Band gap and band alignment prediction of nitride-based semiconductors using machine learning-Reference-Cited by-同舟云学术

Band gap and band alignment prediction of nitride-based semiconductors using machine learning

Author:

Huang Yang¹²³⁴⁵,Yu Changyou⁶⁷³⁸⁵^ORCID,Chen Weiguang⁹¹⁰¹¹¹²⁵,Liu Yuhuai⁶⁷³⁸⁵,Li Chong¹²³⁴⁵,Niu Chunyao¹²³⁴⁵^ORCID,Wang Fei¹²³⁴⁵^ORCID,Jia Yu¹²³⁴⁵

Affiliation:

1. International Laboratory for Quantum Functional Materials of Henan

2. School of Physics and Engineering

3. Zhengzhou University

4. Zhengzhou 450001

5. China

6. National Center for International Joint Research of Electronic Materials and Systems

7. School of Information Engineering

8. Zhengzhou

9. Quantum Materials Research Center

10. College of Physics and Electronic Engineering

11. Zhengzhou Normal University

12. Zhengzhou 450044

Abstract

Machine learning has been utilized to accurately predict band gap and band alignment of wurtzite nitrides in a large design space.

Funder

National Natural Science Foundation of China

Zhengzhou University

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,General Chemistry

Link

Reference33 articles.

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