Discovery of Low-Modulus Ti-Nb-Zr Alloys Based on Machine Learning and First-Principles Calculations-Reference-Cited by-同舟云学术

Discovery of Low-Modulus Ti-Nb-Zr Alloys Based on Machine Learning and First-Principles Calculations

Published:2020-12-09 Issue:51 Volume:12 Page:56850-56861
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Salvador Camilo A. F.¹,Zornio Bruno F.¹^ORCID,Miranda Caetano R.¹^ORCID

Affiliation:

1. Instituto de Física, DFMT, Universidade de São Paulo, CP 66318, 05315-970 São Paulo, SP, Brazil

Funder

Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico

Funda??o de Amparo ? Pesquisa do Estado de S?o Paulo

Publisher

American Chemical Society (ACS)

Subject

General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.0c18506

Reference56 articles.

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4. General approach to phase stability and elastic properties of β-type Ti-alloys using electronic parameters

5. A new thermodynamic parameter to predict formation of solid solution or intermetallic phases in high entropy alloys

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