A stochastic modeling of morphology formation by optical near-field processes
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We previously reported (S. Yukutake et al. in Appl. Phys. B 99:415, 2010) that by depositing Ag particles on the electrode of a photovoltaic device composed of poly(3-hexylthiophene) (P3HT) and ZnO under light illumination (wavelength λ=660 nm) while reversely biasing the P3HT/ZnO p–n junction, a unique granular Ag film was formed. The resultant device generated a photocurrent at wavelengths as long as 670 nm, which is longer than the long-wavelength cutoff λ c (=570 nm) of P3HT. Such an effect originates from a phonon-assisted process induced by an optical near field. In this paper, we analyze the morphological character of the Ag clusters and build a stochastic model in order to understand the principles behind the self-organized pattern formation process. The modeling includes the geometrical character of the material, its associated optical near fields, and the materials that flow in and out of the system. The model demonstrates behavior consistent with that observed in the experiment. We can see these phenomena as a new kind of self-organized criticality taking account of near-field effects, which will provide an insight into the analysis and design of future nanophotonic devices.
KeywordsPhotovoltaic Device Cluster Area Reverse Bias Voltage Incidence Pattern Photocurrent Generation