High-throughput studies and machine learning for design of β titanium alloys with optimum properties

作     者：Wei-min CHEN Jin-feng LING Kewu BAI Kai-hong ZHENG Fu-xing YIN Li-jun ZHANG Yong DU 陈伟民;零锦凤;Kewu BAI;郑开宏;殷福星;张利军;杜勇

作者机构：Guangdong Provincial Key Laboratory of Metal Toughening Technology and ApplicationNational Engineering Research Center of Powder Metallurgy of Titanium&Rare MetalsInstitute of New MaterialsGuangdong Academy of SciencesGuangzhou 510650China Institute of Advanced Wear&Corrosion Resistant and Functional MaterialsJinan UniversityGuangzhou 510632China Institute of High Performance ComputingAgency for ScienceTechnology and Research138632Singapore State Key Laboratory of Powder MetallurgyCentral South UniversityChangsha 410083China 

出 版 物：《Transactions of Nonferrous Metals Society of China》 (中国有色金属学报（英文版）)

年 卷 期：2024年第34卷第10期

页      面：3194-3207页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 080502[工学-材料学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the financial supports from the National Key Research and Development Program of China (No. 2022YFB3707501) the National Natural Science Foundation of China (No. 51701083) the GDAS Project of Science and Technology Development, China (No. 2022GDASZH2022010107) the Guangzhou Basic and Applied Basic Research Foundation, China (No. 202201010686) 

主　　题：high-throughput machine learning Ti-based alloys diffusion couple mechanical properties wear behavior 

摘      要：Based on experimental data,machine learning(ML) models for Young s modulus,hardness,and hot-working ability of Ti-based alloys were *** the models,the interdiffusion and mechanical property data were high-throughput re-evaluated from composition variations and nanoindentation data of diffusion ***,the Ti-(22±0.5)at.%Nb-(30±0.5)at.%Zr-(4±0.5)at.%Cr(TNZC) alloy with a single body-centered cubic(BCC) phase was screened in an interactive *** experimental results exhibited a relatively low Young s modulus of(58±4) GPa,high nanohardness of(3.4±0.2) GPa,high microhardness of HV(520±5),high compressive yield strength of(1220±18) MPa,large plastic strain greater than 30%,and superior dry-and wet-wear *** work demonstrates that ML combined with high-throughput analytic approaches can offer a powerful tool to accelerate the design of multicomponent Ti alloys with desired ***,it is indicated that TNZC alloy is an attractive candidate for biomedical applications.