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Metallurgical and Materials Transactions B
Published in: Metallurgical and Materials Transactions B 1/2021

20-11-2020 | Communication

Machine Learning on Contact Angles of Liquid Metals and Solid Oxides

Authors: Li Zuo, Peiyuan Ni, Toshihiro Tanaka, Ying Li

Published in: Metallurgical and Materials Transactions B | Issue 1/2021

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Abstract

An improved neural network model was developed in this paper to predict the contact angles of 15 metals and 14 solid oxides. The model shows a good performance that predictions are generally within 15 pct deviation from the experimental data. Predictions on 25 test data shows the maximum deviation smaller than 10 pct. Therefore, the developed model is a universal model with a good accuracy, which is useful for material science and manufacturing field.
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Metadata
Title
Machine Learning on Contact Angles of Liquid Metals and Solid Oxides
Authors
Li Zuo
Peiyuan Ni
Toshihiro Tanaka
Ying Li
Publication date
20-11-2020
Publisher
Springer US
Published in
Metallurgical and Materials Transactions B / Issue 1/2021
Print ISSN: 1073-5615
Electronic ISSN: 1543-1916
DOI
https://doi.org/10.1007/s11663-020-02013-5

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