Convolutional Neural Networks for Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix and Magpie Descriptors

Convolutional Neural Networks for Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix and Magpie Descriptors

Computational prediction of crystal materials properties can help to do large-scale in-silicon screening. Recent studies of material informatics have focused on expert design of multi-dimensional interpretable material descriptors/features. However, successes of deep learning such as Convolutional N...

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Bibliographic Details
Main Authors: Zhuo Cao, Yabo Dan, Zheng Xiong, Chengcheng Niu, Xiang Li, Songrong Qian, Jianjun Hu
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Crystals
Subjects:
material informatics
material descriptor
convolutional neural networks
features extraction
formation energy
Online Access:https://www.mdpi.com/2073-4352/9/4/191

Internet

https://www.mdpi.com/2073-4352/9/4/191

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