Best‐practice DFT protocols for basic molecular computational chemistry
Nowadays, many chemical investigations are supported by routine calculations of molecular
structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share …
structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share …
Extended tight‐binding quantum chemistry methods
This review covers a family of atomistic, mostly quantum chemistry (QC) based
semiempirical methods for the fast and reasonably accurate description of large molecules …
semiempirical methods for the fast and reasonably accurate description of large molecules …
[HTML][HTML] Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package
This article summarizes technical advances contained in the fifth major release of the Q-
Chem quantum chemistry program package, covering developments since 2015. A …
Chem quantum chemistry program package, covering developments since 2015. A …
GFN2-xTB—An accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent …
An extended semiempirical tight-binding model is presented, which is primarily designed for
the fast calculation of structures and noncovalent interaction energies for molecular systems …
the fast calculation of structures and noncovalent interaction energies for molecular systems …
Automated exploration of the low-energy chemical space with fast quantum chemical methods
We propose and discuss an efficient scheme for the in silico sampling for parts of the
molecular chemical space by semiempirical tight-binding methods combined with a meta …
molecular chemical space by semiempirical tight-binding methods combined with a meta …
Pushing the frontiers of density functionals by solving the fractional electron problem
Density functional theory describes matter at the quantum level, but all popular
approximations suffer from systematic errors that arise from the violation of mathematical …
approximations suffer from systematic errors that arise from the violation of mathematical …
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 …
r2SCAN-3c: A “Swiss army knife” composite electronic-structure method
The recently proposed r 2 SCAN meta-generalized-gradient approximation (mGGA) of
Furness and co-workers is used to construct an efficient composite electronic-structure …
Furness and co-workers is used to construct an efficient composite electronic-structure …
A generally applicable atomic-charge dependent London dispersion correction
The so-called D4 model is presented for the accurate computation of London dispersion
interactions in density functional theory approximations (DFT-D4) and generally for atomistic …
interactions in density functional theory approximations (DFT-D4) and generally for atomistic …
PhysNet: A neural network for predicting energies, forces, dipole moments, and partial charges
In recent years, machine learning (ML) methods have become increasingly popular in
computational chemistry. After being trained on appropriate ab initio reference data, these …
computational chemistry. After being trained on appropriate ab initio reference data, these …