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Large-Scale Computation of Nuclear Magnetic Resonance Shifts for Paramagnetic Solids Using CP2K
Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).ORCID iD: 0000-0002-2542-8113
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Number of Authors: 72018 (English)In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 14, no 1, p. 377-394Article in journal (Refereed) Published
Abstract [en]

Large-scale computations of nuclear magnetic resonance (NMR) shifts for extended paramagnetic solids (pNMR) are reported using the highly efficient Gaussian-augmented plane-wave implementation of the CP2K code. Combining hyperfine couplings obtained with hybrid functionals with g-tensors and orbital shieldings computed using gradient-corrected functionals, contact, pseudocontact, and orbital-shift contributions to pNMR shifts are accessible. Due to the efficient and highly parallel performance of CP2K, a wide variety of materials with large unit cells can be studied with extended Gaussian basis sets. Validation of various approaches for the different contributions to pNMR shifts is done first for molecules in a large supercell in comparison with typical quantum-chemical codes. This is then extended to a detailed study of g-tensors for extended solid transition-metal fluorides and for a series of complex lithium vanadium phosphates. Finally, lithium pNMR shifts are computed for Li3V2(PO4)(3), for which detailed experimental data are available. This has allowed an in-depth study of different approaches (e.g., full periodic versus incremental cluster computations of g-tensors and different functionals and basis sets for hyperfine computations) as well as a thorough analysis of the different contributions to the pNMR shifts. This study paves the way for a more-widespread computational treatment of NMR shifts for paramagnetic materials.

Place, publisher, year, edition, pages
2018. Vol. 14, no 1, p. 377-394
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Chemical Sciences Physical Sciences
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URN: urn:nbn:se:su:diva-152582DOI: 10.1021/acs.jctc.7b00991ISI: 000419998300034PubMedID: 29182320OAI: oai:DiVA.org:su-152582DiVA, id: diva2:1180707
Available from: 2018-02-06 Created: 2018-02-06 Last updated: 2022-02-28Bibliographically approved

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Mondal, ArobendoPell, Andrew J.

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