Abstract
Strain-induced polarization can control the wavelength of intersubband transition in piezo-phototronic transistor based on GaN/AlN quantum wells. Neural networks can be used for solving the wavelength because their hidden layers can accurately approximate any continuous functions. In this study, two feed-forward neural network (FNN) models have been developed for obtaining the wave functions of ground state and first excited state in piezo-phototronic GaN/AlN quantum well. This method provides an effective way of the numerical computation for design and optimization of piezotronic and piezo-phototronic devices.
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