM.13 The induced deep traps cause increased recombination and degrade the performance of the solar cells, particularly the fill factor. Light-induced traps are studied here and the results are compared in a range of different cell materials. 2. Methods The solar cell samples were made in various labs (references are given in section 2.1) and are encapsulated with glass covers. Samples are stored in nitrogen but measured and illuminated in ambient. Capacitance-frequency measurements are made in the dark with an impedance analyzer. The photocurrent spectroscopy measurement technique is discussed elsewhere.14,15 Light-soaking is performed with a halogen light with an IR absorbing filter; the light intensity was the same for all measurements and is about 200mW/cm2. Since the IR filtered white light is a better match to the cell absorption than sunlight, the illumination corresponds to more than 2 suns exposure.

The illumination causes some warming of the sample and the substrate

temperature was measured to be 31-34°C. Previous work showed that the defect creation rate was roughly linear in light intensity.16 2.1 Solar cell samples The samples are all polymer:fullerene BHJ organic solar cells fabricated at a variety of laboratories, and described in publications as noted below. The specific materials studied are, P3HT; Poly(3-hexyl thiophene).17



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PCDTBT; poly[carbazole-dithienyl-benzothiadiazole).18,19 PTB7; poly(thieno[3,4-b]-thiophene/benzodi¬thiophene).20 PBDTT-DPP;

poly{di(ethylhexylthienyl)benzodithiophene-alt-5-dibutyloctyl-bis(5-

bromothiophen-2-yl) pyrrolo pyrrole-dione}.21 GeIDT-BT;poly{germaindacenodithiophen-co-benzothiadiazole}22 DPPTTT; poly{Diketopyrrolopyrrole-Thieno[3,2-b]thiophene}23 The fullerenes, PC60(70)BM; phenyl-C61(70)-butyric acid methyl ester, and ICBA; indene-C60 bisadduct, were used as the electron acceptor. The samples include one pair of cells (PBDTTDPP) with normal and inverted structure and one pair of cells (PTB7) comparing PC60BM and ICBA fullerenes. The cells range from 0.1-0.3 cm2 in area. The study was confined to electronic properties measurements and did not include morphological or compositional studies. It is possible that prolonged illumination results in a measureable morphological change and that the polymer to fullerene ratio influences the trap creation. More detailed studies would be needed to investigate such effects. 2.2 Capacitance measurements and analysis Capacitance-frequency C-ω measurements were made in the dark, mostly at room temperature, mostly at zero dc bias and in the frequency range 10-106 Hz. The applied ac voltage was 0.1 V which was chosen to be small enough to minimize distortion of the data and large enough to minimize measurement noise. Measurements at different dc bias were used to confirm aspects of the model used to analyze the data. C-ω measurements reflect the density of deep states because the capacitance measures the charge trapped in the active layer and the frequency determines what fraction of the trapped charge can respond to the ac field by thermal 4 ACS Paragon Plus Environment

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excitation to mobile transport states. The analysis developed by Walter et al is used to extract the density of states.24 The trap density of states (DOS) distribution NT(E) for a device of area A and thickness d is related to the capacitance at frequency ω by, =

(1)

The trap energy Eω corresponding to a measurement frequency ω is given by

=

(2)

where VBI is the built-in potential, ω0 is the rate prefactor for thermal excitation from the trap, q is the electric charge and β is a small correction factor discussed below. Eq. 2 relates the trap energy to the measurement frequency because release of a carrier from a trap is by thermal excitation. The mechanism for the frequency dependence of C(ω) is illustrated in the band diagram of Fig. 1. The small ac applied voltage shifts the Fermi energy EF and alternately traps and releases carriers from states near EF. At a certain measurement frequency ω, only states shallower than an energy Eω can respond fast enough to the ac field to contribute to the capacitance.

The derivative term (ω/kT)dC/dω in Eq. 1 picks out only the response of traps

within kT of Eω. The other terms in Eq. 1 give the effective volume of traps that contribute to the capacitance from which the total NT(Eω) is obtained. The factor β in eq. 1 arises because the ac field of the capacitance measurement decreases with distance from the contact. Ref 23 gives analytical expressions for the correction for the case of a linear internal field distribution as shown in Fig. 1 and for a parabolic internal field for the case of a depletion layer. Absent further information about the actual band profile in the samples measured, the factor β is set equal to 1 in our analysis. Since β is greater than 1 but usually less than 2, and increases with trap depth, 5 ACS Paragon Plus Environment


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our measurements slightly underestimate the density of states, particularly for the deeper states. For the example of hole states as in Fig. 1, only states above the Fermi energy are occupied and can contribute to the capacitance. (a)

(b)

LUMO

LUMO

NT(E) occupied VAC

Eω

ETmin

Polymer

e

Deep traps

CT

EF

EGI Fullerene

HOMO

VBI

Band tail

h HOMO

Figure 1. (a) Band diagram illustrating the measurement of deep hole traps by the capacitancefrequency technique. (b) Illustration of BHJ solar cell density of states showing band tail and deep trap states, the trapping and release process and the charge transfer absorption. A value 1012 s-1 for ω0 is assumed for the analysis because it is typical for thermal excitations but the value is not known explicitly for organic solar cells. This choice and the evidence that it is approximately correct is discussed in Section 4. The prefactor is related to the capture cross section for capture into the trap, and may be different for different types of trap states. From Eq. 2, the assumed value of ω0 corresponds to a measured energy range roughly from 0.3-0.6 eV at room temperature. A different value of ω0 by a factor 10 changes the measured energy range by 60 meV. There is a minimum measurable trap energy (ETmin in Fig. 1a) given by the position of the Fermi energy at the contact. When the Fermi energy is sufficiently deep, none of the traps can respond at the highest frequency and the measurement should result in the geometrical capacitance with the active layer acting as an insulator. The analysis assumes that the energy dependence of the DOS is slowly varying compared to kT; the analysis causes a more rapidly changing DOS to appear broader than the true DOS. 6 ACS Paragon Plus Environment

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The C-ω experiment cannot distinguish between electron and hole traps, and measures the sum of both. There is an energy near the middle of the band gap where traps are not measured.23 This occurs under conditions that the trap occupancy does not change with the ac field because the electron and hole thermal excitation rates are equal. The measured DOS may therefore be a combination of electron and hole traps in either or both of the polymer and fullerene materials. The capacitance measures all the traps in the material, including those near and further away from the BHJ interface. In contrast, the photocurrent spectroscopy technique discussed below only measures states that are close to the BHJ interfaces. To illustrate the analysis, Fig. 2a shows an example of the C-ω measurement for a PTB7:PCBM solar cell plotted on a log(frequency) scale, which corresponds to a linear trap energy scale. The figure shows data before and after white light illumination for about 4 days. Since ωdC/dω=dC/dln(ω), the density of states according to Eq. 1 is proportional to the slope of the data in Fig. 2a, and is therefore easy to interpret qualitatively. NT(E) is evidently large at high frequency and small trap depth because here the capacitance changes rapidly. The trap density decreases rapidly at the middle of the frequency/energy range and then increases again at low frequency showing a separation between the deep and shallow traps. Furthermore, the long illumination evidently increases the density of deep traps but not of shallow traps. The observation that the high frequency capacitance is unchanged by light soaking also implies that the Fermi energy at the contact is unchanged in this case.



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Figure 2. (a) Room temperature capacitance-frequency measurements on a PTB7:PCBM cell before and after light soaking. Open data points are measurements and the lines are fits to the DOS. (b) Density of states (DOS) used to fit the C-ω data. Rather than take the derivative of the C-ω data to obtain the density of states according to Eq. 1, we construct a simple model DOS, calculate the expected C(ω) and adjust the DOS parameters to fit the data. The reason for this approach is that the noise in the capacitance measurement gives large fluctuations in the derivative. The model DOS is shown in Figure 2b and comprises an exponential distribution at low trap energy and a broad gaussian band of deeper states. The model is constructed in this way because it generally conforms to the qualitative form of the data. Furthermore there is prior information showing the presence of an exponential band tail in the organic solar cells as well as evidence for the presence of deep traps, along with the expectation that the deep traps are broadened by disorder and hence have a density of states that varies smoothly with energy.25 The fit to the data is shown by the black lines in Fig. 2a for the DOS in Fig. 2b. The results agree with the qualitative interpretation that the deep trap band increases with illumination but the exponential band tail region does not change. It is apparent that the peak of the defect band is beyond the measurement window, and so its parameters are only approximate. The fit of the model to the data is close but not perfect. We do not attempt a detailed least squares fit because we expect that the DOS is not exactly of


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the assumed form.

However, the model DOS is evidently accurate enough to be a good

representation of the true DOS.

At this point we are primarily interested in having an

approximate DOS from which to study trends across many material systems. The shape of the DOS comes directly from the C-ω data but the quantitative trap density requires the extra parameters in Eq. 1, of which the device area is easily measured. The thickness of the active cell layer is not known very accurately but is approximately 100 nm for all the devices and this is the assumed value. The built-in potential VBI is the internal potential of the cell in the dark as indicated in Fig. 1a. VBI can be measured from the voltage dependence of the photocurrent, since the photocurrent changes sign at an applied bias of VBI, as discussed elsewhere.14 In those cases that we do not have this data, it can be estimated reasonably accurately because it must be larger than VOC but no more than the work function difference between the contacts. According to Eq. 1, an increase in VBI should decrease ωdC/dω for a fixed density of states distribution. This aspect of the mechanism can be tested by performing measurements with an applied dc bias. A dc bias will shift the electron and hole Fermi energy at their respective contacts and provided the bias is small and the device current is low, then the Fermi energies will be approximately at constant energy across the region of the device near the contact where the trap occupancy is responding to the capacitance measurement. The result is that the effective built-in potential is increased or reduced by the bias voltage and the change should be evident from the capacitance measurement. Fig. 3a shows C-ω measurements for P3HT:PCBM for a range of dc bias. The capacitance decreases in reverse bias and increases with forward bias as expected and the linear relation in Fig 3b shows that the data is reasonably consistent with Eq. 1.

This measurement provides a test to confirm consistency with the model and that the 9 ACS Paragon Plus Environment


capacitance changes do indeed originate from bulk traps in the active BHJ layer.

The other

feature of the data in Fig. 3a is that the capacitance becomes independent of frequency at high frequency, unlike the data of Fig. 2a. The interpretation is that the Fermi energy position at the contact is deeper in P3HT:PCBM so that the shallower traps are unoccupied and hence do not contribute to the capacitance. To this extent the measurements provide information about how well the effective work function of the contacts is matched to the HOMO or LUMO levels of the BHJ cell.

66.E-09

5

Capacitance at 1 kHz (nF)

5

5.0E-09

(a)

0.5

5.E-09

Capacitance (nF)

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0.4

4

4.E-09

0.3

33.E-09 0.2

22.E-09

0 -0.5

11.E-09

dc bias

(b)

4.0E-09

4

3.0E-09

3

2.0E-09

2

1.0E-09

1

0.0E+00

0

00.E+00 10

100

1000

10000 100000 1000000

0

Frequency (Hz)

2 4 1/(VBI+Vbias) (V-1)

6

Figure 3. (a) C-ω data for P3HT:PCBM measured at different applied dc bias. (b) Plot of the capacitance at 1 kHz versus the effective built-in potential for the data of Fig. 3a, showing consistency with eq. 1. VBI is 0.67V There are several sources of experimental uncertainty that can affect the accuracy of the estimated DOS distribution. The kT thermal broadening of the DOS and the β value are discussed above. The trap energy is measured from the transport energy which is probably not a precise energy and may also contribute to broadening of the apparent DOS. The high frequency capacitance could be affected by the external series resistance RS when ω>1/RSC.

The

capacitance model also assumes that charge that is released from a trap moves rapidly to the contact, otherwise it would not contribute to the capacitance. In low mobility materials, it is possible that the high frequency capacitance is similarly limited by the internal series resistance. 10 ACS Paragon Plus Environment

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A high series resistance suppresses the solar cell fill factor, and since the cells mostly have fill factor >60% (see data in Ref. 26) the series resistance cannot be large. The focus of this paper is mostly on the deep traps which correspond to low frequency data unaffected by the series resistance. These effects are relatively small numerical factors and the general trends and comparison between samples will be only slightly affected. Primarily because of the β factor, the measurements generally underestimate the trap density but probably by no more than a factor 2. 3. Results 3.1 Capacitance measurements Fig. 4 shows the raw capacitance frequency data for eight different organic solar cells, before and after light soaking, and the derived DOS is shown in each case, based on the analysis described above. The solid lines in the raw data plots are the capacitances calculated from the DOS fits. Although there are differences in the details, the data broadly show the same qualitative behavior in each material system, summarized as follows.

2.4E-09 2.4 2.2E-09 2.2

2.3 1016 1.E+16 1016

5 1015

2.0E-09 2.0

11

1010

2 100 10

0.3

3 4 1000 10000 100000 10 10 105 1000000 106

1.E+17 1017

5.5E-09

PBDTTDPP Light soak 77hr

1.8E-09

1.6

1.6E-09

1.4 1.4E-09

4.5E-09 4.5 4.0E-09 4.0 3.5E-09 3.5

1 1

10 10

1002 10

3 1000 10

10000 104 100000 105 1000000 106

Frequency (Hz)

0.3

0.4

0.5

1.E+16

5 1015

1 1

10 10

1002 10

3 1000 10

0.3

4 10000 100000 10 105 1000000 106

0.6

0.5

0.6

1.E+18 18 10

2.5

Light soak 114 hours

2.0E-09 2.0

1.5E-09 1.5

PCDTBT:PCBM

1.0 1.0E-09

PCDTBT:PCBM

17 1.E+17 10

1.8 1016

4.6 1015 16 10 1.E+16

0.5 5.0E-10 1 1

Trap energy (eV)

0.4

Trap energy (eV)

2.5E-09

1015 1.E+15

3.0E-09 3.0

1.7 1016

1016

Frequency (Hz)

3.5 1015

C3DPPTTT:PCBM

15 10 1.E+15

1.0 1.0E-09

0.6

PBDTTDPP

1.E+16 1016

Initial

1.2 1.2E-09

6 1015

DOS (cm-3 eV-1)

5.0E-09 5.0

0.5

Light soaked 95 hr

2.0E-09 1.8

Trap energy (eV)

Frequency (Hz) 5.5

0.4

Capacitance (nF)

1.8

C3DPPTTT:PCBM

2.2 2.2E-09

1015 1.E+15

1.8E-09

17 1.E+17 10

2.4E-09

DOS (cm-3 eV-1)

DOS (cm-3 eV-1)

Capacitance (nF)

Light soak 112 hours

2.6E-09 2.6

2.4

C8GeIDT

DOS (cm-3eV-1)

1.E+17 1017

C8GeIDT 2.8E-09 2.8

Capacitance (nF)

3.0E-09 3.0

Capacitance (nF)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


10 10

100 2 10

1000 10000 100000 1000000 3 4 5 10 10 10 106

Frequency (Hz)


0.3

0.4

0.5

Trap energy (eV)

0.6


18 1.E+18 10

6.E-09

6

5.E-09

5

1.E+17 1017

8 1016

4.E-09

4

1.5 1016

1016 1.E+16

3.E-09

3

11

10 10

1002 10

1000 103

10000 104 1000001000000 105 106

0.3

Frequency Hz)

0.4

0.5

0.6

light soak 93 hrs

4.0E-09 4.0 3.5E-09 3.5

17 10 1.E+17

1.6 1016

1.0 1016

16 10 1.E+16

3.0E-09 3.0

11

10 10

2 100 10

3 1000 10

10000 104 1000001000000 105 106

Frequency (Hz)

1000 103

0.3 0.4 0.5 0.6 0.7

10000 104 100000 105 1000000 106

Trap depth (eV)

Frequency (Hz)

PTB7:ICBA

DOS (cm3/eV)

5.0

16 1.E+16 10 100 102

10 10

18 1.E+18 10

6.0

PTB7:ICBA

0.3

0.4

0.5

1.1 1016 3.6 1015

17 1.E+17 10

1.E-09 1

6.0E-09

5.5

4.5E-09 4.5

2.E-09 2

11

10

5.0E-09

Light soak 106 hr

3.E-09 3

Trap energy (eV)

6.0

5.5E-09

4.E-09 4

0 0.E+00

18 1.E+18

6.0E-09

P3HT:PCBM

P3HT:PCBM

DOS (cm3/eV)

light soak 112 hrs

1.E+18 18 10

5.E-09 5

PTB7:PCBM

Capacitance (nF)

Capacitance (nF)

7

Capacitance (nF)

PTB7:PCBM

DOS (cm-3eV-1)

8

7.E-09

light-soak 120hrs

5.0E-09 5.0 4.5E-09 4.5 4.0E-09 4.0 3.5E-09 3.5

1

1

0.6

17 10 1.E+17

1.4 1016

6.3 1015

16 10 1.E+16

3.0 3.0E-09

Energy (eV)

PBDTTDPP:PC

PBDTTDPP:PCBM

5.5E-09 5.5

DOS (cm-3/eV)

8.E-09

Capacitance (nF)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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10

10

100

102

10003 10

100004 1000005 1000000 10 10 106

Frequency (Hz)

0.3

0.4

0.5

0.6

Energy (eV)

Figure 4. C-ω measurements and the corresponding DOS, before and after light soaking, for the different solar cells that were studied. Open data points are measurements and lines are fits to the data from the DOS. Light soaking times are about 4 days and the trap densities before and after light soaking are indicated. 1. All the results can be fit reasonably well with the exponential band tail plus gaussian deep state DOS model. The extent of the band tail region that is observed varies considerably either because the geometrical capacitance is reached or because the band tail energy is at the lower energy limit of the measurement window. 2. In all the devices there is evidence for deep trap states in the cells before light soaking. In some cases the deep trap density is low enough to be barely distinguishable, but the fit to the DOS is always better than if zero trap density is assumed. 3. In all cases, light soaking increases the deep state density. In most cases the shape of the trap DOS is consistent with being the same before and after light-soaking, although in some cases the small annealed state DOS makes it difficult to extract an accurate DOS. P3HT:PCBM is the only case where there seems to be a significant shift of the trap energy after light soaking. The trap density falls within a fairly narrow range both before


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and after light soaking. In the annealed state the trap density is 3x1015-2x1016 cm-3 and after light soaking it is 6x1015-1017 cm-3. 4. The peak of the trap DOS varies from being just inside the upper limit of the measurement energy range to being just outside, i.e. it is in the range 0.5-0.7 eV. Figure 5 plots the estimated trap energy versus the interface band gap EGI, as determined from the photocurrent spectrum.26 There is a weak trend to a deeper trap energy with increasing EGI, but the similar trap energy suggests that the trap has similar local structure in each case. 5. Light soaking has no measurable effect on the band tail DOS. Even though in some cases the capacitance in the high frequency region differs before and after light soaking, the analysis showed no change in the band tail DOS. Instead the changes are attributable to shifts in the Fermi energy, and it is reasonable that the increased trap density can cause the Fermi energy at the contact electrode to shift. These observations show that a broadly similar mechanism for light-induced trap creation applies to all the materials. 0.75

Trap depth (eV)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


0.65

0.55

0.45 1

1.1

1.2

1.3

1.4

Interface gap (eV)

Figure 5. Plot of the measured trap depth and the interface band gap for the different solar cells.



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Solar cells made from P3HT and PCDTBT have high frequency capacitance that tends to a constant value indicating that the contact Fermi energy is relatively deep. Other cells, notably of the higher performance recent materials are not limited by the Fermi energy and the capacitance changes rapidly at the highest measurement frequency indicating a shallower contact Femi energy, which is perhaps a reflection of their improved performance. The defect band of P3HT:PCBM is the narrowest of all the devices measured and drops sharply near 0.6 eV. Since EGI is estimated to be 1.1-1.2 eV, it is possible that the defect band shape is affected by the property that the capacitance measurement does not respond to states near the middle of the gap where the thermal excitation rate for electrons and holes is the same. The capacitance-measured defect band may therefore be artificially narrow and the effect might account for the apparent shift in peak position with illumination. Figure 6 shows the increase in deep trap density with illumination time for PCDBTB:PCBM and PBDTTDPP:PCBM measured by C-ω. The relative change is obtained by measuring the enhanced capacitance below 1000 Hz at different stages of light soaking and annealing. In both cases the increase in trap density tends to saturate at long exposures. The results for PCDTBT agree with our previous studies and the data for PBDTTDPP show that the same behavior also applies to this polymer, suggesting that it is a general property of the polymer:fullerene cells. The data also show that the light-induced traps are reversible with thermal annealing to about 100C, again similar to previous observations with P3HT and PCDTBT. The data in Fig 6 also indicates the range in the trap density enhancement with light soaking, since PBDTTDPP:PCBM has the smallest increase of about 30% and PCDTBT has the largest at about a factor 3. PCDTBT is also the most disordered polymer having the largest band tail slope. 14 ACS Paragon Plus Environment

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Figure 6. Capacitance frequency measurement of relative trap density induced by illumination in PBDTTDPP versus illumination time (closed circles), also showing that the induced traps are reversible by annealing to 80C (open triangles). 3.2 Photocurrent spectroscopy Photocurrent spectroscopy PCS measurements were also made on the same solar cell samples, also before and after light soaking, and the results are shown in Fig. 7.

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measurement technique and the PCS spectra of most of the cells used here have been reported before and in several cases a cell from the same substrate was measured.26 As shown in previous publications, the low energy region of the PCS gives information about the charge transfer (CT) absorption from the HOMO level of the polymer donor to the LUMO of the fullerene acceptor, while the higher energy region corresponds to bulk exciton absorption. The exponentially decreasing portion of the CT absorption corresponds to transitions from band tail states and hence provides a measure of the band tail slope (see Ref 25, Supporting Information). The lower energy region of the PCS spectra below the band tail transitions corresponds to optical excitations from deep traps. Hence the PCS measurement provides additional data on these two types of states and can be compared to the capacitance data.



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Figure 7. Photocurrent spectroscopy before (red) and after (blue) light soaking for the same samples as the C-ω data. The qualitative similarity between the PCS spectra and the capacitance data is obvious. All the cells show evidence of deep state transitions before light soaking and there is an obvious increase in intensity after light soaking, while maintaining roughly the same spectral shape. In contrast, there is no observable change in the region of the band tail absorption as a result of light soaking. The increase in trap photocurrent with light soaking is about a factor 2-10, similar to the increase measured by capacitance. However the correlation between the capacitance and photocurrent data is not particularly good when looked at in more detail. Partly this is because the trap state absorption spectra have different shapes and so the comparison is difficult to make. Also, the photocurrent arises from absorption at the BHJ interfaces while the capacitance arises from traps anywhere in the bulk of the BHJ, and so a different microstructure can lead to different relative DOS values of PCS and C-ω from one material to the next. 16 ACS Paragon Plus Environment

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4 Discussion The present data adds to previous studies that show deep trap states in BHJ solar cells that increase with prolonged exposure to radiation. Deep traps and the effects of light soaking have been observed by Samiee et al using similar experimental techniques,8 and our data for PTB7:PCBM are similar to theirs. Previously we have shown that radiation-induced deep traps cause observable additional recombination, as is typical of deep traps.13 Those measurements used the photocurrent spectroscopy which measures the relative trap density but not the absolute value. The capacitance adds the trap density information from which we can estimate trapping parameters, and this is discussed in 4.2. Section 4.1 discusses the value of the thermal emission rate prefactor from which the energy scale is obtained. 4.1 The thermal emission prefactor and the energy scale As noted above, the energy scale for the traps measured by capacitance depends on the choice of the thermal excitation prefactor ω0 in eq. 2. One test of the choice is the comparison of the C-ω data with other information about the DOS. The unilluminated data for two devices for which the capacitance data give extended data for the band tail state DOS are replotted in Fig 8a on a vertical and horizontal scale that includes the band edge DOS, obtained from earlier work.25 The density of states in the polymer HOMO band is given by density functional calculations, and both PCS data and transient photoconductivity give a slope of 45 meV for the band tail of PCDTBT:PCBM.14 In the other example of PBDTTDPP, the band tail slope measured by PCS is 30 meV. The band tail DOS for each are shown in the figure and the zero of the energy scale is set by the transport energy which is positioned at the top of the band tail. The capacitance measurements line up well to give a consistent and continuous band tail DOS over the whole energy range. A large change in the prefactor from the chosen value would shift the energy 17 ACS Paragon Plus Environment


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scale, and a substantial shift in either direction would lead to a DOS that does not line up so well. Hence the prefactor choice of ω0=1012 s-1 seems to be correct to within an order of magnitude or better. Figure 8a also shows that the exponential band tail extends over a wide range of DOS values from 1020 cm-3eV-1 near the transport energy to 1016 cm-3eV-1. The agreement between the band tail slope as measured by C-ω and photocurrent spectroscopy is also evidence that the C-ω data at high frequency is not significantly affected by series resistance.

Figure 8. (a) DOS data from C-ω measurements for two solar cells (color) compared to the band tail DOS from other measurements and the band edge DOS from theoretical calculation, showing consistency in the energy scale. (b) C-ω data for GeIDT:PCBM at two measurement temperatures and the derived DOS (inset). In principle, the prefactor can also be estimated from the temperature dependence of the capacitance, through the effect of temperature on the trap energy according to Eq. 2. Elevated temperature shifts the capacitance arising from a specific trap energy to higher frequency. Figure 8b shows measurements of C-ω on one of the other cells, at two temperatures and the DOS model that fits the data. The capacitance data is shifted to higher frequency as expected, and the deep trap DOS is the same for the two data sets, indicating that the assumed prefactor is roughly correct. The band tail DOS is shifted slightly which might suggest a different prefactor. However a more likely explanation is that the analysis according to Eq. 1 introduces a thermal 18 ACS Paragon Plus Environment

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broadening of a rapidly changing DOS, and the exponential band tail slope in several of the measured devices is only ~30 meV. Given the limited operational temperature range, this method of obtaining the prefactor is not very accurate and so was not measured on further devices. The comparison of the optical and capacitance data provides further information on the energy scale of the deep states. The optical transition energy is not affected by the thermal excitation prefactor and therefore can provide an independent measurement of the defect trap energy. The PCS data all show a deep defect transition with an onset energy of about 0.6-0.8 eV, for devices for which EGI is 1.1 to 1.4 eV. The measurements are consistent with peak trap depths of ~0.5-0.7 eV, as measured by capacitance. Figure 9a and b show this comparison in a combined plot of the PCS and capacitance spectra for two different cells fabricated from PTB7 and PCDTBT. A band gap state with trap energy ET is expected to have a transition to the opposite band edge with an onset at EGI-ET. The absorption spectra is a convolution with the density of states in the band and so the absorption tends to be monotonically increasing at higher energy. Hence the absorption spectra is expected to have a similar shape to the trap DOS on the low energy side but to be different on the high energy side because of the convolution. The capacitance spectra in Fig 9a and b correspond to the light soaked state and have been replotted as EGI-ET with EGI chosen to match the low energy regions of the band tail and deep trap regions of the PCS and capacitance data. The comparison shows that the two measurements give roughly consistent DOS distributions, again suggesting that the assumed 1012 s-1 thermal excitation prefactor is approximately correct. This method is also only approximate. The optical transition is between the broad defect band and the band edge density of states, which is not known accurately. There may also be an 19 ACS Paragon Plus Environment


energy-dependent optical matrix element. Nevertheless, the results in Fig 9 demonstrate at least consistency with the assumed thermal excitation prefactor.

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Figure 9. Comparison of the photocurrent spectra (black) and the DOS from C-ω measurements (grey), adjusted as described in the text, for (a) PTB7:PCBM and (b) PCDTBT:PCBM. Closed data points are measured data and crosses are extrapolations of the data using the model DOS. 4.2 Trapping parameters. The distance traveled by a carrier in a uniform electric field E is µτE where µ and τ are the mobility and trapping lifetime. Carriers are collected at the electrodes with high probability when µτE>>d in a device of thickness d, while most carriers are trapped when µτE

Capacitance Spectroscopy of Light Induced Trap States in Organic

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