Litcius/Paper detail

Multiscale Computational Approaches toward the Understanding of Materials

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

2022Advanced Theory and Simulations22 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Computer scienceNanotechnologySelection (genetic algorithm)Biochemical engineeringSoftware deploymentComputational modelManagement scienceSystems engineeringMaterials scienceArtificial intelligenceEngineeringSoftware engineeringZeolite Catalysis and SynthesisMachine Learning in Materials ScienceCatalysis and Oxidation Reactions