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

Author(s)

de Mendonca, Joao Paulo A. ; Calderan, Felipe, V ; Lourenco, Tuanan C. ; Quiles, Marcos G. ; Da Silva, Juarez L. F.

• Document type: Journal article
• Source: JOURNAL OF CHEMICAL INFORMATION AND MODELING; v. 62, n. 22, p. 10-pg., 2022-10-27.

Abstract

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)

• FAPESP's process: 20/05329-4 - Selection of representative molecules via machine learning
• Grantee: Felipe Vaiano Calderan
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• FAPESP's process: 18/21401-7 - Multi-User Equipment approved in grant 2017/11631-2: cluster computational de alto desempenho - ENIAC
• Grantee: Juarez Lopes Ferreira da Silva
• Support Opportunities: Multi-user Equipment Program
• FAPESP's process: 17/11631-2 - CINE: computational materials design based on atomistic simulations, meso-scale, multi-physics, and artificial intelligence for energy applications
• Grantee: Juarez Lopes Ferreira da Silva
• Support Opportunities: Research Grants - Research Centers in Engineering Program
• FAPESP's process: 19/23681-0 - From ab initio to continuum methods to the screening of sodium-ion battery materials
• Grantee: Tuanan da Costa Lourenço
• Support Opportunities: Scholarships in Brazil - Post-Doctoral