Efficient high-throughput method utilizing neural network potentials to calculate interaction energies, validated by clean transfer experiment of CVD graphene with polymer mixtures
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引用次数: 0
Abstract
In this study, we designed a computational model involving energy decomposition using ground state energy minimized geometries resulting from a general-purpose neural network potential (ANI-1ccx). The numerical simulations show a distribution of energies, which indicate a two-fold reduction in interaction energy and polarity shift in electrostatic interaction, highlighting the computational novelty in exploring over a million metastable configurations. Experimentally, we validate our model by observing that using a mixture of two distinct polymers in the wet transfer process reduces transfer-induced doping and strain on transferred CVD graphene compared to the conventional single polymer wet transfer method, primarily due to decreased polymer contamination from the transfer process. This reduction is linked to the decreased interaction energy in the mixture of polymethyl methacrylate and angelica lactone polymer on graphene.
期刊介绍:
The journal Carbon is an international multidisciplinary forum for communicating scientific advances in the field of carbon materials. It reports new findings related to the formation, structure, properties, behaviors, and technological applications of carbons. Carbons are a broad class of ordered or disordered solid phases composed primarily of elemental carbon, including but not limited to carbon black, carbon fibers and filaments, carbon nanotubes, diamond and diamond-like carbon, fullerenes, glassy carbon, graphite, graphene, graphene-oxide, porous carbons, pyrolytic carbon, and other sp2 and non-sp2 hybridized carbon systems. Carbon is the companion title to the open access journal Carbon Trends. Relevant application areas for carbon materials include biology and medicine, catalysis, electronic, optoelectronic, spintronic, high-frequency, and photonic devices, energy storage and conversion systems, environmental applications and water treatment, smart materials and systems, and structural and thermal applications.