A first-principles and machine-learning investigation on the electronic, photocatalytic, mechanical and heat conduction properties of nanoporous C<sub>5</sub>N monolayers-Reference-Cited by-同舟云学术

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

Published:2022 Issue:11 Volume:14 Page:4324-4333
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Mortazavi Bohayra¹²^ORCID,Shahrokhi Masoud³^ORCID,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

Link

http://pubs.rsc.org/en/content/articlepdf/2022/NR/D1NR06449E

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