Overview
Quantum-chemical and semi-empirical methods give electronic-level insight into molecules and reactions.
Salient features
- DFT geometry, energy and property calculations
- Reaction path and mechanism exploration
- Fast machine-learned potentials
Analyses we offer
DFT Studies
Runs density functional theory calculations for geometries, energies, spectra and reactivity.
Methods: pyscf, psi4, cp2k, q-e.
Computational Chemistry
Handles molecular modelling, conformers, descriptors and materials calculations.
Methods: rdkit, openbabel, pymatgen.
Investigation of Reaction mechanisms
Explores reaction pathways, transition states and kinetics computationally.
Methods: xtb, crest, RMG-Py, molecularGSM.
Machine-learned interatomic potentials
Uses trained potentials to simulate large systems at near-quantum accuracy.
Methods: mace, torchani.
What you receive
- A written report with methods, parameters and interpretation
- Processed data tables and publication-quality figures
- Scripts and settings so every result can be reproduced
Not sure which analysis fits your data? Contact us and we will advise.