Editorial on the Special Topic “Modern semiempirical methods” published in JCP

Our editorial on the Special Topic “Modern semiempirical methods” was published in JCP. We overview contributions and overview the trends in the development and applications of semiempirical quantum mechanical methods. The contributions include improvements in the formalism of the method and often introduce a larger basis set. An increasing number of works use machine learning to improve the methods. The renaissance in the development of semiempirical methods is also reflected by a growing number of software packages supporting them.

Our group also contributed two papers to the issue: one about the benchmark of the AIQM1 (AI-enhanced semiempirical QM methods approaching coupled-cluster accuracy) on barrier heights and another about its implementation (and much more) in the SCINE Sparrow package (used on the XACS cloud computing platform through the interface to MLatom).

Interestingly, an independent group also tested AIQM1 (to be precise its downgraded AIQM1@DFT version approaching DFT instead of coupled cluster accuracy) for the noncovalent interactions needed in drug discovery and recommended it based on AIQM1’s good performance.

Hopefully, you will enjoy reading the papers on this special topic as much as we did!

Editorial

• Pavlo O. Dral*, Ben Hourahine*, Stefan Grimme*. Modern semiempirical electronic structure methods. J. Chem. Phys. 2024, 160, 040401. DOI: 10.1063/5.0196138.