Machine Learning Full NMR Chemical Shift Tensors of Silicon Oxides with Equivariant Graph Neural Networks-Reference-Cited by-同舟云学术

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Machine Learning Full NMR Chemical Shift Tensors of Silicon Oxides with Equivariant Graph Neural Networks

Published:2023-03-02 Issue:10 Volume:127 Page:2388-2398
ISSN:1089-5639
Container-title:The Journal of Physical Chemistry A
language:en
Short-container-title:J. Phys. Chem. A

Author:

Venetos Maxwell C.¹^ORCID,Wen Mingjian²,Persson Kristin A.¹³^ORCID

Affiliation:

1. Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States

2. Department of Chemical and Biomolecular Engineering, University of Houston, Houston, Texas 77204, United States

3. Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States

Funder

University of Houston

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.2c07530

Reference73 articles.

1. Dynamics of the ?-? phase transitions in quartz and cristobalite as observed by in-situ high temperature 29Si and 17O NMR

2. An X-ray study of the temperature dependence of the quartz structure

3. Magnetic resonance studies on neutron irradiated quartz and amorphous silica

4. Real-space rigid-unit-mode analysis of dynamic disorder in quartz, cristobalite and amorphous silica

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1. Accurate Prediction of NMR Chemical Shifts: Integrating DFT Calculations with Three-Dimensional Graph Neural Networks;Journal of Chemical Theory and Computation;2024-06-06

2. Carbon-based molecular properties efficiently predicted by deep learning-based quantum chemical simulation with large language models;Computers in Biology and Medicine;2024-06

3. Carbohydrate NMR chemical shift prediction by GeqShift employing E(3) equivariant graph neural networks;RSC Advances;2024

4. An equivariant graph neural network for the elasticity tensors of all seven crystal systems;Digital Discovery;2024

5. The need for operando modelling of ²⁷Al NMR in zeolites: the effect of temperature, topology and water;Chemical Science;2023

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