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Daniel G A Smith

Showing results (1-10 of 26) with videos related to

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Journal of Chemical Theory and Computation|November 22, 2015
Interactions between Methane and Polycyclic Aromatic Hydrocarbons: A High Accuracy Benchmark StudyDaniel G A Smith, Konrad Patkowski
Physical Chemistry Chemical Physics : PCCP|June 10, 2015
An accurate benchmark description of the interactions between carbon dioxide and polyheterocyclic aromatic compounds containing nitrogenSicheng Li, Daniel G A Smith, Konrad Patkowski
The Journal of Chemical Physics|July 15, 2022
Implementation of symmetry-adapted perturbation theory based on density functional theory and using hybrid exchange-correlation kernels for dispersion termsYi Xie, Daniel G A Smith, C David Sherrill
The Journal of Chemical Physics|May 3, 2018
First-order symmetry-adapted perturbation theory for multiplet splittingsKonrad Patkowski, Piotr S Żuchowski, Daniel G A Smith
The Journal of Chemical Physics|October 15, 2013
Highly accurate potential energy surface for the He-H2 dimerBrandon W Bakr, Daniel G A Smith, Konrad Patkowski
The Journal of Physical Chemistry Letters|May 21, 2016
Revised Damping Parameters for the D3 Dispersion Correction to Density Functional TheoryDaniel G A Smith, Lori A Burns, Konrad Patkowski, et al.
Journal of Chemical Theory and Computation|November 21, 2015
Basis Set Convergence of the Post-CCSD(T) Contribution to Noncovalent Interaction EnergiesDaniel G A Smith, Piotr Jankowski, Michał Slawik, et al.
The Journal of Chemical Physics|April 4, 2020
Efficient and automated computation of accurate molecular geometries using focal-point approximations to large-basis coupled-cluster theoryConstance E Warden, Daniel G A Smith, Lori A Burns, et al.
The Journal of Chemical Physics|July 3, 2020
Driving torsion scans with wavefront propagationYudong Qiu, Daniel G A Smith, Chaya D Stern, et al.
Journal of Chemical Theory and Computation|July 9, 2019
PES-Learn: An Open-Source Software Package for the Automated Generation of Machine Learning Models of Molecular Potential Energy SurfacesAdam S Abbott, Justin M Turney, Boyi Zhang, et al.
Pageof 3

Showing results (1-10 of 26) with videos related to

Sort By:
Pageof 3
Journal of Chemical Theory and Computation|November 22, 2015
Interactions between Methane and Polycyclic Aromatic Hydrocarbons: A High Accuracy Benchmark StudyDaniel G A Smith, Konrad Patkowski
Physical Chemistry Chemical Physics : PCCP|June 10, 2015
An accurate benchmark description of the interactions between carbon dioxide and polyheterocyclic aromatic compounds containing nitrogenSicheng Li, Daniel G A Smith, Konrad Patkowski
The Journal of Chemical Physics|July 15, 2022
Implementation of symmetry-adapted perturbation theory based on density functional theory and using hybrid exchange-correlation kernels for dispersion termsYi Xie, Daniel G A Smith, C David Sherrill
The Journal of Chemical Physics|May 3, 2018
First-order symmetry-adapted perturbation theory for multiplet splittingsKonrad Patkowski, Piotr S Żuchowski, Daniel G A Smith
The Journal of Chemical Physics|October 15, 2013
Highly accurate potential energy surface for the He-H2 dimerBrandon W Bakr, Daniel G A Smith, Konrad Patkowski
The Journal of Physical Chemistry Letters|May 21, 2016
Revised Damping Parameters for the D3 Dispersion Correction to Density Functional TheoryDaniel G A Smith, Lori A Burns, Konrad Patkowski, et al.
Journal of Chemical Theory and Computation|November 21, 2015
Basis Set Convergence of the Post-CCSD(T) Contribution to Noncovalent Interaction EnergiesDaniel G A Smith, Piotr Jankowski, Michał Slawik, et al.
The Journal of Chemical Physics|April 4, 2020
Efficient and automated computation of accurate molecular geometries using focal-point approximations to large-basis coupled-cluster theoryConstance E Warden, Daniel G A Smith, Lori A Burns, et al.
The Journal of Chemical Physics|July 3, 2020
Driving torsion scans with wavefront propagationYudong Qiu, Daniel G A Smith, Chaya D Stern, et al.
Journal of Chemical Theory and Computation|July 9, 2019
PES-Learn: An Open-Source Software Package for the Automated Generation of Machine Learning Models of Molecular Potential Energy SurfacesAdam S Abbott, Justin M Turney, Boyi Zhang, et al.
Pageof 3