Combining machine learning and computational chemistry for predictive insights into chemical systems
Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …
by dramatically accelerating computational algorithms and amplifying insights available from …
Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals
N Mardirossian, M Head-Gordon - Molecular physics, 2017 - Taylor & Francis
In the past 30 years, Kohn–Sham density functional theory has emerged as the most popular
electronic structure method in computational chemistry. To assess the ever-increasing …
electronic structure method in computational chemistry. To assess the ever-increasing …
[HTML][HTML] PSI4 1.4: Open-source software for high-throughput quantum chemistry
DGA Smith, LA Burns, AC Simmonett… - The Journal of …, 2020 - pubs.aip.org
PSI4 is a free and open-source ab initio electronic structure program providing
implementations of Hartree–Fock, density functional theory, many-body perturbation theory …
implementations of Hartree–Fock, density functional theory, many-body perturbation theory …
Realistic phase diagram of water from “first principles” data-driven quantum simulations
Since the experimental characterization of the low-pressure region of water's phase diagram
in the early 1900s, scientists have been on a quest to understand the thermodynamic …
in the early 1900s, scientists have been on a quest to understand the thermodynamic …
[HTML][HTML] ωB97M-V: A combinatorially optimized, range-separated hybrid, meta-GGA density functional with VV10 nonlocal correlation
N Mardirossian, M Head-Gordon - The Journal of chemical physics, 2016 - pubs.aip.org
A combinatorially optimized, range-separated hybrid, meta-GGA density functional with
VV10 nonlocal correlation is presented. The final 12-parameter functional form is selected …
VV10 nonlocal correlation is presented. The final 12-parameter functional form is selected …
Parmbsc1: a refined force field for DNA simulations
We present parmbsc1, a force field for DNA atomistic simulation, which has been
parameterized from high-level quantum mechanical data and tested for nearly 100 systems …
parameterized from high-level quantum mechanical data and tested for nearly 100 systems …
Advances in molecular quantum chemistry contained in the Q-Chem 4 program package
Y Shao, Z Gan, E Epifanovsky, ATB Gilbert… - Molecular …, 2015 - Taylor & Francis
A summary of the technical advances that are incorporated in the fourth major release of the
q-Chem quantum chemistry program is provided, covering approximately the last seven …
q-Chem quantum chemistry program is provided, covering approximately the last seven …
Computer modeling of halogen bonds and other σ-hole interactions
MH Kolar, P Hobza - Chemical reviews, 2016 - ACS Publications
In the field of noncovalent interactions a new paradigm has recently become popular. It
stems from the analysis of molecular electrostatic potentials and introduces a label, which …
stems from the analysis of molecular electrostatic potentials and introduces a label, which …
How accurate are the Minnesota density functionals for noncovalent interactions, isomerization energies, thermochemistry, and barrier heights involving molecules …
N Mardirossian, M Head-Gordon - Journal of chemical theory and …, 2016 - ACS Publications
The 14 Minnesota density functionals published between the years 2005 and early 2016 are
benchmarked on a comprehensive database of 4986 data points (84 data sets) involving …
benchmarked on a comprehensive database of 4986 data points (84 data sets) involving …
Semiempirical quantum mechanical methods for noncovalent interactions for chemical and biochemical applications
Semiempirical (SE) methods can be derived from either Hartree–Fock or density functional
theory by applying systematic approximations, leading to efficient computational schemes …
theory by applying systematic approximations, leading to efficient computational schemes …