Litcius/Paper detail

High-throughput computation of novel ternary B–C–N structures and carbon allotropes with electronic-level insights into superhard materials from machine learning

Mohammed Al‐Fahdi, Tao Ouyang, Ming Hu

2021Journal of Materials Chemistry A40 citationsDOI

Abstract

Novel carbon allotropes and ternary B–C–N structures with ultrahigh hardness were screened and proposed by high-throughput computation. Electronic-level insights into superhard materials were provided from machine learning.

Topics & Concepts

Ternary operationComputationThroughputMaterials scienceCarbon fibersComputational scienceNanotechnologyComputer scienceComposite materialAlgorithmComposite numberProgramming languageWirelessTelecommunicationsBoron and Carbon Nanomaterials ResearchMXene and MAX Phase MaterialsMetal and Thin Film Mechanics
High-throughput computation of novel ternary B–C–N structures and carbon allotropes with electronic-level insights into superhard materials from machine learning | Litcius