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Abstract
This research developed a computational pipeline to discover stable semiconductors by combining generative adversarial networks (GANs), classifiers, and high-throughput first-principles calculations. Using CubicGAN, a GAN-based algorithm for generating cubic materials, and a classifier to screen semiconductors, the study identified 12 stable AA'MH6 semiconductors in the F-43m space group. These semiconductors were found to be wide-bandgap, with BaSrZnH6 and KNaNiH6 exhibiting direct bandgaps while others showed indirect bandgaps. The research highlights the significant differences in properties between AA'MnH6 and NaYRuH6 compared to other AA'MH6 semiconductors.
Publisher
npj Computational Materials
Published On
Jan 31, 2022
Authors
Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Indika Perera, Jianjun Hu
Tags
semiconductors
generative adversarial networks
CubicGAN
stable materials
bandgap properties
high-throughput calculations
AA'MH6

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