Bayesian probabilistic assignment of chemical shifts in organic solids-Reference-Cited by-同舟云学术

Bayesian probabilistic assignment of chemical shifts in organic solids

Published:2021-11-26 Issue:48 Volume:7 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Cordova Manuel¹²^ORCID,Balodis Martins¹,Simões de Almeida Bruno¹^ORCID,Ceriotti Michele²³^ORCID,Emsley Lyndon¹²^ORCID

Affiliation:

1. Laboratory of Magnetic Resonance, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.

2. National Centre for Computational Design and Discovery of Novel Materials MARVEL, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.

3. Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.

Abstract

Machine-learned chemical shifts enable probabilistic assignment in organic solids without knowledge of the structure.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference78 articles.

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4. All-electron magnetic response with pseudopotentials: NMR chemical shifts

5. Chemical shift computations on a crystallographic basis: some reflections and comments

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