Fatigue dataset of high-entropy alloys

Author:

Chen Shiyi,Fan Xuesong,Steingrimsson BaldurORCID,Xiong Qingang,Li Weidong,Liaw Peter K.

Abstract

AbstractFatigue failure of metallic structures is of great concern to industrial applications. A material will not be practically useful if it is prone to fatigue failures. To take the advantage of lately emerged high-entropy alloys (HEAs) for designing novel fatigue-resistant alloys, we compiled a fatigue database of HEAs from the literature reported until the beginning of 2022. The database is subdivided into three categories, i.e., low-cycle fatigue (LCF), high-cycle fatigue (HCF), and fatigue crack growth rate (FCGR), which contain 15, 23, and 28 distinct data records, respectively. Each data record in any of three categories is characteristic of a summary, which is comprised of alloy compositions, key fatigue properties, and additional information influential to, or interrelated with, fatigue (e.g., material processing history, phase constitution, grain size, uniaxial tensile properties, and fatigue testing conditions), and an individual dataset, which makes up the original fatigue testing curve. Some representative individual datasets in each category are graphically visualized. The dataset is hosted in an open data repository, Materials Cloud.

Funder

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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