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 …
From DFT to machine learning: recent approaches to materials science–a review
Recent advances in experimental and computational methods are increasing the quantity
and complexity of generated data. This massive amount of raw data needs to be stored and …
and complexity of generated data. This massive amount of raw data needs to be stored and …
Efficient evaluation of electrostatic potential with computerized optimized code
J Zhang, T Lu - Physical Chemistry Chemical Physics, 2021 - pubs.rsc.org
The evaluation of molecular electrostatic potential (ESP) is a performance bottleneck for
many computational chemical tasks like restrained ESP charge fitting or quantum …
many computational chemical tasks like restrained ESP charge fitting or quantum …
Reunderstanding aqueous Zn electrochemistry from interfacial specific adsorption of solvation structures
Although sulfate-and sulfonate-based electrolytes have been widely used in the study of
aqueous zinc-ion batteries (AZIBs), discrepancies in the faradaic reaction kinetics of cation …
aqueous zinc-ion batteries (AZIBs), discrepancies in the faradaic reaction kinetics of cation …
Late-stage diversification of indole skeletons through nitrogen atom insertion
Compared with peripheral late-stage transformations mainly focusing on carbon–hydrogen
functionalizations, reliable strategies to directly edit the core skeleton of pharmaceutical lead …
functionalizations, reliable strategies to directly edit the core skeleton of pharmaceutical lead …
QuantumATK: an integrated platform of electronic and atomic-scale modelling tools
QuantumATK is an integrated set of atomic-scale modelling tools developed since 2003 by
professional software engineers in collaboration with academic researchers. While different …
professional software engineers in collaboration with academic researchers. While different …
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 …
Accurate crystal structures and chemical properties from NoSpherA2
The relationship between the structure and the properties of a drug or material is a key
concept of chemistry. Knowledge of the three-dimensional structure is considered to be of …
concept of chemistry. Knowledge of the three-dimensional structure is considered to be of …
New advances in using Raman spectroscopy for the characterization of catalysts and catalytic reactions
C Hess - Chemical Society Reviews, 2021 - pubs.rsc.org
Gaining insight into the mode of operation of heterogeneous catalysts is of great scientific
and economic interest. Raman spectroscopy has proven its potential as a powerful …
and economic interest. Raman spectroscopy has proven its potential as a powerful …
OctaDist: a tool for calculating distortion parameters in spin crossover and coordination complexes
OctaDist is an interactive and visual program for determination of structural distortion in
octahedral coordination complexes such as spin crossover complexes, single-ion magnets …
octahedral coordination complexes such as spin crossover complexes, single-ion magnets …