A first-principles and machine-learning investigation on the electronic, photocatalytic, mechanical and heat conduction properties of nanoporous C5N monolayers

Author:

Mortazavi Bohayra12ORCID,Shahrokhi Masoud3ORCID,Shojaei Fazel4,Rabczuk Timon5,Zhuang Xiaoying15,Shapeev Alexander V.6

Affiliation:

1. Chair of Computational Science and Simulation Technology, Department of Mathematics and Physics, Leibniz Universität Hannover, Appelstraße 11, 30167 Hannover, Germany

2. Cluster of Excellence PhoenixD (Photonics, Optics, and Engineering – Innovation Across Disciplines), Gottfried Wilhelm Leibniz Universität Hannover, Hannover, Germany

3. Young Researchers Club, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

4. Department of Chemistry, Faculty of Nano and Bioscience and Technology, Persian Gulf University, Bushehr 75169, Iran

5. College of Civil Engineering, Department of Geotechnical Engineering, Tongji University, 1239 Siping Road, Shanghai, China

6. Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Bolshoy Bulvar, 30, Moscow, 143026, Russia

Abstract

Phononic thermal transport, mechanical/failure response, electronic, optical and photocatalytic properties of the C5N monolayer are explored using the density functional theory and machine-learning interatomic potentials.

Funder

Deutsche Forschungsgemeinschaft

Russian Science Foundation

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

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