Literature DB >> 28272886

First-Principles Models for van der Waals Interactions in Molecules and Materials: Concepts, Theory, and Applications.

Jan Hermann1, Robert A DiStasio2, Alexandre Tkatchenko1,3.   

Abstract

Noncovalent van der Waals (vdW) or dispersion forces are ubiquitous in nature and influence the structure, stability, dynamics, and function of molecules and materials throughout chemistry, biology, physics, and materials science. These forces are quantum mechanical in origin and arise from electrostatic interactions between fluctuations in the electronic charge density. Here, we explore the conceptual and mathematical ingredients required for an exact treatment of vdW interactions, and present a systematic and unified framework for classifying the current first-principles vdW methods based on the adiabatic-connection fluctuation-dissipation (ACFD) theorem (namely the Rutgers-Chalmers vdW-DF, Vydrov-Van Voorhis (VV), exchange-hole dipole moment (XDM), Tkatchenko-Scheffler (TS), many-body dispersion (MBD), and random-phase approximation (RPA) approaches). Particular attention is paid to the intriguing nature of many-body vdW interactions, whose fundamental relevance has recently been highlighted in several landmark experiments. The performance of these models in predicting binding energetics as well as structural, electronic, and thermodynamic properties is connected with the theoretical concepts and provides a numerical summary of the state-of-the-art in the field. We conclude with a roadmap of the conceptual, methodological, practical, and numerical challenges that remain in obtaining a universally applicable and truly predictive vdW method for realistic molecular systems and materials.

Entities:  

Mesh:

Year:  2017        PMID: 28272886     DOI: 10.1021/acs.chemrev.6b00446

Source DB:  PubMed          Journal:  Chem Rev        ISSN: 0009-2665            Impact factor:   60.622


  39 in total

Review 1.  Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems.

Authors:  Paraskevi Gkeka; Gabriel Stoltz; Amir Barati Farimani; Zineb Belkacemi; Michele Ceriotti; John D Chodera; Aaron R Dinner; Andrew L Ferguson; Jean-Bernard Maillet; Hervé Minoux; Christine Peter; Fabio Pietrucci; Ana Silveira; Alexandre Tkatchenko; Zofia Trstanova; Rafal Wiewiora; Tony Lelièvre
Journal:  J Chem Theory Comput       Date:  2020-07-16       Impact factor: 6.006

2.  Water-mediated correlations in DNA-enzyme interactions.

Authors:  P Kurian; A Capolupo; T J A Craddock; G Vitiello
Journal:  Phys Lett A       Date:  2017-10-23       Impact factor: 2.654

3.  Accurate molecular polarizabilities with coupled cluster theory and machine learning.

Authors:  David M Wilkins; Andrea Grisafi; Yang Yang; Ka Un Lao; Robert A DiStasio; Michele Ceriotti
Journal:  Proc Natl Acad Sci U S A       Date:  2019-02-07       Impact factor: 11.205

4.  Are beryllium-containing biphenyl derivatives efficient anion sponges?

Authors:  Oriana Brea; Otilia Mó; Manuel Yáñez; M Merced Montero-Campillo; Ibon Alkorta; José Elguero
Journal:  J Mol Model       Date:  2017-12-18       Impact factor: 1.810

5.  Regiochemical Effects on the Carbohydrate Binding and Selectivity of Flexible Synthetic Carbohydrate Receptors with Indole and Quinoline Heterocyclic Groups.

Authors:  Khushabu Thakur; Milan A Shlain; Mateusz Marianski; Adam B Braunschweig
Journal:  European J Org Chem       Date:  2021-09-12

6.  A collection of forcefield precursors for metal-organic frameworks.

Authors:  Taoyi Chen; Thomas A Manz
Journal:  RSC Adv       Date:  2019-11-13       Impact factor: 4.036

7.  First-principles calculations of hybrid inorganic-organic interfaces: from state-of-the-art to best practice.

Authors:  Oliver T Hofmann; Egbert Zojer; Lukas Hörmann; Andreas Jeindl; Reinhard J Maurer
Journal:  Phys Chem Chem Phys       Date:  2021-03-25       Impact factor: 3.676

8.  Machine Learning Force Fields.

Authors:  Oliver T Unke; Stefan Chmiela; Huziel E Sauceda; Michael Gastegger; Igor Poltavsky; Kristof T Schütt; Alexandre Tkatchenko; Klaus-Robert Müller
Journal:  Chem Rev       Date:  2021-03-11       Impact factor: 60.622

9.  Stereoelectronic effects in stabilizing protein-N-glycan interactions revealed by experiment and machine learning.

Authors:  Maziar S Ardejani; Louis Noodleman; Evan T Powers; Jeffery W Kelly
Journal:  Nat Chem       Date:  2021-03-15       Impact factor: 24.427

10.  Interactions between large molecules pose a puzzle for reference quantum mechanical methods.

Authors:  Yasmine S Al-Hamdani; Péter R Nagy; Andrea Zen; Dennis Barton; Mihály Kállay; Jan Gerit Brandenburg; Alexandre Tkatchenko
Journal:  Nat Commun       Date:  2021-06-24       Impact factor: 14.919

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