Thermal fluctuation and conformational effects on NMR parameters in β-O-4 lignin dimers from QM/MM and machine-learning approaches-Reference-Cited by-同舟云学术

Thermal fluctuation and conformational effects on NMR parameters in β-O-4 lignin dimers from QM/MM and machine-learning approaches

Published:2022 Issue:15 Volume:24 Page:8820-8831
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Aguilera-Segura Sonia Milena¹,Dragún Dominik²,Gaumard Robin¹,Di Renzo Francesco¹^ORCID,Ondík Irina Malkin²³^ORCID,Mineva Tzonka¹^ORCID

Affiliation:

1. ICGM, Univ Montpellier, CNRS, ENSCM, Montpellier, France

2. FIIT STU in Bratislava, Ilkovičova 2, 842 16 Bratislava, Slovakia

3. MicroStep-MIS spol. s.r.o. Čavojského 1, 84104 Bratislava, Slovakia

Abstract

Quantum chemical and machine-learning methods may enable high throughput into the structural and dynamics effects on NMR parameters in lignin fragments.

Funder

Grand Équipement National De Calcul Intensif

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2022/CP/D2CP00361A

Reference74 articles.

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2. S. A.Ralph , L. L.Landucci and J.Ralph , NMR Database of Lignin and Cell Wall Model Compounds , 2004 , https://www.glbrc.org/databases_and_software/nmrdatabase/

3. Recent Advances in Characterization of Lignin Polymer by Solution-State Nuclear Magnetic Resonance (NMR) Methodology

4. Structural Characterization of Lignin and Lignin-Carbohydrate Complex (LCC) from Ginkgo Shells (Ginkgo biloba L.) by Comprehensive NMR Spectroscopy

5. Identification of 4–O–5-Units in Softwood Lignins via Definitive Lignin Models and NMR

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