Literature DB >> 33469007

Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature.

Huziel E Sauceda1,2,3, Valentin Vassilev-Galindo4, Stefan Chmiela5, Klaus-Robert Müller6,7,8,9, Alexandre Tkatchenko10.   

Abstract

Nuclear quantum effects (NQE) tend to generate delocalized molecular dynamics due to the inclusion of the zero point energy and its coupling with the anharmonicities in interatomic interactions. Here, we present evidence that NQE often enhance electronic interactions and, in turn, can result in dynamical molecular stabilization at finite temperature. The underlying physical mechanism promoted by NQE depends on the particular interaction under consideration. First, the effective reduction of interatomic distances between functional groups within a molecule can enhance the n → π* interaction by increasing the overlap between molecular orbitals or by strengthening electrostatic interactions between neighboring charge densities. Second, NQE can localize methyl rotors by temporarily changing molecular bond orders and leading to the emergence of localized transient rotor states. Third, for noncovalent van der Waals interactions the strengthening comes from the increase of the polarizability given the expanded average interatomic distances induced by NQE. The implications of these boosted interactions include counterintuitive hydroxyl-hydroxyl bonding, hindered methyl rotor dynamics, and molecular stiffening which generates smoother free-energy surfaces. Our findings yield new insights into the versatile role of nuclear quantum fluctuations in molecules and materials.

Entities:  

Year:  2021        PMID: 33469007      PMCID: PMC7815839          DOI: 10.1038/s41467-020-20212-1

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  47 in total

1.  Local and tunable n-->pi* interactions regulate amide isomerism in the peptoid backbone.

Authors:  Benjamin C Gorske; Brent L Bastian; Grant D Geske; Helen E Blackwell
Journal:  J Am Chem Soc       Date:  2007-07-03       Impact factor: 15.419

2.  Accurate molecular van der Waals interactions from ground-state electron density and free-atom reference data.

Authors:  Alexandre Tkatchenko; Matthias Scheffler
Journal:  Phys Rev Lett       Date:  2009-02-20       Impact factor: 9.161

3.  Nuclear Quantum Effects in Hydrophobic Nanoconfinement.

Authors:  Buddha Ratna Shrestha; Sreekiran Pillai; Adriano Santana; Stephen H Donaldson; Tod A Pascal; Himanshu Mishra
Journal:  J Phys Chem Lett       Date:  2019-09-06       Impact factor: 6.475

4.  Psi4NumPy: An Interactive Quantum Chemistry Programming Environment for Reference Implementations and Rapid Development.

Authors:  Daniel G A Smith; Lori A Burns; Dominic A Sirianni; Daniel R Nascimento; Ashutosh Kumar; Andrew M James; Jeffrey B Schriber; Tianyuan Zhang; Boyi Zhang; Adam S Abbott; Eric J Berquist; Marvin H Lechner; Leonardo A Cunha; Alexander G Heide; Jonathan M Waldrop; Tyler Y Takeshita; Asem Alenaizan; Daniel Neuhauser; Rollin A King; Andrew C Simmonett; Justin M Turney; Henry F Schaefer; Francesco A Evangelista; A Eugene DePrince; T Daniel Crawford; Konrad Patkowski; C David Sherrill
Journal:  J Chem Theory Comput       Date:  2018-06-11       Impact factor: 6.006

5.  Perspective: Machine learning potentials for atomistic simulations.

Authors:  Jörg Behler
Journal:  J Chem Phys       Date:  2016-11-07       Impact factor: 3.488

6.  A DNA methylation reader complex that enhances gene transcription.

Authors:  C Jake Harris; Marion Scheibe; Somsakul Pop Wongpalee; Wanlu Liu; Evan M Cornett; Robert M Vaughan; Xueqin Li; Wei Chen; Yan Xue; Zhenhui Zhong; Linda Yen; William D Barshop; Shima Rayatpisheh; Javier Gallego-Bartolome; Martin Groth; Zonghua Wang; James A Wohlschlegel; Jiamu Du; Scott B Rothbart; Falk Butter; Steven E Jacobsen
Journal:  Science       Date:  2018-12-07       Impact factor: 47.728

7.  Bypassing the Kohn-Sham equations with machine learning.

Authors:  Felix Brockherde; Leslie Vogt; Li Li; Mark E Tuckerman; Kieron Burke; Klaus-Robert Müller
Journal:  Nat Commun       Date:  2017-10-11       Impact factor: 14.919

8.  The n→π* Interaction.

Authors:  Robert W Newberry; Ronald T Raines
Journal:  Acc Chem Res       Date:  2017-07-23       Impact factor: 22.384

9.  Reciprocal carbonyl-carbonyl interactions in small molecules and proteins.

Authors:  Abdur Rahim; Pinaki Saha; Kunal Kumar Jha; Nagamani Sukumar; Bani Kanta Sarma
Journal:  Nat Commun       Date:  2017-07-19       Impact factor: 14.919

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  7 in total

1.  BIGDML-Towards accurate quantum machine learning force fields for materials.

Authors:  Huziel E Sauceda; Luis E Gálvez-González; Stefan Chmiela; Lauro Oliver Paz-Borbón; Klaus-Robert Müller; Alexandre Tkatchenko
Journal:  Nat Commun       Date:  2022-06-29       Impact factor: 17.694

2.  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

Review 3.  Dynamics & Spectroscopy with Neutrons-Recent Developments & Emerging Opportunities.

Authors:  Kacper Drużbicki; Mattia Gaboardi; Felix Fernandez-Alonso
Journal:  Polymers (Basel)       Date:  2021-04-29       Impact factor: 4.329

4.  Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting.

Authors:  Stephan Thaler; Julija Zavadlav
Journal:  Nat Commun       Date:  2021-11-25       Impact factor: 14.919

5.  Low-Barrier Hydrogen Bond in Fujikurin A-D: A Computational Study.

Authors:  Hikaru Tanaka; Kazuaki Kuwahata; Masanori Tachikawa; Taro Udagawa
Journal:  ACS Omega       Date:  2022-04-15

6.  How Robust Is the Reversible Steric Shielding Strategy for Photoswitchable Organocatalysts?

Authors:  Simone Gallarati; Raimon Fabregat; Veronika Juraskova; Theo Jaffrelot Inizan; Clemence Corminboeuf
Journal:  J Org Chem       Date:  2022-06-28       Impact factor: 4.198

7.  Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems.

Authors:  John A Keith; Valentin Vassilev-Galindo; Bingqing Cheng; Stefan Chmiela; Michael Gastegger; Klaus-Robert Müller; Alexandre Tkatchenko
Journal:  Chem Rev       Date:  2021-07-07       Impact factor: 60.622

  7 in total

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