Literature DB >> 34045704

Electronic-structure methods for materials design.

Nicola Marzari1, Andrea Ferretti2, Chris Wolverton3.   

Abstract

The accuracy and efficiency of electronic-structure methods to understand, predict and design the properties of materials has driven a new paradigm in research. Simulations can greatly accelerate the identification, characterization and optimization of materials, with this acceleration driven by continuous progress in theory, algorithms and hardware, and by adaptation of concepts and tools from computer science. Nevertheless, the capability to identify and characterize materials relies on the predictive accuracy of the underlying physical descriptions, and on the ability to capture the complexity of realistic systems. We provide here an overview of electronic-structure methods, of their application to the prediction of materials properties, and of the different strategies employed towards the broader goals of materials design and discovery.

Year:  2021        PMID: 34045704     DOI: 10.1038/s41563-021-01013-3

Source DB:  PubMed          Journal:  Nat Mater        ISSN: 1476-1122            Impact factor:   43.841


  5 in total

1.  Gaussian Process Regression for Materials and Molecules.

Authors:  Volker L Deringer; Albert P Bartók; Noam Bernstein; David M Wilkins; Michele Ceriotti; Gábor Csányi
Journal:  Chem Rev       Date:  2021-08-16       Impact factor: 60.622

2.  Numerically Precise Benchmark of Many-Body Self-Energies on Spherical Atoms.

Authors:  S Vacondio; D Varsano; A Ruini; A Ferretti
Journal:  J Chem Theory Comput       Date:  2022-05-13       Impact factor: 6.578

3.  Understanding Contact Electrification at Water/Polymer Interface.

Authors:  Yang Nan; Jiajia Shao; Morten Willatzen; Zhong Lin Wang
Journal:  Research (Wash D C)       Date:  2022-02-16

4.  Radiationless mechanism of UV deactivation by cuticle phenolics in plants.

Authors:  Ana González Moreno; Abel de Cózar; Pilar Prieto; Eva Domínguez; Antonio Heredia
Journal:  Nat Commun       Date:  2022-04-04       Impact factor: 14.919

5.  Gap Opening in Double-Sided Highly Hydrogenated Free-Standing Graphene.

Authors:  Maria Grazia Betti; Ernesto Placidi; Chiara Izzo; Elena Blundo; Antonio Polimeni; Marco Sbroscia; José Avila; Pavel Dudin; Kailong Hu; Yoshikazu Ito; Deborah Prezzi; Miki Bonacci; Elisa Molinari; Carlo Mariani
Journal:  Nano Lett       Date:  2022-03-16       Impact factor: 12.262

  5 in total

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