Theoretical Prediction of Yield Strength in Co(1-x-y)CryNix Medium-Entropy Alloys: Integrated Solid Solution and Grain Boundary Strengthening

CoCrNi medium-entropy alloys (MEAs) have emerged as a promising class of structural materials due to their exceptional strength–ductility synergy. However, the lack of composition-dependent predictive models severely hinders rational alloy design, forcing reliance on costly trial-and-error experimentation. This study develops a comprehensive theoretical model to predict the yield strength of single-phase face-centered-cubic (FCC) Co(1-x-y)CryNix MEAs by quantitatively evaluating the contributions of grain boundary and solid solution strengthening. The model demonstrates that increasing Cr content significantly enhances grain boundary strengthening through elevated shear modulus and Peierls stress, whereas Ni has a minimal effect. Solid solution strengthening, determined by the minimum resistance among Co–Cr, Co–Ni, and Cr–Ni atomic pairs, peaks at 1726.21 MPa for the composition Co17Cr64Ni19. For equiatomic CoCrNi, theoretical yield strengths range from 1287.8 to 1575.4 MPa across grain sizes of 0.5–50 µm, showing excellent agreement with experimental results. This work provides a reliable, composition-dependent predictive framework that surpasses traditional trial-and-error methods, enabling efficient design of high-strength MEAs through targeted control of lattice distortion and elemental interactions.

Authors

Institutions

Publication Details

Journal
Metals
Published
2025-12-09
DOI
https://doi.org/10.3390/met15121352
Citations
1
Primary Topic
High Entropy Alloys Studies
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Theoretical Prediction of Yield Strength in Co(1-x-y)CryNix Medium-Entropy Alloys: Integrated Solid Solution and Grain Boundary Strengthening

Linkun Zhang, Zhao-Wen Yu, Zhipeng Wang
1 citations
Metals
High Entropy Alloys Studies
0.71
article

Theoretical Prediction of Yield Strength in Co(1-x-y)CryNix Medium-Entropy Alloys: Integrated Solid Solution and Grain Boundary Strengthening

Linkun Zhang, Zhao-Wen Yu, Zhipeng Wang
article en
1 citations

Abstract

CoCrNi medium-entropy alloys (MEAs) have emerged as a promising class of structural materials due to their exceptional strength–ductility synergy. However, the lack of composition-dependent predictive models severely hinders rational alloy design, forcing reliance on costly trial-and-error experimentation. This study develops a comprehensive theoretical model to predict the yield strength of single-phase face-centered-cubic (FCC) Co(1-x-y)CryNix MEAs by quantitatively evaluating the contributions of grain boundary and solid solution strengthening. The model demonstrates that increasing Cr content significantly enhances grain boundary strengthening through elevated shear modulus and Peierls stress, whereas Ni has a minimal effect. Solid solution strengthening, determined by the minimum resistance among Co–Cr, Co–Ni, and Cr–Ni atomic pairs, peaks at 1726.21 MPa for the composition Co17Cr64Ni19. For equiatomic CoCrNi, theoretical yield strengths range from 1287.8 to 1575.4 MPa across grain sizes of 0.5–50 µm, showing excellent agreement with experimental results. This work provides a reliable, composition-dependent predictive framework that surpasses traditional trial-and-error methods, enabling efficient design of high-strength MEAs through targeted control of lattice distortion and elemental interactions.

MetalsVol. 15(12)
Central South University (CN), Hunan University (CN), Yantai University (CN), Dongguan University of Technology (CN)
Openalex Percentile: Top 24%
High Entropy Alloys Studies
0.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.