Machine-Learning-Based phase diagram construction for high-throughput batch experiments

Machine-Learning-Based phase diagram construction for high-throughput batch experiments

To know phase diagrams is a time saving approach for developing novel materials. To efficiently construct phase diagrams, a machine learning technique was developed using uncertainty sampling, which is called as PDC (Phase Diagram Construction) package [K. Terayama et al. Phys. Rev. Mater. 3, 033802...

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Bibliographic Details
Main Authors: Ryo Tamura, Guillaume Deffrennes, Kwangsik Han, Taichi Abe, Haruhiko Morito, Yasuyuki Nakamura, Masanobu Naito, Ryoji Katsube, Yoshitaro Nose, Kei Terayama
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Science and Technology of Advanced Materials: Methods
Subjects:
phase diagram
machine learning
high-throughput batch experiments
lab automation
Online Access:http://dx.doi.org/10.1080/27660400.2022.2076548

Internet

http://dx.doi.org/10.1080/27660400.2022.2076548

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