4.7 Article

Insights on phase formation from thermodynamic calculations and machine learning of 2436 experimentally measured high entropy alloys

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Materials Science, Multidisciplinary

Machine learning-based prediction of phases in high-entropy alloys

Ronald Machaka

Summary: The study explores the use of machine learning approaches to classify solid solution high-entropy alloy phases, utilizing a dataset constructed from numerous experimental publications. Different feature selection schemes, feature ensembles, and machine learning classifiers were employed, with the RF, SVM, kNN, and NNET classifiers performing the best in classifying HEA solid solution phases. Results also demonstrated the validity and applicability of the model in predicting phase transitions in various alloy systems.

COMPUTATIONAL MATERIALS SCIENCE (2021)

Article Nanoscience & Nanotechnology

Machine learning approach to predict new multiphase high entropy alloys

Yegi Vamsi Krishna et al.

Summary: The study used machine learning to predict a multiphase alloy system SS + IM with high entropy alloys, with Artificial Neural Network (ANN) showing the highest accuracy. Experimental verification confirmed the accuracy of ANN predictions in the alloy system, but also revealed overlapping design parameters hindering successful prediction.

SCRIPTA MATERIALIA (2021)

Article Materials Science, Multidisciplinary

Revealing high-fidelity phase selection rules for high entropy alloys: A combined CALPHAD and machine learning study

Yingzhi Zeng et al.

Summary: This study presents new phase selection rules for high entropy alloys (HEAs) by combining CALPHAD calculations and the machine learning (ML) method. The eXtreme Gradient Boosting (XGBoost) method is used to identify 5 important descriptors for delineating single and mixed phases in HEAs. The established rules offer a success rate above 90% in predicting single FCC and BCC phases, outperforming existing rules and providing a powerful tool for mapping single-phase regions in the complex temperature-composition space of HEAs.

MATERIALS & DESIGN (2021)

Article Physics, Applied

Structure prediction in high-entropy alloys with machine learning

D. Q. Zhao et al.

Summary: High-entropy alloy is a concept of alloy design that lacks principal components and has complex compositions and multiple intermediate metastable states. With machine learning, elemental characteristics can be combined with long-term ordering to successfully predict with 87% accuracy, accelerating the discovery of potential compositions.

APPLIED PHYSICS LETTERS (2021)

Article Multidisciplinary Sciences

High-throughput design of high-performance lightweight high-entropy alloys

Rui Feng et al.

Summary: The study introduces a high-throughput computational method to design precipitation-strengthened lightweight high-entropy alloys for elevated-temperature applications. By integrating experimental and theoretical understanding, the accuracy of the thermodynamic database is improved, accelerating the discovery of advanced structural materials. This approach proves to be efficient and useful in screening promising high-entropy alloys for high-temperature applications.

NATURE COMMUNICATIONS (2021)

Review Nanoscience & Nanotechnology

Machine learning for alloys

Gus L. W. Hart et al.

Summary: The integration of machine learning and alloys has played a crucial role in advancing research on various materials. Computational materials science has benefited from advancements in machine learning methods and data generation, opening up new possibilities for alloy research.

NATURE REVIEWS MATERIALS (2021)

Article Thermodynamics

Review on the transition from conventional to multi-component-based nano-high-entropy alloys-NHEAs

U. L. Ganesh et al.

JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY (2020)

Review Materials Science, Multidisciplinary

High-Throughput Calculations for High-Entropy Alloys: A Brief Review

Ruixuan Li et al.

FRONTIERS IN MATERIALS (2020)

Article Nanoscience & Nanotechnology

Thermal stability of AlCoFeMnNi high-entropy alloy

Anirudha Karati et al.

SCRIPTA MATERIALIA (2019)

Article Materials Science, Multidisciplinary

Machine-learning phase prediction of high-entropy alloys

Wenjiang Huang et al.

ACTA MATERIALIA (2019)

Article Multidisciplinary Sciences

Materials informatics for the screening of multi-principal elements and high-entropy alloys

J. M. Rickman et al.

NATURE COMMUNICATIONS (2019)

Article Chemistry, Physical

Machine learning guided appraisal and exploration of phase design for high entropy alloys

Ziqing Zhou et al.

NPJ COMPUTATIONAL MATERIALS (2019)

Review Materials Science, Multidisciplinary

Machine learning in materials science

Jing Wei et al.

INFOMAT (2019)

Article Materials Science, Multidisciplinary

Machine learning for phase selection in multi-principal element alloys

Nusrat Islam et al.

COMPUTATIONAL MATERIALS SCIENCE (2018)

Article Materials Science, Multidisciplinary

Database development and Calphad calculations for high entropy alloys: Challenges, strategies, and tips

Hai-Lin Chen et al.

MATERIALS CHEMISTRY AND PHYSICS (2018)

Article Nanoscience & Nanotechnology

Equilibrium high entropy alloy phase stability from experiments and thermodynamic modeling

James E. Saal et al.

SCRIPTA MATERIALIA (2018)

Article Engineering, Manufacturing

A Comparative Study of Feature Selection Methods for Stress Hotspot Classification in Materials

Ankita Mangal et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2018)

Article Chemistry, Physical

Investigation of the phase stabilities in AlNiCoCrFe high entropy alloys

Todd M. Butler et al.

JOURNAL OF ALLOYS AND COMPOUNDS (2017)

Article Chemistry, Physical

TCHEA1: A Thermodynamic Database Not Limited for High Entropy'' Alloys

Huahai Mao et al.

JOURNAL OF PHASE EQUILIBRIA AND DIFFUSION (2017)

Article Materials Science, Multidisciplinary

Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis

Franck Tancret et al.

MATERIALS & DESIGN (2017)

Review Chemistry, Physical

Machine learning in materials informatics: recent applications and prospects

Rampi Ramprasad et al.

NPJ COMPUTATIONAL MATERIALS (2017)

Review Materials Science, Multidisciplinary

A critical review of high entropy alloys and related concepts

D. B. Miracle et al.

ACTA MATERIALIA (2017)

Article Materials Science, Multidisciplinary

Robust FCC solute diffusion predictions from ab-initio machine learning methods

Henry Wu et al.

COMPUTATIONAL MATERIALS SCIENCE (2017)

Article Materials Science, Multidisciplinary

Predicting the formation and stability of single phase high-entropy alloys

D. J. M. King et al.

ACTA MATERIALIA (2016)

Article Nanoscience & Nanotechnology

Design of high entropy alloys: A single-parameter thermodynamic rule

Y. F. Ye et al.

SCRIPTA MATERIALIA (2015)

Article Multidisciplinary Sciences

Accelerated exploration of multi-principal element alloys with solid solution phases

O. N. Senkov et al.

NATURE COMMUNICATIONS (2015)

Article Materials Science, Multidisciplinary

A Novel Low-Density, High-Hardness, High-entropy Alloy with Close-packed Single-phase Nanocrystalline Structures

Khaled M. Youssef et al.

MATERIALS RESEARCH LETTERS (2015)

Article Materials Science, Multidisciplinary

Electronic and thermodynamic criteria for the occurrence of high entropy alloys in metallic systems

M. G. Poletti et al.

ACTA MATERIALIA (2014)

Article Materials Science, Multidisciplinary

Microstructure, physical and chemical properties of nanostructured (Ti-Hf-Zr-V-Nb)N coatings under different deposition conditions

A. D. Pogrebnjak et al.

MATERIALS CHEMISTRY AND PHYSICS (2014)

Review Materials Science, Multidisciplinary

Microstructures and properties of high-entropy alloys

Yong Zhang et al.

PROGRESS IN MATERIALS SCIENCE (2014)

Article Multidisciplinary Sciences

A fracture-resistant high-entropy alloy for cryogenic applications

Bernd Gludovatz et al.

SCIENCE (2014)

Article Multidisciplinary Sciences

A Promising New Class of High-Temperature Alloys: Eutectic High-Entropy Alloys

Yiping Lu et al.

SCIENTIFIC REPORTS (2014)

Review Materials Science, Multidisciplinary

High-Entropy Alloys: A Critical Review

Ming-Hung Tsai et al.

MATERIALS RESEARCH LETTERS (2014)

Article Materials Science, Multidisciplinary

Computational Thermodynamics Aided High-Entropy Alloy Design

Chuan Zhang et al.

Article Materials Science, Multidisciplinary

Alloy Design and Properties Optimization of High-Entropy Alloys

Y. Zhang et al.

Article Chemistry, Physical

Analysis of phase formation in multi-component alloys

R. Raghavan et al.

JOURNAL OF ALLOYS AND COMPOUNDS (2012)

Article Materials Science, Multidisciplinary

Prediction of high-entropy stabilized solid-solution in multi-component alloys

X. Yang et al.

MATERIALS CHEMISTRY AND PHYSICS (2012)

Article Materials Science, Multidisciplinary

Phase stability in high entropy alloys: Formation of solid-solution phase or amorphous phase

Sheng Guo et al.

PROGRESS IN NATURAL SCIENCE-MATERIALS INTERNATIONAL (2011)

Article Materials Science, Multidisciplinary

Solid-solution phase formation rules for multi-component alloys

Yong Zhang et al.

ADVANCED ENGINEERING MATERIALS (2008)

Article Materials Science, Multidisciplinary

Nanostructured high-entropy alloys with multiple principal elements: Novel alloy design concepts and outcomes

JW Yeh et al.

ADVANCED ENGINEERING MATERIALS (2004)

Article Materials Science, Ceramics

Relationship between the widths of supercooled liquid regions and bond parameters of Mg-based bulk metallic glasses

SS Fang et al.

JOURNAL OF NON-CRYSTALLINE SOLIDS (2003)

Article Nanoscience & Nanotechnology

Quantitative evaluation of critical cooling rate for metallic glasses

A Takeuchi et al.

MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING (2001)

Article Materials Science, Multidisciplinary

Stabilization of metallic supercooled liquid and bulk amorphous alloys

A Inoue

ACTA MATERIALIA (2000)