ArticleJournal of molecular modeling2023
An improved parameterization procedure for NDDO-descendant semi-empirical methods.
Article in Journal of molecular modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A Near Black Box Parameter Optimizer for NDDO-Descendant Semiempirical Methods: Demonstrations for MNDO and AM1.The journal of physical chemistry. A · 2026Article
- Geometry-Corrected Quadratic Optimization Algorithm for NDDO-Descendant Semiempirical Models.Journal of chemical theory and computation · 2025Article
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3 authors.
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Abstract
conceptMNDO-based semi-empirical methods in quantum chemistry have found widespread application in the modelling of large and complex systems. A method for the analytic evaluation of first and second derivatives of molecular properties against semi-empirical parameters in MNDO-based NDDO-descendant models is presented, and the resultant parameter Hessian is compared against the approximant currently used in parameterization for the PMx models.
methodsAs a proof of concept, the exact parameter Hessian is employed in a limited reparameterization of MNDO for the elements C, H, N, O and F using 1206 molecules for reference data (heats of formation, ionization energies, dipole moments and reference geometries). The correctness of our MNDO implementation was verified by comparing the calculated molecular properties with the MOPAC program.
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