Editing Computational chemistry (section)

=== Catalysis ===
[[File:CatalysisScheme.png|thumb|Computational chemistry can help predict values like activation energy from catalysis. The presence of the catalyst opens a different reaction pathway (shown in red) with lower activation energy. The final result and the overall thermodynamics are the same.]]
Computational chemistry is a tool for analyzing catalytic systems without doing experiments. Modern [[Electronic structure|electronic structure theory]] and [[density functional theory]] has allowed researchers to discover and understand [[Catalysis|catalysts]].<ref>{{Cite journal |last1=Elnabawy |first1=Ahmed O. |last2=Rangarajan |first2=Srinivas |last3=Mavrikakis |first3=Manos |date=2015-08-01 |title=Computational chemistry for NH3 synthesis, hydrotreating, and NOx reduction: Three topics of special interest to Haldor Topsøe |url=https://www.sciencedirect.com/science/article/pii/S0021951714003534 |journal=Journal of Catalysis |series=Special Issue: The Impact of Haldor Topsøe on Catalysis |volume=328 |pages=26–35 |doi=10.1016/j.jcat.2014.12.018 |issn=0021-9517}}</ref> Computational studies apply theoretical chemistry to catalysis research. Density functional theory methods calculate the energies and orbitals of molecules to give models of those structures.<ref name="Patel-2020">{{Cite journal |last1=Patel |first1=Prajay |last2=Wilson |first2=Angela K. |date=2020-12-01 |title=Computational chemistry considerations in catalysis: Regioselectivity and metal-ligand dissociation |journal=Catalysis Today |series=Proceedings of 3rd International Conference on Catalysis and Chemical Engineering |volume=358 |pages=422–429 |doi=10.1016/j.cattod.2020.07.057 |s2cid=225472601 |issn=0920-5861|doi-access=free }}</ref> Using these methods, researchers can predict values like [[activation energy]], [[Active site|site reactivity]]<ref name="van Santen-1996">{{Cite journal |last=van Santen |first=R. A. |date=1996-05-06 |title=Computational-chemical advances in heterogeneous catalysis |url=https://dx.doi.org/10.1016/1381-1169%2895%2900161-1 |journal=Journal of Molecular Catalysis A: Chemical |series=Proceedings of the 8th International Symposium on the Relations between Homogeneous and Heterogeneous Catalysis |volume=107 |issue=1 |pages=5–12 |doi=10.1016/1381-1169(95)00161-1 |s2cid=59580128 |issn=1381-1169}}</ref> and other thermodynamic properties.<ref name="Patel-2020" />

Data that is difficult to obtain experimentally can be found using computational methods to model the mechanisms of catalytic cycles.<ref name="van Santen-1996" /> Skilled computational chemists provide predictions that are close to experimental data with proper considerations of methods and basis sets. With good computational data, researchers can predict how catalysts can be improved to lower the cost and increase the efficiency of these reactions.<ref name="Patel-2020" />