TY - JOUR
T1 - Multiscale computational approaches towards the understanding of materials
AU - Bordonhos, Marta
AU - Galvão, Tiago L. P.
AU - Gomes, José R.B.
AU - Gouveia, José D.
AU - Jorge, Miguel
AU - Lourenço, Mirtha
AU - Pereira, José M.
AU - Pérez-Sánchez, Germán
AU - Pinto, Moisés L.
AU - Silva, Carlos M.
AU - Tedim, João
AU - Zêzere, Bruno
PY - 2022/11/27
Y1 - 2022/11/27
N2 - 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.
AB - 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.
KW - density functional theory
KW - molecular dynamics
KW - machine learning
KW - gas adsorption/separation
KW - corrosion protection
KW - heterogeneous catalysis
UR - https://onlinelibrary.wiley.com/journal/25130390
U2 - 10.1002/adts.202200628
DO - 10.1002/adts.202200628
M3 - Review article
SN - 2513-0390
VL - 6
JO - Advanced Theory and Simulations
JF - Advanced Theory and Simulations
IS - 10
M1 - 2200628
ER -