Machine learning for high-entropy alloys: Progress, challenges and opportunities

Composition design of high-entropy alloys with deep sets learning

(2022) Jie Zhang et al.   npj Computational Materials

Origins of structural and electronic transitions in disordered silicon

(2021) Volker L. Deringer et al.   NATURE

Convolutional neural network-assisted recognition of nanoscale L12 ordered structures in face-centred cubic alloys

(2021) Yue Li et al.   npj Computational Materials

Machine-learned interatomic potentials for alloys and alloy phase diagrams

(2021) Conrad W. Rosenbrock et al.   npj Computational Materials

Screening of generalized stacking fault energies, surface energies and intrinsic ductile potency of refractory multicomponent alloys

(2021) Yong-Jie Hu et al.   ACTA MATERIALIA

Generalized stacking fault energies and Peierls stresses in refractory body-centered cubic metals from machine learning-based interatomic potentials

(2021) Xiaowang Wang et al.   COMPUTATIONAL MATERIALS SCIENCE

Direct observation of chemical short-range order in a medium-entropy alloy

(2021) Xuefei Chen et al.   NATURE

Machine learning for design, phase transformation and mechanical properties of alloys

(2021) J.F. Durodola   PROGRESS IN MATERIALS SCIENCE

A ductility criterion for bcc high entropy alloys

(2021) Eleanor Mak et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

Bifunctional nanoprecipitates strengthen and ductilize a medium-entropy alloy

(2021) Ying Yang et al.   NATURE

Machine-learned potentials for next-generation matter simulations

(2021) Pascal Friederich et al.   NATURE MATERIALS

Hidden Effects of Negative Stacking Fault Energies in Complex Concentrated Alloys

(2021) Zongrui Pei et al.   PHYSICAL REVIEW LETTERS

Application of atom probe tomography in understanding high entropy alloys: 3D local chemical compositions in atomic scale analysis

(2021) Rong Hu et al.   PROGRESS IN MATERIALS SCIENCE

Gradient-cell–structured high-entropy alloy with exceptional strength and ductility

(2021) Qingsong Pan et al.   SCIENCE

Atomistic simulations of dislocation mobility in refractory high-entropy alloys and the effect of chemical short-range order

(2021) Sheng Yin et al.   Nature Communications

Machine learning for alloys

(2021) Gus L. W. Hart et al.   Nature Reviews Materials

Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture

(2021) Cheol Woo Park et al.   npj Computational Materials

Benchmarking graph neural networks for materials chemistry

(2021) Victor Fung et al.   npj Computational Materials

B2 ordering in body-centered-cubic AlNbTiV refractory high-entropy alloys

(2021) Fritz Körmann et al.   Physical Review Materials

Finite-temperature interplay of structural stability, chemical complexity, and elastic properties of bcc multicomponent alloys from ab initio trained machine-learning potentials

(2021) Konstantin Gubaev et al.   Physical Review Materials

A machine learning-based alloy design system to facilitate the rational design of high entropy alloys with enhanced hardness

(2021) Chen Yang et al.   ACTA MATERIALIA

Effect of short-range order on the mechanical behaviors of tensile and shear for NiCoFeCr

(2021) Xiaotao Liu et al.   APPLIED PHYSICS LETTERS

Accelerated discovery of single-phase refractory high entropy alloys assisted by machine learning

(2021) Yonggang Yan et al.   COMPUTATIONAL MATERIALS SCIENCE

Deep learning for mapping element distribution of high-entropy alloys in scanning transmission electron microscopy images

(2021) Marco Ragone et al.   COMPUTATIONAL MATERIALS SCIENCE

Decoupling between Shockley partials and stacking faults strengthens multiprincipal element alloys

(2021) Zongrui Pei et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Nanoprecipitate‐Strengthened High‐Entropy Alloys

(2021) Liyuan Liu et al.   Advanced Science

Machine‐Learning Microstructure for Inverse Material Design

(2021) Zongrui Pei et al.   Advanced Science

Inverse design of two-dimensional materials with invertible neural networks

(2021) Victor Fung et al.   npj Computational Materials

Machine-learning potentials enable predictive and tractable high-throughput screening of random alloys

(2021) M. Hodapp et al.   Physical Review Materials

Machine learning for interatomic potential models

(2020) Tim Mueller et al.   JOURNAL OF CHEMICAL PHYSICS

Performance and Cost Assessment of Machine Learning Interatomic Potentials

(2020) Yunxing Zuo et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Improved protein structure prediction using potentials from deep learning

(2020) Andrew W. Senior et al.   NATURE

Crystal symmetry determination in electron diffraction using machine learning

(2020) Kevin Kaufmann et al.   SCIENCE

Opportunities and Challenges for Machine Learning in Materials Science

(2020) Dane Morgan et al.   Annual Review of Materials Research

Short-range order and its impact on the CrCoNi medium-entropy alloy

(2020) Ruopeng Zhang et al.   NATURE

Machine-learning informed prediction of high-entropy solid solution formation: Beyond the Hume-Rothery rules

(2020) Zongrui Pei et al.   npj Computational Materials

Complex strengthening mechanisms in the NbMoTaW multi-principal element alloy

(2020) Xiang-Guo Li et al.   npj Computational Materials

Developing an improved crystal graph convolutional neural network framework for accelerated materials discovery

(2020) Cheol Woo Park et al.   Physical Review Materials

Searching for high entropy alloys: A machine learning approach

(2020) Kevin Kaufmann et al.   ACTA MATERIALIA

On the quantification and efficient propagation of imprecise probabilities with copula dependence

(2020) Jiaxin Zhang et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Spectral neural network potentials for binary alloys

(2020) David Zagaceta et al.   JOURNAL OF APPLIED PHYSICS

Tailoring nanoprecipitates for ultra-strong high-entropy alloys via machine learning and prestrain aging

(2020) Tao Zheng et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

Machine learned feature identification for predicting phase and Young's modulus of low-, medium- and high-entropy alloys

(2020) Ankit Roy et al.   SCRIPTA MATERIALIA

Natural-mixing guided design of refractory high-entropy alloys with as-cast tensile ductility

(2020) Shaolou Wei et al.   NATURE MATERIALS

Multicomponent high-entropy Cantor alloys

(2020) B. Cantor   PROGRESS IN MATERIALS SCIENCE

Identifying domains of applicability of machine learning models for materials science

(2020) Christopher Sutton et al.   Nature Communications

Materials Cloud, a platform for open computational science

(2020) Leopold Talirz et al.   Scientific Data

Directional Gaussian smoothing optimization method for computational inverse design in nanophotonics

(2020) Jiaxin Zhang et al.   MATERIALS & DESIGN

Data augmentation in microscopic images for material data mining

(2020) Boyuan Ma et al.   npj Computational Materials

Coupling physics in machine learning to predict properties of high-temperatures alloys

(2020) Jian Peng et al.   npj Computational Materials

Statistics of the NiCoCr medium-entropy alloy: Novel aspects of an old puzzle

(2020) Zongrui Pei et al.   npj Computational Materials

Machine learning for metallurgy I. A neural-network potential for Al-Cu

(2020) Daniel Marchand et al.   Physical Review Materials

Machine learning for metallurgy II. A neural-network potential for magnesium

(2020) Markus Stricker et al.   Physical Review Materials

Fast and stable deep-learning predictions of material properties for solid solution alloys

(2020) Massimiliano Lupo Pasini et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Expanded dataset of mechanical properties and observed phases of multi-principal element alloys

(2020) Christopher K. H. Borg et al.   Scientific Data

Deep learning-based phase prediction of high-entropy alloys: Optimization, generation, and explanation

(2020) Soo Young Lee et al.   MATERIALS & DESIGN

Monte Carlo simulation of order-disorder transition in refractory high entropy alloys: A data-driven approach

(2020) Xianglin Liu et al.   COMPUTATIONAL MATERIALS SCIENCE

Machine learning as a contributor to physics: Understanding Mg alloys

(2019) Zongrui Pei et al.   MATERIALS & DESIGN

Enhanced strength–ductility synergy in ultrafine-grained eutectic high-entropy alloys by inheriting microstructural lamellae

(2019) Peijian Shi et al.   Nature Communications

A high-bias, low-variance introduction to Machine Learning for physicists

(2019) Pankaj Mehta et al.   PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS

Machine learning assisted design of high entropy alloys with desired property

(2019) Cheng Wen et al.   ACTA MATERIALIA

Active learning of uniformly accurate interatomic potentials for materials simulation

(2019) Linfeng Zhang et al.   PHYSICAL REVIEW MATERIALS

Machine-learning phase prediction of high-entropy alloys

(2019) Wenjiang Huang et al.   ACTA MATERIALIA

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

(2019) Chi Chen et al.   CHEMISTRY OF MATERIALS

Machine-learned multi-system surrogate models for materials prediction

(2019) Chandramouli Nyshadham et al.   npj Computational Materials

Impact of lattice relaxations on phase transitions in a high-entropy alloy studied by machine-learning potentials

(2019) Tatiana Kostiuchenko et al.   npj Computational Materials

Chemi-Net: A Molecular Graph Convolutional Network for Accurate Drug Property Prediction

(2019) Ke Liu et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

Engineering atomic-level complexity in high-entropy and complex concentrated alloys

(2019) Hyun Seok Oh et al.   Nature Communications

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

(2019) J. M. Rickman et al.   Nature Communications

High-entropy alloys

(2019) Easo P. George et al.   Nature Reviews Materials

Tracking materials science data lineage to manage millions of materials experiments and analyses

(2019) Edwin Soedarmadji et al.   npj Computational Materials

First-principles and Machine Learning Predictions of Elasticity in Severely Lattice-distorted High-Entropy Alloys with Experimental Validation

(2019) George Kim et al.   ACTA MATERIALIA

Sublattice formation in CoCrFeNi high-entropy alloy

(2019) E.A. Meshkov et al.   INTERMETALLICS

Applying a machine learning interatomic potential to unravel the effects of local lattice distortion on the elastic properties of multi-principal element alloys

(2019) Mehdi Jafary-Zadeh et al.   JOURNAL OF ALLOYS AND COMPOUNDS

Data‐Driven Materials Science: Status, Challenges, and Perspectives

(2019) Lauri Himanen et al.   Advanced Science

Recent advances and applications of machine learning in solid-state materials science

(2019) Jonathan Schmidt et al.   npj Computational Materials

Machine-learning model for predicting phase formations of high-entropy alloys

(2019) Yao Li et al.   Physical Review Materials

One Pixel Attack for Fooling Deep Neural Networks

(2019) Jiawei Su et al.   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

Unsupervised discovery of solid-state lithium ion conductors

(2019) Ying Zhang et al.   Nature Communications

Dislocation core structures and Peierls stresses of the high-entropy alloy NiCoFeCrMn and its subsystems

(2019) Xianglin Liu et al.   MATERIALS & DESIGN

Phase prediction in high entropy alloys with a rational selection of materials descriptors and machine learning models

(2019) Yan Zhang et al.   ACTA MATERIALIA

Uncovering the eutectics design by machine learning in the Al–Co–Cr–Fe–Ni high entropy system

(2019) Qingfeng Wu et al.   ACTA MATERIALIA

Tailoring heterogeneities in high-entropy alloys to promote strength–ductility synergy

(2019) Evan Ma et al.   Nature Communications

Robust data-driven approach for predicting the configurational energy of high entropy alloys

(2019) Jiaxin Zhang et al.   MATERIALS & DESIGN

The relation between two ductility mechanisms for Mg alloys revealed by high-throughput simulations

(2019) Zongrui Pei et al.   MATERIALS & DESIGN

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

(2019) Ziqing Zhou et al.   npj Computational Materials

High entropy alloys: A focused review of mechanical properties and deformation mechanisms

(2019) E.P. George et al.   ACTA MATERIALIA

Efficient exploration of the High Entropy Alloy composition-phase space

(2018) A. Abu-Odeh et al.   ACTA MATERIALIA

Material structure-property linkages using three-dimensional convolutional neural networks

(2018) Ahmet Cecen et al.   ACTA MATERIALIA

Machine learning for phase selection in multi-principal element alloys

(2018) Nusrat Islam et al.   COMPUTATIONAL MATERIALS SCIENCE

SchNet – A deep learning architecture for molecules and materials

(2018) K. T. Schütt et al.   JOURNAL OF CHEMICAL PHYSICS

Extending the accuracy of the SNAP interatomic potential form

(2018) Mitchell A. Wood et al.   JOURNAL OF CHEMICAL PHYSICS

Ab initio phase stabilities and mechanical properties of multicomponent alloys: A comprehensive review for high entropy alloys and compositionally complex alloys

(2018) Yuji Ikeda et al.   MATERIALS CHARACTERIZATION

On the quantification and efficient propagation of imprecise probabilities resulting from small datasets

(2018) Jiaxin Zhang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

(2018) Tian Xie et al.   PHYSICAL REVIEW LETTERS

Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

(2018) Linfeng Zhang et al.   PHYSICAL REVIEW LETTERS

Learning atoms for materials discovery

(2018) Quan Zhou et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Mechanistic origin and prediction of enhanced ductility in magnesium alloys

(2018) Zhaoxuan Wu et al.   SCIENCE

Inverse design in search of materials with target functionalities

(2018) Alex Zunger   Nature Reviews Chemistry

Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron

(2018) Daniele Dragoni et al.   PHYSICAL REVIEW MATERIALS

Modeling the structure and thermodynamics of high-entropy alloys

(2018) Michael Widom   JOURNAL OF MATERIALS RESEARCH

Machine learning for molecular and materials science

(2018) Keith T. Butler et al.   NATURE

Machine learning at the energy and intensity frontiers of particle physics

(2018) Alexander Radovic et al.   NATURE

Tunable stacking fault energies by tailoring local chemical order in CrCoNi medium-entropy alloys

(2018) Jun Ding et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Inverse molecular design using machine learning: Generative models for matter engineering

(2018) Benjamin Sanchez-Lengeling et al.   SCIENCE

Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization

(2018) Benjamin Peherstorfer et al.   SIAM REVIEW

Accelerating high-throughput searches for new alloys with active learning of interatomic potentials

(2018) Konstantin Gubaev et al.   COMPUTATIONAL MATERIALS SCIENCE

Active learning in Gaussian process interpolation of potential energy surfaces

(2018) Elena Uteva et al.   JOURNAL OF CHEMICAL PHYSICS

Enhanced strength and ductility in a high-entropy alloy via ordered oxygen complexes

(2018) Zhifeng Lei et al.   NATURE

Efficient Monte Carlo resampling for probability measure changes from Bayesian updating

(2018) Jiaxin Zhang et al.   PROBABILISTIC ENGINEERING MECHANICS

Multicomponent intermetallic nanoparticles and superb mechanical behaviors of complex alloys

(2018) T. Yang et al.   SCIENCE

Screw dislocation structure and mobility in body centered cubic Fe predicted by a Gaussian Approximation Potential

(2018) Francesco Maresca et al.   npj Computational Materials

Machine-learning the configurational energy of multicomponent crystalline solids

(2018) Anirudh Raju Natarajan et al.   npj Computational Materials

The effect of randomness on the strength of high-entropy alloys

(2018) Luchan Zhang et al.   ACTA MATERIALIA

Effects of the stacking fault energy fluctuations on the strengthening of alloys

(2018) Yifei Zeng et al.   ACTA MATERIALIA

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

Mastering the game of Go without human knowledge

(2017) David Silver et al.   NATURE

Fast automated analysis of strong gravitational lenses with convolutional neural networks

(2017) Yashar D. Hezaveh et al.   NATURE

Dislocation mechanisms and 3D twin architectures generate exceptional strength-ductility-toughness combination in CrCoNi medium-entropy alloy

(2017) Zijiao Zhang et al.   Nature Communications

Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis

(2017) Franck Tancret et al.   MATERIALS & DESIGN

Machine learning unifies the modeling of materials and molecules

(2017) Albert P. Bartók et al.   Science Advances

Machine learning in materials informatics: recent applications and prospects

(2017) Rampi Ramprasad et al.   npj Computational Materials

First-principles prediction of high-entropy-alloy stability

(2017) Rui Feng et al.   npj Computational Materials

Neural network potential for Al-Mg-Si alloys

(2017) Ryo Kobayashi et al.   PHYSICAL REVIEW MATERIALS

Atomic-scale characterization and modeling of 60° dislocations in a high-entropy alloy

(2016) T.M. Smith et al.   ACTA MATERIALIA

A new approach to the analysis of short-range order in alloys using total scattering

(2016) L.R. Owen et al.   ACTA MATERIALIA

Thermal activation mechanisms and Labusch-type strengthening analysis for a family of high-entropy and equiatomic solid-solution alloys

(2016) Zhenggang Wu et al.   ACTA MATERIALIA

Theory of strengthening in fcc high entropy alloys

(2016) Céline Varvenne et al.   ACTA MATERIALIA

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials

(2016) Alexander V. Shapeev   MULTISCALE MODELING & SIMULATION

Machine-learning-assisted materials discovery using failed experiments

(2016) Paul Raccuglia et al.   NATURE

Metastable high-entropy dual-phase alloys overcome the strength–ductility trade-off

(2016) Zhiming Li et al.   NATURE

EfficientAb initioModeling of Random Multicomponent Alloys

(2016) Chao Jiang et al.   PHYSICAL REVIEW LETTERS

The generalization of Latin hypercube sampling

(2016) Michael D. Shields et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Reproducibility in density functional theory calculations of solids

(2016) K. Lejaeghere et al.   SCIENCE

Optimal Model Management for Multifidelity Monte Carlo Estimation

(2016) Benjamin Peherstorfer et al.   SIAM JOURNAL ON SCIENTIFIC COMPUTING

Exceptional damage-tolerance of a medium-entropy alloy CrCoNi at cryogenic temperatures

(2016) Bernd Gludovatz et al.   Nature Communications

Ab initio thermodynamics of the CoCrFeMnNi high entropy alloy: Importance of entropy contributions beyond the configurational one

(2015) Duancheng Ma et al.   ACTA MATERIALIA

Constructing high-dimensional neural network potentials: A tutorial review

(2015) Jörg Behler   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Gaussian approximation potentials: A brief tutorial introduction

(2015) Albert P. Bartók et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

(2015) A.P. Thompson et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Deep learning

(2015) Yann LeCun et al.   NATURE

Rapid theory-guided prototyping of ductile Mg alloys: from binary to multi-component materials

(2015) Zongrui Pei et al.   NEW JOURNAL OF PHYSICS

Atomic short-range order and incipient long-range order in high-entropy alloys

(2015) Prashant Singh et al.   PHYSICAL REVIEW B

Nanoscale origins of the damage tolerance of the high-entropy alloy CrMnFeCoNi

(2015) ZiJiao Zhang et al.   Nature Communications

Multilevel Monte Carlo methods

(2015) Michael B. Giles   ACTA NUMERICA

Ductility improvement of Mg alloys by solid solution: Ab initio modeling, synthesis and mechanical properties

(2014) S. Sandlöbes et al.   ACTA MATERIALIA

A fracture-resistant high-entropy alloy for cryogenic applications

(2014) B. Gludovatz et al.   SCIENCE

Guidelines in predicting phase formation of high-entropy alloys

(2014) Y. Zhang et al.   MRS Communications

High-Entropy Alloys: A Critical Review

(2014) Ming-Hung Tsai et al.   Materials Research Letters

Relative effects of enthalpy and entropy on the phase stability of equiatomic high-entropy alloys

(2013) F. Otto et al.   ACTA MATERIALIA

Considerations for choosing and using force fields and interatomic potentials in materials science and engineering

(2013) Chandler A. Becker et al.   CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE

Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

(2013) James E. Saal et al.   JOM

On representing chemical environments

(2013) Albert P. Bartók et al.   PHYSICAL REVIEW B

Microstructures and properties of high-entropy alloys

(2013) Yong Zhang et al.   PROGRESS IN MATERIALS SCIENCE

The relation between ductility and stacking fault energies in Mg and Mg–Y alloys

(2012) S. Sandlöbes et al.   ACTA MATERIALIA

AFLOW: An automatic framework for high-throughput materials discovery

(2012) Stefano Curtarolo et al.   COMPUTATIONAL MATERIALS SCIENCE

High-dimensional neural network potentials for metal surfaces: A prototype study for copper

(2012) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Inverse Design of High Absorption Thin-Film Photovoltaic Materials

(2012) Liping Yu et al.   Advanced Energy Materials

Mechanical properties of Nb25Mo25Ta25W25 and V20Nb20Mo20Ta20W20 refractory high entropy alloys

(2011) O.N. Senkov et al.   INTERMETALLICS

Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

(2011) Jörg Behler   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons

(2010) Albert P. Bartók et al.   PHYSICAL REVIEW LETTERS

Cluster expansion method for multicomponent systems based on optimal selection of structures for density-functional theory calculations

(2009) Atsuto Seko et al.   PHYSICAL REVIEW B

Multilevel Monte Carlo Path Simulation

(2008) Michael B. Giles   OPERATIONS RESEARCH