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Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of Finite- Size Particles

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Autor(es):
de Mendonca, Joao Paulo A. ; Calderan, Felipe, V ; Lourenco, Tuanan C. ; Quiles, Marcos G. ; Da Silva, Juarez L. F.
Número total de Autores: 5
Tipo de documento: Artigo Científico
Fonte: JOURNAL OF CHEMICAL INFORMATION AND MODELING; v. 62, n. 22, p. 10-pg., 2022-10-27.
Resumo

Nanoclusters are remarkably promising for the capture and activation of small molecules for fuel production or as precursors for other chemicals of high commercial value. Since this process occurs under a wide variety of experimental conditions, an improved atomistic understanding of the stability and phase transitions of these systems will be key to the development of successful technological applications. In this work, we proposed a theoretical framework to explore the potential energy surface and configuration space of nanoclusters to map the most important morphologies presented by those systems and the phase transitions between them. A fully automated process was developed, which combines global opti-mization techniques, classical molecular dynamics, and unsupervised machine learning algorithms. To showcase these capabilities of the approach, we explored the example of copper nanoclusters (Cun) where n = 13, 38, 55, 75, 98, 102, and 147. We not only reported a graphical potential energy surface for each size, but also explored the topology of the configuration space via structural and thermodynamic analyses. The effect of size on the potential energy surface and the critical temperature for solid-liquid phase transitions were also reported, highlighting the impact of magic numbers on those quantities. (AU)

Processo FAPESP: 20/05329-4 - Seleção de moléculas representativas via aprendizado de máquina
Beneficiário:Felipe Vaiano Calderan
Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
Processo FAPESP: 18/21401-7 - EMU concedido no processo 2017/11631-2: cluster computacional de alto desempenho - ENIAC
Beneficiário:Juarez Lopes Ferreira da Silva
Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários
Processo FAPESP: 17/11631-2 - CINE: desenvolvimento computacional de materiais utilizando simulações atomísticas, meso-escala, multi-física e inteligência artificial para aplicações energéticas
Beneficiário:Juarez Lopes Ferreira da Silva
Modalidade de apoio: Auxílio à Pesquisa - Programa Centros de Pesquisa em Engenharia
Processo FAPESP: 19/23681-0 - De métodos ab initio até o contínuo para a busca de materiais para baterias de sódio-íon
Beneficiário:Tuanan da Costa Lourenço
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado