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22 results on '"Liu, Yinqiao"'

4. Predicting Elastic Properties of Materials from Electronic Charge Density Using 3D Deep Convolutional Neural Networks

Author

Zhao, Yong, Yuan, Kunpeng, Liu, Yinqiao, Louis, Steph-Yves, Hu, Ming, and Hu, Jianjun

Subjects
Condensed Matter - Materials Science, Computer Science - Computational Engineering, Finance, and Science, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Physics - Computational Physics, 74B99, I.2.1
Abstract

Materials representation plays a key role in machine learning based prediction of materials properties and new materials discovery. Currently both graph and 3D voxel representation methods are based on the heterogeneous elements of the crystal structures. Here, we propose to use electronic charge density (ECD) as a generic unified 3D descriptor for materials property prediction with the advantage of possessing close relation with the physical and chemical properties of materials. We developed an ECD based 3D convolutional neural networks (CNNs) for predicting elastic properties of materials, in which CNNs can learn effective hierarchical features with multiple convolving and pooling operations. Extensive benchmark experiments over 2,170 Fm-3m face-centered-cubic (FCC) materials show that our ECD based CNNs can achieve good performance for elasticity prediction. Especially, our CNN models based on the fusion of elemental Magpie features and ECD descriptors achieved the best 5-fold cross-validation performance. More importantly, we showed that our ECD based CNN models can achieve significantly better extrapolation performance when evaluated over non-redundant datasets where there are few neighbor training samples around test samples. As additional validation, we evaluated the predictive performance of our models on 329 materials of space group Fm-3m by comparing to DFT calculated values, which shows better prediction power of our model for bulk modulus than shear modulus. Due to the unified representation power of ECD, it is expected that our ECD based CNN approach can also be applied to predict other physical and chemical properties of crystalline materials., Comment: 15 pages; 5 figures

Published
2020
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18. Fluoride‐Based Anion Doping: A New Strategy for Improving the Performance of Protonic Ceramic Conductors of the Form BaZrO3.

Author

Gao, Jun, Liu, Yinqiao, Meng, Yuqing, Hu, Ming, and Brinkman, Kyle S.

Subjects
SOLID oxide fuel cells, X-ray photoelectron spectroscopy, ANIONS, CHEMICAL bonds, CELL membranes
Abstract

A new strategy is reported to improve the performance of BaZrO3‐based protonic ceramic conductors by substitution on the anion sublattice, specifically replacing F− in the O2− site. The F−‐doped material exhibited higher conductivity under both reducing and oxidizing atmospheres compared to the undoped oxide. Ab initio calculations and X‐ray photoelectron spectroscopy results showed that the improved performance can be attributed to weakened chemical bonding between the cations (A or B site) and the oxygen ions as a result of F− doping, resulting in improved oxygen mobility. Finally, improved performance was demonstrated by using BaZr0.8Y0.2O3‐δ‐σFσ (σ=0.1) as the electrolyte in protonic ceramic fuel cells measurements. The anions doping strategy shows great promise for the development of a new generation of high‐performance electrolyte materials. [ABSTRACT FROM AUTHOR]

Published
2020
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22. Cover Feature: Fluoride‐Based Anion Doping: A New Strategy for Improving the Performance of Protonic Ceramic Conductors of the Form BaZrO3 (ChemElectroChem 10/2020).

Author

Gao, Jun, Liu, Yinqiao, Meng, Yuqing, Hu, Ming, and Brinkman, Kyle S.

Subjects
ANIONS, CHARGE carrier mobility, ENERGY conversion
Abstract

Cover Feature: Fluoride-Based Anion Doping: A New Strategy for Improving the Performance of Protonic Ceramic Conductors of the Form BaZrO3 (ChemElectroChem 10/2020) Keywords: protonic ceramic conductor; energy conversion and storage; fluoride ion doping; ab initio calculations; BaZrO3 EN protonic ceramic conductor energy conversion and storage fluoride ion doping ab initio calculations BaZrO3 2207 2207 1 06/01/20 20200515 NES 200515 B The Cover Feature b illustrates the enhanced mobility of ionic charge carriers after substitution of F SP - sp on the O SP 2- sp site. Interestingly, weakened chemical bonds were observed between the cations (A or B site) and the oxygen ions by the anion doping strategy resulting in an improved oxygen mobility in the lattice. [Extracted from the article]

Published
2020
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