A Fast, Low-Cost and Simple Method for Predicting Atomic/Inter-Atomic Properties by Combining a Low Dimensional Deep Learning Model with a Fragment Based Graph Convolutional Network

A Fast, Low-Cost and Simple Method for Predicting Atomic/Inter-Atomic Properties by Combining a Low Dimensional Deep Learning Model with a Fragment Based Graph Convolutional Network

Calculations with high accuracy for atomic and inter-atomic properties, such as nuclear magnetic resonance (NMR) spectroscopy and bond dissociation energies (BDEs) are valuable for pharmaceutical molecule structural analysis, drug exploration, and screening. It is important that these calculations s...

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Bibliographic Details
Main Authors: Peng Gao, Zonghang Liu, Jie Zhang, Jia-Ao Wang, Graeme Henkelman
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Crystals
Subjects:
quantum mechanics
neural network
NMR
bond dissociation energy
machine-learning
Online Access:https://www.mdpi.com/2073-4352/12/12/1740

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