Machine learning-assisted determination of material chemical compositions: a study case on Ni-base superalloy
Author:
Affiliation:
1. Center for Basic Research on Materials, National Institute for Materials Science, Tsukuba, Japan
Funder
Japan Science and Technology Agency
National Institute for Materials Science
Publisher
Informa UK Limited
Subject
General Medicine
Link
https://www.tandfonline.com/doi/pdf/10.1080/27660400.2023.2278321
Reference48 articles.
1. Relation between Chemical Composition and Physical Properties of C-S-H Generated from Cementitious Materials
2. Influence of Chemical Composition and Process Parameters on Mechanical Properties and Formability of AlMgSi-Sheets for Automotive Application
3. Effect of Chemical Composition Variation on Microstructure and Mechanical Properties of a 6060 Aluminum Alloy
4. Optimization of Chemical Composition and Microstructure of Iron Ore Sinter for Low-temperature Drip of Molten Iron with High Permeability
5. Composition optimization of low modulus and high-strength TiNb-based alloys for biomedical applications
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