Supporting Data for: Advancing 19F NMR Prediction of Metal-Fluoride Complexes in Solution: Insights from Ab Initio Molecular Dynamics

DOI

Introduction: This Dataverse entry contains supporting data for our journal article “Advancing 19F NMR Prediction of Metal-Fluoride Complexes in Solution: Insights from Ab Initio Molecular Dynamics” submitted for review. The dataset contains additional computational work performed to support the research work, which was not included in the manuscript. The dataset consists of two files: 1) 'Additional_computational_results.pdf', and 2) 'XYZ_Coordinates_Static+Dynamic.xyz'. The first file contains additional computational data and analysis to support the research work. The second file contains the XYZ structures of the computated geometries studied in the work.

Abstract from article: 19F NMR parameters are versatile probes for studying metal-fluoride complexes. Quantum chemical calculations of 19F NMR chemical shifts enhance the accuracy and validity of resonance signal assignments in complex spectra. However, the treatment of solvation effects in these calculations remains challenging. In this study, we establish a successful computational protocol using ab initio molecular dynamics simulations for the accurate prediction of 19F NMR chemical shifts in solution for the square-planar trans-[NiF(2,3,4,5-C6F4I)(PEt3)2] complex. Our computations revealed that accounting for the dynamic conformational flexibility of the complex, including intramolecular interactions, is crucial for obtaining reliable 19F NMR chemical shifts. Overall, our study advances the understanding of employing state-of-the-art quantum chemistry methods for the accurate model 19F NMR chemical shifts of metal-fluoride complexes in solution, emphasizing the importance of addressing solvation effects in such calculations.

CP2K, 5.1

ADF, 2022.104

NCIPLOT, 4.0

VMD, 1.9.4a53

PACKMOL, 20.3.3

Identifier
DOI https://doi.org/10.18710/OEYQII
Metadata Access https://dataverse.no/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18710/OEYQII
Provenance
Creator Gahlawat, Sahil ORCID logo; Hopmann, Kathrin H. (ORCID: 0000-0003-2798-716X); Castro, Abril C. ORCID logo
Publisher DataverseNO
Contributor Gahlawat, Sahil; Hopmann, Kathrin H.; UiT The Arctic University of Norway; Castro, Abril C.
Publication Year 2024
Funding Reference Marie Skłodowska-Curie Actions (European Union’s Horizon 2020 research and innovation program) Grant agreement No. 859910 ; The Research Council of Norway Grants no. 300769 and 325231, and Centre of Excellence grant no. 262695 ; Sigma2 nn9330k and nn14654k ; NordForsk Grant no. 85378
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact Gahlawat, Sahil (UiT The Arctic University of Norway); Hopmann, Kathrin H. (UiT The Arctic University of Norway)
Representation
Resource Type Computational data; Dataset
Format text/plain; application/pdf; chemical/x-xyz
Size 8130; 739613; 1515095
Version 1.0
Discipline Chemistry; Natural Sciences