Efficient high-throughput method utilizing neural network potentials to calculate interaction energies, validated by clean transfer experiment of CVD graphene with polymer mixtures-Reference-Cited by-同舟云学术

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Efficient high-throughput method utilizing neural network potentials to calculate interaction energies, validated by clean transfer experiment of CVD graphene with polymer mixtures

Published:2024-10 Issue: Volume:229 Page:119336
ISSN:0008-6223
Container-title:Carbon
language:en
Short-container-title:Carbon

Author:

Averitt Jared Keith^ORCID,Pourianejad Sajedeh^ORCID,Ayodele Olubunmi O.^ORCID,Schmidt Kirby^ORCID,Trofe Anthony^ORCID,Starobin Joseph^ORCID,Ignatova Tetyana^ORCID

Publisher

Elsevier BV

Reference72 articles.

1. Interfacial adhesion between graphene and silicon dioxide by density functional theory with vdW corrections;Gao;J. Phys. D: Appl. Phys.,2014

2. Adsorption of poly(ethylene succinate) chain onto graphene nanosheets: A molecular simulation;Kelich;J. Mol. Graph. Model.,2016

3. The classical molecular dynamics simulation of graphene on Ru(0001) using a fitted Tersoff interface potential;Süle;Surf. Interface Anal.,2014

4. Interactions between large molecules pose a puzzle for reference quantum mechanical methods;Al-Hamdani;Nature Commun.,2021

5. Paraffin-enabled graphene transfer;Leong;Nature Commun.,2019

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