Literature DB >> 34060549

Replacing hybrid density functional theory: motivation and recent advances.

Benjamin G Janesko1.   

Abstract

Density functional theory (DFT) is the most widely-used electronic structure approximation across chemistry, physics, and materials science. Every year, thousands of papers report hybrid DFT simulations of chemical structures, mechanisms, and spectra. Unfortunately, hybrid DFT's accuracy is ultimately limited by tradeoffs between over-delocalization and under-binding. This review summarizes these tradeoffs, and introduces six modern attempts to go beyond them while maintaining hybrid DFT's relatively low computational cost: DFT+U, self-interaction corrections, localized orbital scaling corrections, local hybrid functionals, real-space nondynamical correlation, and our rung-3.5 approach. The review concludes with practical suggestions for DFT users to identify and mitigate these tradeoffs' impact on their simulations.

Year:  2021        PMID: 34060549     DOI: 10.1039/d0cs01074j

Source DB:  PubMed          Journal:  Chem Soc Rev        ISSN: 0306-0012            Impact factor:   54.564


  6 in total

1.  Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost.

Authors:  Chenru Duan; Daniel B K Chu; Aditya Nandy; Heather J Kulik
Journal:  Chem Sci       Date:  2022-04-05       Impact factor: 9.969

2.  Data-Centric Architecture for Self-Driving Laboratories with Autonomous Discovery of New Nanomaterials.

Authors:  Maria A Butakova; Andrey V Chernov; Oleg O Kartashov; Alexander V Soldatov
Journal:  Nanomaterials (Basel)       Date:  2021-12-21       Impact factor: 5.076

3.  Assessment of Various Density Functional Theory Methods for Finding Accurate Structures of Actinide Complexes.

Authors:  Youngjin Kwon; Hee-Kyung Kim; Keunhong Jeong
Journal:  Molecules       Date:  2022-02-23       Impact factor: 4.411

Review 4.  Recent Advances in Cartesian-Grid DFT in Atoms and Molecules.

Authors:  Sangita Majumdar; Amlan K Roy
Journal:  Front Chem       Date:  2022-07-22       Impact factor: 5.545

Review 5.  A Review of Performance Prediction Based on Machine Learning in Materials Science.

Authors:  Ziyang Fu; Weiyi Liu; Chen Huang; Tao Mei
Journal:  Nanomaterials (Basel)       Date:  2022-08-26       Impact factor: 5.719

6.  Jahn-Teller Effects in a Vanadate-Stabilized Manganese-Oxo Cubane Water Oxidation Catalyst.

Authors:  Sebastian Mai; Marcus Holzer; Anastasia Andreeva; Leticia González
Journal:  Chemistry       Date:  2021-11-05       Impact factor: 5.020

  6 in total

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