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An inexpensive density functional theory-based protocol to predict accurate 19F-NMR chemical shifts. / Benassi, Enrico.

в: Journal of Computational Chemistry, Том 43, № 3, 30.01.2022, стр. 170-183.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

Harvard

Benassi, E 2022, 'An inexpensive density functional theory-based protocol to predict accurate 19F-NMR chemical shifts', Journal of Computational Chemistry, Том. 43, № 3, стр. 170-183. https://doi.org/10.1002/jcc.26780

APA

Vancouver

Benassi E. An inexpensive density functional theory-based protocol to predict accurate 19F-NMR chemical shifts. Journal of Computational Chemistry. 2022 янв. 30;43(3):170-183. doi: 10.1002/jcc.26780

Author

Benassi, Enrico. / An inexpensive density functional theory-based protocol to predict accurate 19F-NMR chemical shifts. в: Journal of Computational Chemistry. 2022 ; Том 43, № 3. стр. 170-183.

BibTeX

@article{129d82e34d8a4b69860bebf568ed9ac1,
title = "An inexpensive density functional theory-based protocol to predict accurate 19F-NMR chemical shifts",
abstract = "Thanks to its advantages, 19F-NMR is an increasingly popular technique for the structural characterization of F-containing molecules, among which polymers, materials, fluorophores, pharmaceuticals, and so forth. However, the computational calculation of the 19F-NMR chemical shifts, both for prediction and interpretation of experimental spectra, remains a challenge. In this work a density functional theory (DFT) based protocol for the calculation of the chemical shifts is established within the framework of the gauge-independent atomic orbital method, upon verifying the performance of Hartree–Fock and 60 DFT functionals coupled with seven different basis sets. The benchmark is conducted using two sets of molecules, namely one used for testing methods and another used for probing; the former set consists of 134 molecules, the latter 50, yet both of them with F in different chemical environments. Following Bally–Rablen–Tantillo strategy, the scaling parameters and other statistical quantities were computed for each method upon least squares linear regression between experimental and computed chemical shifts. The designed computational workflow is computationally inexpensive and represents a significant improvement with respect to the current state of the art.",
keywords = "F-NMR chemical shifts, benchmarking, quantum chemical calculations",
author = "Enrico Benassi",
note = "Funding Information: The computational resources were kindly provided by the Supercomputing Centre at the Nazarbayev University, Nur-Sultan City, Republic of Kazakhstan. Publisher Copyright: {\textcopyright} 2021 Wiley Periodicals LLC.",
year = "2022",
month = jan,
day = "30",
doi = "10.1002/jcc.26780",
language = "English",
volume = "43",
pages = "170--183",
journal = "Journal of Computational Chemistry",
issn = "0192-8651",
publisher = "John Wiley & Sons Inc.",
number = "3",

}

RIS

TY - JOUR

T1 - An inexpensive density functional theory-based protocol to predict accurate 19F-NMR chemical shifts

AU - Benassi, Enrico

N1 - Funding Information: The computational resources were kindly provided by the Supercomputing Centre at the Nazarbayev University, Nur-Sultan City, Republic of Kazakhstan. Publisher Copyright: © 2021 Wiley Periodicals LLC.

PY - 2022/1/30

Y1 - 2022/1/30

N2 - Thanks to its advantages, 19F-NMR is an increasingly popular technique for the structural characterization of F-containing molecules, among which polymers, materials, fluorophores, pharmaceuticals, and so forth. However, the computational calculation of the 19F-NMR chemical shifts, both for prediction and interpretation of experimental spectra, remains a challenge. In this work a density functional theory (DFT) based protocol for the calculation of the chemical shifts is established within the framework of the gauge-independent atomic orbital method, upon verifying the performance of Hartree–Fock and 60 DFT functionals coupled with seven different basis sets. The benchmark is conducted using two sets of molecules, namely one used for testing methods and another used for probing; the former set consists of 134 molecules, the latter 50, yet both of them with F in different chemical environments. Following Bally–Rablen–Tantillo strategy, the scaling parameters and other statistical quantities were computed for each method upon least squares linear regression between experimental and computed chemical shifts. The designed computational workflow is computationally inexpensive and represents a significant improvement with respect to the current state of the art.

AB - Thanks to its advantages, 19F-NMR is an increasingly popular technique for the structural characterization of F-containing molecules, among which polymers, materials, fluorophores, pharmaceuticals, and so forth. However, the computational calculation of the 19F-NMR chemical shifts, both for prediction and interpretation of experimental spectra, remains a challenge. In this work a density functional theory (DFT) based protocol for the calculation of the chemical shifts is established within the framework of the gauge-independent atomic orbital method, upon verifying the performance of Hartree–Fock and 60 DFT functionals coupled with seven different basis sets. The benchmark is conducted using two sets of molecules, namely one used for testing methods and another used for probing; the former set consists of 134 molecules, the latter 50, yet both of them with F in different chemical environments. Following Bally–Rablen–Tantillo strategy, the scaling parameters and other statistical quantities were computed for each method upon least squares linear regression between experimental and computed chemical shifts. The designed computational workflow is computationally inexpensive and represents a significant improvement with respect to the current state of the art.

KW - F-NMR chemical shifts

KW - benchmarking

KW - quantum chemical calculations

UR - http://www.scopus.com/inward/record.url?scp=85118767953&partnerID=8YFLogxK

U2 - 10.1002/jcc.26780

DO - 10.1002/jcc.26780

M3 - Article

C2 - 34757623

AN - SCOPUS:85118767953

VL - 43

SP - 170

EP - 183

JO - Journal of Computational Chemistry

JF - Journal of Computational Chemistry

SN - 0192-8651

IS - 3

ER -

ID: 34657914