Modeling and Simulation of Organic Photodetectors for Low Light Intensity Applications

IEEE TRANSACTIONS ON ELECTRON DEVICES, VOL. 60, NO. 6, JUNE 2013 1975 Modeling and Simulation of Organic Photodetectors for Low Light Intensity Applications Bogdan Vlad Popescu, Dan Horia Popescu, Paolo Lugli, Simone Locci, Francesco Arca, Sandro Francesco Tedde, Maria Sramek, and Oliver Hayden Abstract— In this paper, we investigate the dynamic response of two different bulk heterojunction organic photodetectors over a large illumination and frequency range. To our knowledge, there is no similar study that includes the nW/cm2 regime. Photocurrent transient measurements reveal that the interlayer at the hole-extracting electrode is critical for the device perfor- mance under ultralow illumination. Furthermore, we observe a nonlinear cutoff frequency behavior over the illumination range, which we attribute to interface-related phenomena. We perform a detailed simulation study of the transient response for the measured samples. Making use of a drift diffusion model that also takes into account charge trapping and detrapping effects, both in bulk and at material interfaces, we are able to successfully reproduce the measured transients. Based on our simulations, we propose an explanation for this effect: it can be attributed to the interplay between the potential landscape seen by the charge carriers and to the presence of a large concentration of interface trap states, as well as of fixed interface charges. The importance of smart interface engineering as a key factor for device optimization is also highlighted. Index Terms— Cutoff frequency, interface engineering, organic, photodetector bulk heterojunction, simulation, trap states. I. INTRODUCTION ORGANIC photodetectors (OPDs) have emerged in recentyears as one of the most promising applications for organic electronic devices mainly due to their low fabrication cost on flexible, plastic substrates [1]. Their performance has steadily improved, reaching extremely low dark currents, high rectification ratios, and high reproducibility [2]. One important aspect of the OPDs that still requires optimization is their dynamic response—the cutoff frequency needs to be increased Manuscript received February 8, 2013; revised March 25, 2013; accepted April 14, 2013. Date of current version May 16, 2013. This work was supported in part by the DFG Excellent Cluster Nanosystem Inititiative Munich, the TUM International Graduate School on Science and Engineering, and the TUM Graduate School. The review of this paper was arranged by Editor J. Huang. B. V. Popescu and D. H. Popescu are with the TUM Graduate School and the Institute for Nanoelectronics, Technical University Munich, Munich 80333, Germany (e-mail: [email protected]; [email protected]). P. Lugli and S. Locci are with the Institute for Nanoelectronics, Techni- cal University Munich, Munich D-80333, Germany (e-mail: [email protected]; [email protected]). F. Arca, S. F. Tedde, M. Sramek, and O. Hayden are with Siemens AG, Corporate Technology, Erlangen 91058, Germany (e-mail: francesco. [email protected]; [email protected]; maria.sramek@ siemens.com; [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TED.2013.2259239 in order to replace the standard silicon detectors in commercial applications [3]. In order to improve the dynamic behavior of OPDs, the understanding of all the relevant charge generation, transport, and extraction mechanisms is essential. Subsequently, the lim- iting processes can be identified and the device performance can be optimized. One valuable and versatile tool that can provide valuable information regarding the device physics, beside experimental measurements, is the use of computer- based physical simulations. Such studies of transport mechanisms in organic devices like solar cells and OPDs are still very limited. Most of the published results [4]–[6] focus on the quasistationary analysis of bulk heterojunctions (BHJs). Koster et al. [4] have simulated the current–voltage char- acteristic of OC1C10 PPV-PCBM BHJ solar cells achieving good agreement with measured samples. The model includes bimolecular recombination, temperature, and field-dependent generation of electron-hole pairs and it also accounts for space-charge effects. Mihailetchi et al. [5] have concentrated on the charge transport mechanism in P3HT:PCBM BHJ. With the help of numerical simulation, they prove that under short-circuit conditions the charge separation efficiency at the P3HT:PCBM interface can reach up to 90%; their results confirm the large values for the internal quantum efficiency reported by experimental measurements. Blakesley et al. [6] have modeled the effects of band bending at the organic polymer–metal interface, an important aspect for charge extraction in organic solar cells and photodetectors. Only very recently, transient drift diffusion (DD) simu- lations including trapping and detrapping effects have been presented. McNeill et al. [7] have included a single trap level in their simulation of polymer solar cells. With this simple model, they were able to reproduce measured photoresponses, at several light intensities, including the characteristic long persisting current tail. Christ et al. [8] focused on the role of multiple trap states in the nanosecond response of organic solar cells and photodiodes. Their simulations confirm that the long-lasting tail of the photocurrent in organic device can be attributed to a deep trap state with exponential distribution. However, none of the above cited studies examined the behavior of the cutoff frequency for organic photodiodes under varying illumination conditions, nor the dynamic response of such a device at ultralow illumination intensity—in the nW/cm2 regime. To our knowledge, no comparative study of the dynamic behavior of OPD structures has been performed 0018-9383/$31.00 © 2013 IEEE 1976 IEEE TRANSACTIONS ON ELECTRON DEVICES, VOL. 60, NO. 6, JUNE 2013 until now—able to cover almost five decades, both in fre- quency and in light intensity. Our simulations, based on a modified DD software [9], are intended to clarify the effects of different trap states types— bulk and interface—interface on the transient response of the various samples. This paper is organized as follows. Section II gives a brief description of the fabrication and characterization techniques used for the two samples and presents the measured pho- toresponses. Section III summarizes the simulation procedure and gives a few details on the set of equations that are numerically solved. The proposed models for the two devices are described in Section IV together with the simulation parameters. Simulated transient responses and current voltage characteristics are compared to measured data in Section V. Finally, the conclusion of our study is drawn in the last section. II. FABRICATION AND MEASUREMENTS The two samples under study in this paper are both BHJ photodetetectors, the only difference being the hole extraction interlayer (IL) between the BHJ and the transparent anode: poly(3, 4-ethylenedioxythiophene), poly(styrenesulfonate) (PEDOT:PSS) in the first case (sample 1) and poly(3- hexylthiophene) (P3HT) in the second case (sample 2). Here, we will briefly outline the fabrication and characterization steps. A more detailed description can be found elsewhere [10]. The fabrication steps are described in brief: a 5 × 5 cm2 glass serves as substrate for the OPDs on top of which the indium tin oxide (ITO), the transparent electrode, is deposited. An extra step is performed in order to lower the dark currents: the electrode rims are coated by a transparent photoresist (SU-8) and the electrode active area is defined via standard photolithography (1 cm2). After the subsequent photoresist backing (15 min at 200 °C), acetone, isopropanol, and deion- ized water are used to clean the substrate. Reactive ion etching plasma technique is employed for the activation of the ITO layer before further processing. Spin coating is the method of choice for the deposition of both layers, PEDOT:PSS and P3HT, resulting in thicknesses of around 150 nm and 70 nm. For the BHJ spray coating of a P3HT:PCBM (ratio 1:0.75) solution is used, resulting in an active layer thickness for both samples of around 500 nm. A short annealing step at 140 °C follows before finally evaporating the aluminum top contact (100-nm thick). The samples were characterized both in quasistatic and dynamic regime. For the IV characteristic, the anode is ramped between +2 V and −5 V (reverse bias) under a monochro- matic light source—wavelength of 532 nm—with an intensity of 780 μW/cm2; the same ramp is performed also under dark conditions [Fig. 1(a)]. A square pulse of light is used to examine the dynamic behavior of the devices. We vary the period of the optical excitation, from 10−2 to 104 Hz, and record the response of the photogenerated current. The measurements are repeated for light intensities ranging from 10−8 to almost 10−3 W/cm2. Two striking particularities can be observed when analyzing Fig. 1(b). First, a nonconstant cutoff frequency versus the light Fig. 1. (a) Measured I–V characteristic for samples 1 and 2 under dark conditions and at an illumination intensity of 780 μW/cm2. (b) Measured cutoff frequency versus light intensity for the two samples. intensity range, as opposed to standard Si PD. Second, there is a crossing point, indicating that the two samples have different dynamic behaviors. Since the only major difference between the samples is their hole extraction layer, we can argue that the difference of the cutoff frequency versus light intensity, for the two samples, must be attributed to an interface-related effect. In the following section, we carry out numerical simula- tions that can confirm our assumption and further clarify the underlying physics. III. SIMULATION METHODS Simulations are carried out using the Sentaurus device, a drift–diffusion simulator from Synopsys [11]. The electron and hole continuity equations are coupled with the Poisson equation ∇ · [ε∇V ] = q (n − p − N+D + N−A + qT ) (1) ∂n ∂ t = 1 q ∇ Jn + Gn − Rn (2) ∂p ∂ t = − 1 q ∇ Jp + G p − Rp (3) where ε is the electrical permittivity, N+D and N − A are the densities of ionized donors and acceptors, respectively, q is the unit charge, n and p are the electron/hole densities, respectively, and ρT is the trap density. According to the drift-diffusion model, the equations for electron and hole current densities are Jn = qnμn∇V + q Dn∇n (4) Jp = qpμp∇V − q Dp∇ p (5) where μn and μp are the electron and hole mobilities and Dn and Dp the carrier diffusion coefficients. The simulator also has the capability of including trap states with various distributions—for example constant, exponential or Gaussian—both in bulk materials or at material interfaces. Adding trap states in the simulated device will transform the Poisson equation into ∇·(ε∇ϕ) = q ( n− p−N+D + ∑ Et (NDt −nDt)− ∑ Et (NAt − pAt) ) . (6) The number of trapped electrons (holes) nDt (NAt ) is computed from the product of the trap concentration NDt POPESCU et al.: MODELING AND SIMULATION OF ORGANIC PHOTO DETECTORS 1977 (NAt ) and the occupation probability function for electrons (holes) fn ( f p). For each trap level, a balanced flow of the charge carriers from and into the trap level is assumed, which translates into the following time-dependent equation: dnt dt = σPvth NEt [p1(1 − fn)− p fn] − σnvth NEt [n(1 − fn)− n1 fn ] (7) where σnvth (σpvth) is the capture cross-section—thermal velocity product for electrons (holes). In the above equation, the n(1 − fn) and p fn terms describe the charge carrier flow into the trap while the other two terms n1 fn and p1(1 − fn) express the thermionic flow of charge carriers from the trap to the corresponding energy band. Some simplifications are performed in order to reduce simulation complexity and resource requirements. The mesh resolution needed to simulate a realistic BHJ would be in the nm range but the simulated device area must be approx. 1 cm2. Since only the highest occupied molecular orbital (HOMO) of the donor and the lowest unoccupied molecular orbital (LUMO) of the acceptor material are significant in the charge- transfer process after exciton separation, we model the BHJ as a virtual semiconductor with a bandgap determined by the P3HT HOMO and PCBM LUMO. This approach is presented in [12] and has proved its validity and accuracy in numerous other studies [4], [5], [13], [14]. A further simplification that we undertake is to assume that exciton dynamics occuron a timescale much shorter than the transport one and will not be the limiting process in the dynamic response [15]. Thus, every photogenerated exciton contributes an electron and a hole, an assumption confirmed by experimental evidences [4], [5]. IV. PROPOSED MODELS A. BHJ Model The important parameters used to simulate the P3HT:PCBM blend are summarized in Table I; they are in good agreement with values reported in the literature [4], [5], [14], [16]. Additionally, two bulk trap levels are introduced in order to duplicate both the steady-state and the dynamic device characteristics. For these bulk trap states, two commonly used distributions have been implemented, namely exponential and Gaussian, both for electron and holes. The Gaussian level is situated at 0.1 eV from midgap (can be considered a deep level, attributed to structural defects) while the exponential tail lies at 0.3 eV from the mid bandgap energy (shallow traps). Values of 3 · 1018 cm−3and 4 · 1018 cm−3 are chosen for the density of traps in the two levels, in the same range with measured trap state densities in literature [17]–[22]. The absorption coefficient for P3HT used to calculate the photogenerated carrier distributions is taken from [16]. B. PEDOT:PSS Interlayer Device The device with the PEDOT:PSS layer between the transpar- ent anode and the organic blend is the standard implementation for an OPD, and it has been thoroughly studied, mostly under TABLE I BULK HETEROJUNCTION PARAMETERS Parameter Symbol Value Bandgap Eg 1.01 eV Electron affinity χ 3.8 eV Density of states Nc/Nv 5.1020 cm−2 Electron mobility μn 5.10−4 cm2/V · s Hole mobility μp 5.10−5 cm2/V · s Dielectric constant ε 3 Absorption coefficient α 105 cm−1 Thickness t 500 nm normal (mW/cm2) operating conditions [2], [3]. However, the characterization of such a device under ultralow illumination condition has not been performed yet. As mentioned above from the measurements in Fig. 1, a strongly nonlinear and nonconstant cutoff frequency can be observed, and we attribute this behavior to an interface-related effect. Recent studies [6] have suggested that the presence of trap states due to energy disorder, especially at metal/organic semiconductor or organic semiconductor/organic semiconduc- tor interfaces, can lead to band-bending or the formation of surface dipoles. These effects can significantly influence the charge transport and charge injection/extraction at electrodes. Consequently, we add interface trap states [23], [24] and fixed charges [25] in the modeling of the PEDOT:PSS—virtual semiconductor interface. Two exponential trap distributions having the same concentration—8 · 1012 cm−2—are activated with an energy sigma of 0.1 eV. One trap level is situated at 0.2 eV from the valence band of the virtual semiconductor while the second one is deeper, at 0.4 eV. For the concentration of interface fixed charges, we use a value of 3 · 1011 cm−2, which is in the same range as the reported data. For the interlayer, the following parameters have been used: a valence band level at Ev = 4.95 eV and a hole mobility μh of 10−3cm2/V · s, similar to values reported in [24]. With this set of parameters, we were able to closely repro- duce the measured data of sample 1. C. P3HT Interlayer Device The second device that has been modeled and simulated uses the polymer P3HT instead of the PEDOT:PSS interlayer. We employ the same two exponential interface trap states as in the previous case but with a modified trap concentration: the number has been decreased to 6 · 1012 cm−2. Also the charges located at the interlayer/virtual semiconductor interface have been preserved in the model with a value of 3.5 · 1011 cm−2. These modifications are needed to better reproduce the mea- sured curves—as will be shown in Section V. The reduced concentration of interface trap states is in good agreement with experimental thermally stimulated current measurements recently presented in [10]. Measured values, given in [26] are used for the modeling of the P3HT interlayer: the LUMO level is assumed at 4.9 eV while the hole mobility μh is 10−4 cm2/V· s. 1978 IEEE TRANSACTIONS ON ELECTRON DEVICES, VOL. 60, NO. 6, JUNE 2013 Fig. 2. (a) Model of sample 1 consisting of an ITO anode, a PEDOT:PSS IL, photoactive layer, and aluminum cathode. (b) Measured versus simulated I–V characteristic under an illumination intensity of 276 μW/cm2 and dark conditions. Fig. 3. Measured versus simulated response of sample 1 under different illumination intensities and different frequencies of pulsed light. (a) Light intensity of 276 μW/cm2 and frequency of 500 Hz. (b) Light intensity of 185 nW/cm2 and frequency of 50 mHz. (c) Light intensity of 23 nW/cm2 and frequency of 5 Hz. (d) Light intensity of 185 nW/cm2 and frequency of 50 Hz. Another feature included in the model for this sample is the presence of a bulk trap state in the interlayer. In order to be consistent in the modeling of the organic interlayer, the trap level has identical energy distribution and depth as one of the trap levels present in the BHJ, namely the exponential one closer to the valence band. V. RESULTS AND DISCUSSION The first simulated results, for the PEDOT sample, are shown in Fig. 2. In the first picture, the modeled structure of the device is presented—it consists of a transparent ITO anode, the PEDOT interlayer, the virtual semiconductor (BHJ), and finally the Al cathode. A good overlap between the measured and the simulated current–voltage characteristic can be observed in Fig. 2(b), where the anode is ramped from +2 to −5 V. Obtaining a good fit for the steady-state analysis is critical since all further transient analyses are performed in reverse bias at −5 V; the dark current level needs to be well matched. Next, some selected transient curves are presented in Fig. 3—again measured versus simulated device performance. The selected curves are obtained at different light intensities, ranging from 23 nW/cm2 to 276 μW/cm2, while the period of the illumination pulse is varied as well. Fig. 4. Measured versus simulated Bode plot for sample 1 at three different illumination intensities. Examining the four shapes, we notice especially at low light intensity, a characteristic long-lasting photocurrent tail that suggests that charge carriers are still being extracted long after turnoff. These phenomena can be conveniently explained by the slow release of charge carriers from deep traps levels [7] within the bandgap, included in our model. An observation should be made at this point: since the hole mobility is over one order of magnitude lower than the electron mobility, the charge carriers that are responsible for the slow turnoff dynamics must be holes, as the electrons are being extracted faster under the applied electric field. This finding is in accordance with the results presented in [5]. From the curves plotted in Fig. 3, one can extract the Bode plot presented in Fig. 4. The cutoff frequency is the frequency that corresponds to the 3-dB attenuation point of the signal amplitude and, as it can be clearly seen, this frequency is not constant with the illumination intensity. Simulations indicate that solely bulk or interface trap states cannot reproduce the complex behavior of the cutoff frequency depicted in Fig. 4. Instead, we argue, based on our model, that the combined effect of both bulk and interface traps is responsible for it. We propose that the poor performance at ultralow light intensity must be attributed to the interface trap states density. Only few carriers are generated, all in the vicinity of the PEDOT:PSS/BHJ interface, the majority of these photogen- erated carriers get detained, and a slow emission process from deep traps follows, thus explaining the cutoff frequency at only a few Hz. At high light intensity, the number of generated carriers is large—sufficient to fill the interface trap states with no signif- icant impact on the measured current. The cutoff dynamics in this regime are dominated by the volume trap states resulting in 3-dB frequencies in the range of 104 Hz, typical for OPD, as previously reported in the literature [2]. Furthermore, we can conclude that the fast emission and capture rate of the shallow bulk trap states—the exponential tale—is the predominant dynamic process, as deeper traps have a high occupation probability. POPESCU et al.: MODELING AND SIMULATION OF ORGANIC PHOTO DETECTORS 1979 Fig. 5. (a) Model of sample 1 consisting of an ITO anode, a P3HT IL, photoactive layer, and aluminum cathode. (b) Measured versus simulated I–V characteristic under an illumination intensity of 276 μW/cm2 and dark conditions. Fig. 6. Measured versus simulated response of sample 2 under different illumination intensities and different frequencies of pulsed light. (a) Light intensity of 23 nW/cm2 and frequency of 50 Hz. (b) Light intensity of 185 nW/cm2 and frequency of 500 mHz. (c) Light intensity of 23 nW/cm2 and frequency of 5 Hz. (d) Light intensity of 276 μW/cm2 and frequency of 50 mHz. Fig. 5(a) shows the structure of the second sample, namely the one that uses P3HT as an interlayer. Again a measured and a simulated I–V curve are given in Fig. 5(b) and a good qualitative fit is obtained as well. The dynamic analysis follows with four selected transient photoresponses shown in Fig. 6. The difference in the cutoff frequency of the two samples— see Fig. 1—depending on the choice of the interlayer can be explained if we take into account the different interface trap states density. In addition, a further reason for the observed difference can be a band misalignment at the interface between the active material and the hole extraction layer (interlayer). This misalignment or small barrier [27] arises from the dif- ference in HOMO levels at the IL/BHJ interfaces in agreement with the Schottky–Mott model. According to the Schottky– Mott picture, the vacuum levels of the stacked (organic) materials will align themselves [28], [29]. Using the simulation parameters given above, a barrier of around 0.1 eV for sam- ple 2 and 0.15 eV for sample 1 can be computed. The presence of such a misalignment will hinder efficient charge extraction and will enhance trapping effects. Hence, we can provide two possible solutions in order to maximize the cutoff frequency at low light intensity: the interlayer with the optimal workfunction needs to be found and the number of trap states on the interface must be minimized through appropriate processing techniques. Fig. 7. Simulated dynamic response for the two samples. The simulated dynamic response over the entire illumination and frequency range is given in Fig. 7. For both samples, there is a nonconstant cutoff frequency with a more pronounced effect in the case of the PEDOT sample—qualitatively dupli- cating the measurements in Fig. 1. One concluding remark should be added at this point: all data used for the modeling and transient fitting were data obtained from single pulse measurement (that is, duty cycle 1%) whereas the amplitudes used to determine the dynamic response of Fig. 1(a) were extracted from continuous mode measurements (duty cycle 50%). While the P3HT sample behaves almost identical under the two operation modes, the same cannot be said about the PEDOT sample (effect visible also in measurements). We therefore performed train of pulses simulations, up to 30 pulses, with the limiting factor being simulation resources and time. Indeed a drift of the cutoff frequency toward higher fre- quency values, especially at intermediate illumination inten- sities, with increasing number of pulses can be noticed. The curve in Fig. 7 is extracted, as mentioned before, after 30 pulses, but it is plausible to assume that increasing the simulation time would have improved the agreement between measured and simulated responses even further. Our interpretation of the above presented results is the following: at intermediate intensities the trapping and slow detrapping from the interface trap states limits the dynamics of the device. At turn on, a trap-filling process takes place, and several light pulses are needed until the number of captured charge carriers reaches an equilibrium with those emitted from the near-midgap trap states. Since a sufficient number of carriers are generated, opposed to ultralow intensities, each new illumination pulse reduces the number of free trap states; as a result the amplitude of the photoresponse will slowly increase. No significant change in the amplitude can be noted at high light intensities. The dynamic equilibrium of the trapped charge carriers is reached almost immediately, and therefore any subsequent light pulse will not modify the trap occupation and the amplitude will remain constant. This effect is visible only for the PEDOT sample, mainly due to the presence of a larger barrier between the virtual 1980 IEEE TRANSACTIONS ON ELECTRON DEVICES, VOL. 60, NO. 6, JUNE 2013 semiconductor and the interlayer and an increased number of interface traps. VI. CONCLUSION In this paper, we performed an extensive simulation study for two measured OPDs. For this task, we employed a drift- diffusion simulator, which takes into account multiple trap- ping and detrapping effects in bulk, as well as at material interfaces. The nonlinear and nonconstant cutoff frequencies measured have been successfully duplicated. We identified several factors that are responsible for the observed behavior: the concentration, position, and distribution of trap states at the interface between the BHJ and the hole extraction layer, the number of fixed interface charges, and the band discontinuity at the same interface. Our results suggest that the choice of the hole extraction layer and the possible interface treatment can be critical, especially for the low-illumination applications. REFERENCES [1] A. C. Mayer, S. R. Scully, B. E. Hardin, M. W. Rowell, and M. D. McGe- hee, “Polymer-based solar cells,” Mater. Today, vol. 10, no. 11, pp. 28–33, Nov. 2007. [2] S.F. 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Milliron, J. Schwartz, and A. Kahn, “Organic semiconduc- tor interfaces: Electronic structure and transport properties,” Appl. Surf. Sci., vol. 166, nos. 1–4, pp. 354–362, Oct. 2000. [29] G. Dennler and N. S. Sariciftci, “Flexible conjugated polymer-based plastic solar cells: From basics to applications,” Proc. IEEE, vol. 93, no. 8, pp. 1429–1439, Aug. 2005. Bogdan Vlad Popescu is currently pursuing the Ph.D. degree with the Institute for Nanoelectronics, Technical University of Munich, Munich, Germany. His current research interests include the sim- ulation and modeling of nanostructures (InAs nanowires) and organic devices. Dan Horia Popescu is currently pursuing the Ph.D. degree with the Institute for Nanoelectronics, Tech- nical University of Munich, Munich, Germany. His current research interests include the simula- tion and modeling of transport mechanisms in high-k dielectrics and organic semiconductors. POPESCU et al.: MODELING AND SIMULATION OF ORGANIC PHOTO DETECTORS 1981 Paolo Lugli received the M.S. and Ph.D. degrees in electrical engineering from Colorado State Uni- versity, Fort Collins, CO, USA, in 1982 and 1985, respectively. He was a Head of the Institute for Nanoelectronics, Technical University of Munich, Munich, Germany, in 2003. Simone Locci received the M.S. and Ph.D. degrees from the University of Cagliari, Cagliari, Italy, in 2005 and 2009, respectively, both in electronic engi- neering. He is currently a Post-Doctoral Research Assis- tant with the Centre for Nanoelectronics, Technical University of Munich, Germany. Francesco Arca received the M.S. degree in elec- tronic engineering from the University of Cagliari, Cagliari, Italy, in 2008. He is currently pursuing the Ph.D. degree with Siemens AG, Erlangen, Germany. He joined Siemens AG in 2009. Sandro Francesco Tedde received the Ph.D. degree from the Department of Nanoelectronic, TU Munich, Munich, Germany. His current research interests include the integra- tion of organic photodetectors in different electronic systems such as biosensors, position sensing devices, and medical imaging systems. Maria Sramek received the Ph.D. degree in chemistry from the Department of Organic Chemistry, LMU Munich, Munich, Germany. She is now a Senior Key Expert Research Scientist with the Bio Science Research Group, Erlangen, Germany. Oliver Hayden received the Ph.D. degree in bio- chemistry and the venia docendi for analytical chem- istry from the University of Vienna, Vienna, Austria. His current research interests include organic semi- conductors and biosensors for medical imaging and in-vitro diagnostic applications. /ColorImageDict > /JPEG2000ColorACSImageDict > /JPEG2000ColorImageDict > /AntiAliasGrayImages false /CropGrayImages true /GrayImageMinResolution 150 /GrayImageMinResolutionPolicy /OK /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 600 /GrayImageDepth -1 /GrayImageMinDownsampleDepth 2 /GrayImageDownsampleThreshold 1.50000 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages false /GrayImageAutoFilterStrategy /JPEG /GrayACSImageDict > /GrayImageDict > /JPEG2000GrayACSImageDict > /JPEG2000GrayImageDict > /AntiAliasMonoImages false /CropMonoImages true /MonoImageMinResolution 400 /MonoImageMinResolutionPolicy /OK /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 1200 /MonoImageDepth -1 /MonoImageDownsampleThreshold 1.50000 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict > /AllowPSXObjects false /CheckCompliance [ /None ] /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly false /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile (None) /PDFXOutputConditionIdentifier () /PDFXOutputCondition () /PDFXRegistryName () /PDFXTrapped /False /Description > >> setdistillerparams > setpagedevice