Feature-Assisted Machine Learning for Predicting Band Gaps of Binary Semiconductors

The band gap is a key parameter in semiconductor materials that is essential for advancing optoelectronic device development. Accurately predicting band gaps of materials at low cost is a significant challenge in materials science. Although many machine learning (ML) models for band gap prediction a...

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Detalhes bibliográficos

Principais autores:	Sitong Huo, Shuqing Zhang, Qilin Wu, Xinping Zhang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2024-02-01
coleção:	Nanomaterials
Assuntos:	machine learning SISSO insightful prediction band gap binary semiconductors
Acesso em linha:	https://www.mdpi.com/2079-4991/14/5/445
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