Computational chemistry is particularly helpful in the realm of thermo-chemical and kinetic reactions. Typically, these reactions would be expensive, energy-intensive, potentially dangerous or impossible to carry out but computational chemistry allows for the generation of data whilst bypassing those unwanted factors. Moreover, mechanisms can often only be inferred from indirect evidence, while computational chemistry provides a direct route to it. The practice is particularly helpful in the pharmaceutical industry in the design of new drugs, the agricultural sector in the design of pesticides and is being used in the clean energy sector to develop improved energy-capturing technologies.
The research field looks to increase the accuracy and efficiency of calculations and increase its reliability and validity as an independent source of experimental data. This collection aims to collate recent and novel work that focuses on all aspects of computational chemistry. Potential topics that can be submitted to this collection include, but are not limited to, the following:
- Ab-initio wavefunction theory
- Density Functional Theory
- Biomolecular dynamics & enzyme design
- Structure-property relationships
- Photochemistry and excited states
- Force field development and solvation models
- Machine learning in chemistry
- Chemical bonding
- Reaction mechanisms and potential energy surface explorations
- Quantum dynamics
- Statistical mechanics, including non-equilibrium statistical mechanics
- Macromolecular structure prediction and dynamics
- Computer-aided molecular design and modelling