Advances in Multiconfiguration Pair Density Functional Theory and Applications to Excited State, Singlet-Triplet Gaps and Magnetism
2020-11
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Advances in Multiconfiguration Pair Density Functional Theory and Applications to Excited State, Singlet-Triplet Gaps and Magnetism
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2020-11
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Computational chemistry methods based on quantum mechanics play a fundamental role in explaining and predicting the properties of atoms and molecules such as excitation energies, electronic spectra, magnetism, characterization of chemical bonds, catalysis etc. It is therefore important to be able to correctly describe the interactions between electrons, also known as electron correlation, whose description is a major challenge for modern electronic structure methods. The correct description of electron correlation has been a major challenge in the development of these methods.A recent computational method called multiconfiguration pair-density functional theory (MC-PDFT), developed by Gagliardi and Truhlar groups, can be used to accurately account for electron correlation effects in multireference systems. The advantage of MC- PDFT is that it can accurately describe molecular systems and chemical reactions requiring less computational time and memory than other multireference methods, like, for example, multireference perturbation theory (CASPT2). In this work, MC-PDFT is applied to study excited states and magnetism. MC-PDFT is extended to use density matrix renormalization group wavefunction as reference to study large systems such as singlet-triplet gaps in polyacenes and polyenes. Finally, the challenges in MC-PDFT have been explored and active-space dependence of MC-PDFT energy and other components is investigated.
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University of Minnesota Ph.D. dissertation. November 2020. Major: Chemistry. Advisor: Laura Gagliardi. 1 computer file (PDF); 241 pages.
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Sharma, Prachi. (2020). Advances in Multiconfiguration Pair Density Functional Theory and Applications to Excited State, Singlet-Triplet Gaps and Magnetism. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/218061.
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