Theory of trap-controlled transient photoconduction

Schmidlin, F. W.

doi:10.1103/physrevb.16.2362

Cited by 450 publications

(159 citation statements)

References 24 publications

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“…The concepts introduced in the previous subsections allow us to use the E 0 max values from the simulated histograms to produce theoretical values of the diffusion coefficient according to eqn (7) and (8). The results, together with the simulated data and the predictions of the approximate formulas (6) and (9) can be found in Fig.…”

Section: E Simulated Diffusion Coefficient Versus Theoretical Predictmentioning

confidence: 97%

Random walk numerical simulation for hopping transport at finite carrier concentrations: diffusion coefficient and transport energy concept

Gonzalez-Vazquez

Anta

Bisquert

2009

Phys. Chem. Chem. Phys.

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The random walk numerical simulation (RWNS) method is used to compute diffusion coefficients for hopping transport in a fully disordered medium at finite carrier concentrations. We use Miller-Abrahams jumping rates and an exponential distribution of energies to compute the hopping times in the random walk simulation. The computed diffusion coefficient shows an exponential dependence with respect to Fermi-level and Arrhenius behavior with respect to temperature. This result indicates that there is a well-defined transport level implicit to the system dynamics. To establish the origin of this transport level we construct histograms to monitor the energies of the most visited sites. In addition, we construct ''corrected'' histograms where backward moves are removed. Since these moves do not contribute to transport, these histograms provide a better estimation of the effective transport level energy. The analysis of this concept in connection with the Fermi-level dependence of the diffusion coefficient and the regime of interest for the functioning of dye-sensitised solar cells is thoroughly discussed.

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Section: E Simulated Diffusion Coefficient Versus Theoretical Predictmentioning

confidence: 97%

Random walk numerical simulation for hopping transport at finite carrier concentrations: diffusion coefficient and transport energy concept

Gonzalez-Vazquez

Anta

Bisquert

2009

Phys. Chem. Chem. Phys.

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“…The density of states and consequently the defect density have been determined from PTPA. Within the framework of the multiple trapping model [67] of carrier transport in amorphous semiconductors the post-transit current depends on the re-emission of carriers from the traps. In the post-transit regime the carrier released at any time will immediately leave the sample.…”

Section: Measurementsmentioning

confidence: 99%

Integration of Expanding Thermal Plasma deposited Hydrogenated Amorphous Silicon in Solar Cells

et al. 2002

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A cascaded arc expanding thermal plasma is used to deposit intrinsic hydrogenated amorphous silicon at growth rates between 0.2 and 3 nm/s. Incorporation into a single junction p-i-n solar cell resulted in an initial efficiency of 6.7%, whereas all the optical and initial electrical properties of the individual layers are comparable with RF-PECVD deposited films. In this cell the intrinsic layer was deposited at 0.85 nm/s and at a deposition temperature of 250°C, which is the temperature limit for growing the p-i-n sequence. The cell efficiency is limited by the fill factor and using a buffer layer at the p-i interface deposited with RF-PECVD at low growth rate can increase this. The increase in fill factor is a result of a lower initial defect density near the p-i interface then obtained with the expanding thermal plasma, resulting in better charge carrier collection. To use larger growth rates, while maintaining the material properties, higher deposition temperatures are required. Higher deposition temperatures result in a smaller optical bandgap for the intrinsic layer and deterioration of the p-type layer, resulting in a lower opencircuit voltage. First results on applying a buffer layer will also be presented.

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“…These devices are normally based in mesoporous materials and nanocomposites. Anomalous or dispersive transport 1,2 features are usually observed in these materials, like extremely slow transport combined with density-dependent diffusion coefficients 3,4 and power-law instead of exponential decays. 5 Diffusion of electrons injected into mesoporous TiO 2 used in dye-sensitized solar cells (DSC) is one of the most studied examples.…”

Section: Introductionmentioning

confidence: 99%

Interpretation of diffusion coefficients in nanostructured materials from random walk numerical simulation

Anta

Mora‐Seró

Dittrich

et al. 2008

Phys. Chem. Chem. Phys.

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We make use of the numerical simulation random walk (RWNS) method to compute the ''jump'' diffusion coefficient of electrons in nanostructured materials via mean-square displacement. First, a summary of analytical results is given that relates the diffusion coefficient obtained from RWNS to those in the multiple-trapping (MT) and hopping models. Simulations are performed in a three-dimensional lattice of trap sites with energies distributed according to an exponential distribution and with a step-function distribution centered at the Fermi level. It is observed that once the stationary state is reached, the ensemble of particles follow Fermi-Dirac statistics with a well-defined Fermi level. In this stationary situation the diffusion coefficient obeys the theoretical predictions so that RWNS effectively reproduces the MT model. Mobilities can be also computed when an electrical bias is applied and they are observed to comply with the Einstein relation when compared with steady-state diffusion coefficients. The evolution of the system towards the stationary situation is also studied. When the diffusion coefficients are monitored along simulation time a transition from anomalous to trap-limited transport is observed. The nature of this transition is discussed in terms of the evolution of electron distribution and the Fermi level. All these results will facilitate the use of RW simulation and related methods to interpret steady-state as well as transient experimental techniques.

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Theory of trap-controlled transient photoconduction

Cited by 450 publications

References 24 publications

Random walk numerical simulation for hopping transport at finite carrier concentrations: diffusion coefficient and transport energy concept

Random walk numerical simulation for hopping transport at finite carrier concentrations: diffusion coefficient and transport energy concept

Integration of Expanding Thermal Plasma deposited Hydrogenated Amorphous Silicon in Solar Cells

Interpretation of diffusion coefficients in nanostructured materials from random walk numerical simulation

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