Multiscale computational approaches towards the understanding of materials

Marta Bordonhos, Tiago L. P. Galvão, José R.B. Gomes, José D. Gouveia, Miguel Jorge, Mirtha Lourenço, José M. Pereira, Germán Pérez-Sánchez, Moisés L. Pinto, Carlos M. Silva, João Tedim, Bruno Zêzere

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Abstract

Herewith, an overview of the group's collaborative research efforts on the development and deployment of computational approaches to understand materials and tools at different length and time scales is presented. The techniques employed range from quantum mechanical approaches based on the density functional theory to classical atomistic and coarse-grained force field methods, targeting molecular systems composed of a few to several million atoms at different levels of detail. These new tools and molecular models are presented to the computational materials science community so they can be used in more realistic molecular modelling studies of the properties of materials and their dependence on subtle modifications of their structures. The review concludes by presenting a selection of recent computational case-studies oriented toward the understanding of the synthesis of materials, the interpretation of unexpected experimental results, the prediction of material properties, and the materials selection based on their characteristics for applications in areas such as gas adsorption/separation, corrosion protection, and catalysis.

Original languageEnglish
Number of pages24
JournalAdvanced Theory and Simulations
Early online date27 Nov 2022
DOIs
Publication statusE-pub ahead of print - 27 Nov 2022

Keywords

  • density functional theory
  • molecular dynamics
  • machine learning
  • gas adsorption/separation
  • corrosion protection
  • heterogeneous catalysis

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