{"title":"Analytical SA-HCISCF Nuclear Gradients from Spin-Adapted Heat-Bath Configuration Interaction","authors":"Mihkel Ugandi, and , Michael Roemelt*, ","doi":"10.1021/acs.jctc.5c0002110.1021/acs.jctc.5c00021","DOIUrl":null,"url":null,"abstract":"<p >This work reports an implementation of the analytical nuclear gradients and nonadiabatic couplings with state-averaged SCF wave functions from a spin-pure selected configuration interaction (SCI) method. At the core of the implementation lies the evaluation of the Lagrange multipliers required for the variational calculation of the nuclear gradient. Using the same code infrastructure, we developed a fully CI-coupled second-order orbital optimization method. Both the calculation of the nuclear gradient and the second-order orbital optimization make use of density fitting in order to accelerate the calculation of the two-electron integrals. We demonstrate the use of analytical nuclear gradients in excited-state geometry optimizations for conjugated molecules. In addition, the first triplet excited-state geometry of a transition-metal catalyst, Fe(PDI), was optimized with up to 30 orbitals in the active space. Our results outline the capabilities of the implemented methods as well as directions for future work.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 8","pages":"3930–3944 3930–3944"},"PeriodicalIF":5.7000,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jctc.5c00021","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Theory and Computation","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jctc.5c00021","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
This work reports an implementation of the analytical nuclear gradients and nonadiabatic couplings with state-averaged SCF wave functions from a spin-pure selected configuration interaction (SCI) method. At the core of the implementation lies the evaluation of the Lagrange multipliers required for the variational calculation of the nuclear gradient. Using the same code infrastructure, we developed a fully CI-coupled second-order orbital optimization method. Both the calculation of the nuclear gradient and the second-order orbital optimization make use of density fitting in order to accelerate the calculation of the two-electron integrals. We demonstrate the use of analytical nuclear gradients in excited-state geometry optimizations for conjugated molecules. In addition, the first triplet excited-state geometry of a transition-metal catalyst, Fe(PDI), was optimized with up to 30 orbitals in the active space. Our results outline the capabilities of the implemented methods as well as directions for future work.
期刊介绍:
The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.