Advanced Theoretical Technology for Understanding Microstructures and Mechanical Properties of Alloys

A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Computation and Simulation on Metals".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1314

Special Issue Editors


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Guest Editor
School of Aerospace Engineering, Xiamen University, Xiamen 361005, China
Interests: data-driven alloy design; materials informatics; microstructure control and mechanical properties characterization of structural alloys

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Guest Editor
Faculty of Materials Science and Engineering, Kunming University of Science and Technology, Kunming 650093, China
Interests: multi-scale integrated models; high-throughput first-principles calculations; phase diagram thermodynamics; machine learning; new precious metal materials; ultra-high temperature structural ceramics and coating materials
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China
Interests: computational materials design; metals and alloys, mechanical properties and microstructur; machine learning

Special Issue Information

Dear Colleagues,

Alloys are the backbone of modern engineering, enabling advancements in aerospace, automotive, energy, and biomedical applications. Their performance is governed by intricate microstructural features—such as grain boundaries, dislocations, precipitates, and phase interfaces—that directly influence mechanical properties like strength, ductility, and fracture resistance. Understanding these microstructure–property relationships at the atomic scale remains a critical challenge in materials science. Theoretical technologies, such as first-principles calculations, have emerged as transformative tools to decode these complexities by providing fundamental insights into bonding, defect energetics, and deformation mechanisms without relying on empirical parameters.

This Special Issue seeks to highlight cutting-edge research leveraging advanced theoretical approaches to unravel the interplay between microstructures and mechanical behavior in alloys. Topics of interest include phase stability, solute–defect interactions, interfacial properties, dislocation dynamics, and predictive modeling of alloy performance. Contributions bridging computational methods with experimental validation, machine learning-enhanced frameworks, or multiscale modeling techniques are particularly encouraged. By fostering interdisciplinary dialogue, this collection aims to accelerate the design of next-generation alloys with tailored properties for extreme environments and sustainable technologies.

Dr. Wei-Wei Xu
Prof. Dr. Xiaoyu Chong
Prof. Dr. Zhihua Dong
Guest Editors

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Keywords

  • first-principles calculations
  • dislocation dynamics
  • multiscale modeling
  • machine learning
  • alloy design
  • microstructure characterization
  • mechanical properties
  • phase stability
  • defect energetics
  • structural materials

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Published Papers (1 paper)

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Research

11 pages, 1526 KB  
Article
Theoretical Prediction of Yield Strength in Co(1-x-y)CryNix Medium-Entropy Alloys: Integrated Solid Solution and Grain Boundary Strengthening
by Zhipeng Wang, Zhaowen Yu, Linkun Zhang and Shuying Chen
Metals 2025, 15(12), 1352; https://doi.org/10.3390/met15121352 - 9 Dec 2025
Cited by 1 | Viewed by 542
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 [...] Read more.
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. Full article
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