Compositional design of compounds with elements not in training data using supervised learning-Reference-Cited by-同舟云学术

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Compositional design of compounds with elements not in training data using supervised learning

Published:2024-07 Issue: Volume: Page:
ISSN:2352-8478
Container-title:Journal of Materiomics
language:en
Short-container-title:Journal of Materiomics

Author:

He Jingjin,Yin Ruowei,Wang Changxin,Liu Chuanbao,Xue Dezhen,Su Yanjing,Qiao Lijie,Lookman Turab,Bai Yang^ORCID

Publisher

Elsevier BV

Reference40 articles.

1. Machine learning in materials design and discovery: examples from the present and suggestions for the future;Gubernatis;Phys Rev Mater,2018

2. Determining multi-component phase diagrams with desired characteristics using active learning;Tian;Adv Sci,2021

3. Machine learning–enabled identification of material phase transitions based on experimental data: exploring collective dynamics in ferroelectric relaxors;Li;Sci Adv,2018

4. Comparison of dissimilarity measures for cluster analysis of X-ray diffraction data from combinatorial libraries;Iwasaki;npj Comput Mater,2017

5. Reconstructing phase diagrams from local measurements via gaussian processes: mapping the temperature-composition space to confidence;Pradhan;npj Comput Mater,2018

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