Powder X‐Ray Diffraction Pattern Is All You Need for Machine‐Learning‐Based Symmetry Identification and Property Prediction-Reference-Cited by-同舟云学术

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Powder X‐Ray Diffraction Pattern Is All You Need for Machine‐Learning‐Based Symmetry Identification and Property Prediction

Published:2022-05-22 Issue:7 Volume:4 Page:2200042
ISSN:2640-4567
Container-title:Advanced Intelligent Systems
language:en
Short-container-title:Advanced Intelligent Systems

Author:

Lee Byung Do¹,Lee Jin-Woong¹,Park Woon Bae²,Park Joonseo¹,Cho Min-Young¹,Pal Singh Satendra¹³,Pyo Myoungho²^ORCID,Sohn Kee-Sun¹^ORCID

Affiliation:

1. Faculty of Nanotechnology and Advanced Materials Engineering Sejong University 209 Neungdong-ro Gwangjin-gu Seoul 143-747 South Korea

2. Department of Advanced Components and Materials Engineering Sunchon National University Chonnam 57922 South Korea

3. Department of Physics University of Lucknow Lucknow Uttar Pradesh 226007 India

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202200042

Reference71 articles.

1. A profile refinement method for nuclear and magnetic structures

2. Advances in powder diffraction pattern indexing:N-TREOR09

3. Results and conclusions of the internet based “Search/match round robin 2002”

4. High-throughput powder diffraction. I. A new approach to qualitative and quantitative powder diffraction pattern analysis using full pattern profiles

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1. Autoencoder latent space sensitivity to material structure in convergent-beam low energy electron diffraction;Ultramicroscopy;2024-12

2. In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination;Small Methods;2024-09-09

3. Deep learning for symmetry classification using sparse 3D electron density data for inorganic compounds;npj Computational Materials;2024-09-09

4. Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids;Advanced Intelligent Systems;2024-09-04

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