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RESEARCH PAPER · Materials Science and Engineering R Reports · 2023

Recent applications of machine learning in alloy design: A review

Mingwei Hu, Qiyang Tan, Ruth Knibbe, Miao Xu, Bin Jiang, Sen Wang, Xue Li, Mingxing Zhang

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Recent applications of machine learning in alloy design: A reviewOriginalCurrent application status of multi-scale simulation and machine learning in research on high-entropy alloys823D-printed microfluidic system for the in situ diagnostics and screening of nanoparticles synthesis parameters16Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations32Review on applications of artificial neural networks to develop high entropy alloys: A state-of-the-art technique47Machine Learning in Enhancing Corrosion Resistance of Magnesium Alloys: A Comprehensive Review21Development of High-Strength Mg–Gd–Y Alloy Based on Machine Learning Method2Neural Networks for Prediction of Swelling in Austenitic Steels Irradiated by Fast Neurons0Unsupervised learning and pattern recognition in alloy design15Enhancing the mechanical properties of high-entropy alloys through severe plastic deformation: A review52Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization40The Prediction of Flow Stress in the Hot Compression of a Ni-Cr-Mo Steel Using Machine Learning Algorithms7A Comprehensive Review of Machine Learning Application Across Different Domains3Review on Cellular Automata for Microstructure Simulation of Metallic Materials34Machine learning-based performance predictions for steels considering manufacturing process parameters: a review26Estimating the lattice thermal conductivity of AlCoCrNiFe high-entropy alloy using machine learning16Multivariate Gaussian process surrogates for predicting basic structural parameters of refractory non-dilute random alloys5Comparison of Predictive Modeling Concrete Compressive Strength with Machine Learning Approaches7Development of Neural Networks to Study Flow Behavior of Medium Carbon Microalloyed Steel during Hot Forming4Design of advanced steels by integrated computational materials engineering40Customised product design optimisation considering module synergy effects and expert preferences8Assessment of Bayesian guidance strategy to develop bake-hardening ferritic steel5Designing unique and high-performance Al alloys via machine learning: Mitigating data bias through active learning24Tribo-informatics analysis of in-situ TiC reinforced ZA27 alloy: Microstructural insights and wear performance modeling by machine learning32Prediction and analysis of mechanical properties of hot-rolled strip steel based on an interpretable machine learning21Discovery of novel materials through machine learning24Machine Learning Algorithms for Prediction and Characterization of Cohesive Zone Parameters for Mixed-Mode Fracture8Morphogenic Modeling of Corrosion Reveals Complex Effects of Intermetallic Particles10Preparation of a novel laser cladding Ni-based alloy with promising applications in high-temperature conditions: Genetic design, multi-phase evolution, and synergy mechanism9Large Language Models as Molecular Design Engines43Density Functional Theory and Machine Learning of Transition Metals in Mo2C for Gas Sensors12Neural networks for prediction of swelling in austenitic steels irradiated by fast neutrons5Investigation of age-hardening behaviour of Al alloys via feature screening-assisted machine learning14Enhancing high-fidelity neural network potentials through low-fidelity sampling2Fatigue Life Prediction of 2024-T3 Al Alloy by Integrating Particle Swarm Optimization—Extreme Gradient Boosting and Physical Model21Superconductor Discovery in the Emerging Paradigm of Materials Informatics8Inverse prediction of Al alloy post-processing conditions using classification with guided oversampling3Recent machine learning-driven investigations into high entropy alloys: A comprehensive review37Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectives124Robustness of machine learning predictions for Fe-Co-Ni alloys prepared by various synthesis methods8Alloy design for 3D-printed shape memory alloys2Artificial intelligence-driven revolution in nanozyme design: from serendipity to rational engineering59Machine Learning for the Design of High Entropy Alloys: A Review3Machine Learning-Based Methods for Materials Inverse Design: A Review34Performance-Driven Inverse Design of Mg-Mn-Based Wrought Magnesium Alloys Based on Conditional Generative Adversarial Networks and Small Sample Dataset0Amorphous-dominated MgO hollow spheres enhanced fluoride adsorption: Mechanism analysis and machine learning prediction7Online mechanical property prediction and automatic product release for hot rolled steel strip products using artificial neural network models1Prediction of post-irradiation swelling rate of 316L stainless steel based on Variational Autoencoders and interpretable machine learning6A Novel Aluminium Alloys Design Strategy for Low Usage of Critical Raw Materials and High Casting Processibility for Automotive Applications7Accelerated design of high-entropy alloy coatings for high corrosion resistance via machine learning16Deep learning-aided preparation and mechanism revaluation of waste wood lignocellulose-based flame-retardant composites12Machine Learning Assisted Design of High Thermal Conductivity and High Strength Mg Alloys8An interpretable and reliable framework for alloy discovery in thermomechanical processing3Realization and Inverse Design of Multifunctional Steerable Transflective Linear-to-Circular Polarization Converter Empowered by Machine Learning1Integration of multiscale simulations and machine learning for predicting dendritic microstructures in solidification of alloys16Influence of Alloy Composition on the Tribomechanical Properties of 50% Blend of CoCrWMoCFeNiSiMn (Stellite 1) and CoCrMoCFeNiSiMn (Stellite 21) Alloys1145Chapter 6 Future trends and research challenges in smart alloys2Accelerated material discovery of high-performance Mg alloys via active learning and high throughput multi-objective informed Bayesian optimization7High-throughput design strategy for creep-resistance steel using machine learning and optimization algorithm0Design of BCC/FCC dual-solid solution refractory high-entropy alloys through CALPHAD, machine learning and experimental methods32Bayesian optimization and explainable machine learning for High-dimensional multi-objective optimization of biodegradable magnesium alloys42Atomic Energy Accuracy of Neural Network Potentials: Harnessing Pretraining and Transfer Learning6Explainable machine learning for predicting tensile properties of aluminum alloys in the laser powder bed fusion process16Influence of voids structure parameters on frost resistance of phase change concrete: ICT non – destructive testing and machine learning6Inverse Engineering of Mg Alloys Using Guided Oversampling and Semi‐Supervised Learning1Machine Learning Unveils the Impacts of Key Elements and Their Interaction on the Ambient-Temperature Tensile Properties of Cast Titanium Aluminides Employing SHAP Analysis8Machine learning assisted phase prediction of refractory multi-component alloys based on data from low-, medium-, and high-entropy alloys10Machine learning-driven alloy digital design for hydrogen storage: a review12Accelerated computational design of BCC refractory high entropy alloys using metaheuristics, CALPHAD, and artificial neural networks7DSMR: an AI framework for exploring combinations of data and algorithm to overcome efficiency-accuracy trade-off2AAKAN-WGAN: Predicting mechanical properties of magnesium alloys based on generative design and adaptive activation of Kolmogorov-Arnold Networks5Additive manufacturing metallurgy guided machine learning design of versatile alloys54Machine learning for obtaining values of thermomechanical processing parameters of high-entropy alloys with desirable strength and ductility13Composition Design of a Novel High-Temperature Titanium Alloy Based on Data Augmentation Machine Learning7Review of machine learning-assisted multi-property design of high-entropy alloys: phase structure, mechanical, tribological, corrosion, and hydrogen storage properties18Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space4Machine Learning Approaches for Heat Treatment in Thermal Manufacturing Processes: A Review9Machine learning-driven insights into the microstructure and properties of high-entropy alloys14Accelerated design and property validation of L12-strengthened Co-Ni-Cr-Al-Cu-Ti high-entropy superalloys based on unsupervised and supervised learning4Multi-objective optimization of corrosion resistance, strength, ductility properties of weathering steel utilizing interpretable attention-based deep learning model6Research on microstructure and corrosion resistance of hypoeutectic Al-5Mg-2Si-xMn alloys based on machine learning1Data-driven design of Al–Fe alloys for laser powder bed fusion to enhance recycled aluminum utilization8A physics-informed machine learning framework for accelerated discovery of single-phase B2 multi-principal element intermetallics17Review: Recent progress in titanium alloys development via machine learning and high-throughput preparation4Achieving interpretable and efficient design of lightweight multi-principal element alloys via machine learning with optimized strengthening-toughening models14Elucidating the key drivers of twin formation in copper alloys via a small-sample AutoML framework0Analysis of thermal conductivity of aluminum alloys by compositions and tempering process using machine learning11BO2L: Two-Layer Bayesian Optimization for Geographical Traveling Salesman Problem1Amorphous High-Entropy Alloys as Innovative Materials for Hydrogen Energy: State of the Art and Development Prospects2Machine learning approach to predict Curie temperature in binary alloys2Achieving simultaneous strength-ductility enhancement of Sn Bi alloys via ultrasonic hierarchical refinement3Enhancing 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materials: A transformative frontier and complementary enabler of the rational alloy design framework10Machine learning-driven design of high-strength ductile Al-Si alloys for casting applications3Predictive Modeling of Porosity Formation in Directionally Solidified AlSi10Mg Alloy: Effects of Temperature Gradient, Solidification Time, and Interface Velocity0Synergistic enhancement of strength and corrosion resistance in Al-Mg-Si alloys through chemical composition design via machine learning approaches8Harnessing the power of α-Mg: Unveiling the matrix phase’s role in Mg alloys from structure to function5An interatomic-energy-based new materials design strategy combining DFT calculations and active machine learning6Machine Learning to Classify and Predict Machinability Index of AISI Low Alloy Steels Based on Chemical Composition and Manufacturing Processes0Machine learning-assisted exploration and experimental assessment of β-type Ti54-xZr15Nb14Mo17Cux alloy with an ultra-low modulus for orthopedic applications1Advances in graph neural networks for alloy design and properties predictions: a review8Machine learning-driven new paradigm for Co-based superalloys3Data‐Driven Design and Fabrication of Heat‐Resistant, Ultrastrong, Lightweight Aluminum‐Based Entropy Alloy by Additive Manufacturing5Prediction of impact damage to Fe-based amorphous coatings via interpretable machine learning0Generative Design for Alloys: Harnessing Generative Models for Faster Discovery6Revolutionizing multi-scale phase identification in superalloys via advanced CNN-transformer integration3Machine learning-assisted design of lightweight refractory high-entropy alloys: A comprehensive review50Investigating the effects of extrusion temperature and speed on the mechanical properties of high-strength Al-Mg-Si alloys using machine learning methods2Machine learning technique for prediction of crystal structure in austenitic and martensitic phase of Ni–Mn-based Heusler alloys1A comprehensive review of machine learning for superalloys: from data-driven prediction to intelligent design2Integration of machine learning and traditional methods for accurate prediction of hot deformation behavior in TC4-Ce titanium alloy2Prediction of mechanical properties of magnesium alloys through machine learning: a review0Machine Learning for Alloy Design: A Property-Oriented Review3Denoising diffusion probabilistic model-based tabular data augmentation for improved phase classification of high-entropy alloys2A multidimensional continuous conditional generative adversarial network to link composition-process-microstructure-properties in Mg alloys5Physics-informed machine learning for mapping of composition and mechanical properties in 316L/AlCrFeNi multi-material alloys fabricated by directed energy deposition1Modeling High-Entropy Alloys: Challenges, Progress, and Future Directions0Interpretable corrosion rate prediction and rational design of amorphous alloy coatings: a deep learning framework with DenseLoss and SHAP interpretability0Machine learning driven discovery of low modulus biomedical titanium alloys for additive manufacturing11Machine learning driven advances in hardness prediction and artificial intelligence based phase classification in aluminium-high entropy alloy systems0Deliberation of using alloy as high temperature thermal energy storage material for concentrated solar power applications – A comprehensive review3Machine learning-assisted interpretable and leakage-resistant prediction of PVA/HA hydrogel mechanical properties under small-sample conditions1Enhancing multi-component alloy composition prediction based on generative adversarial networks and proximal policy optimization2Semantic Embeddings of Chemical Elements for Enhanced Materials Inference and Discovery4Challenges and opportunities in machine learning for metal additive manufacturing: data scarcity and interpretability4Discovering Hidden Relationships of Alloy Properties with Manifold Learning0A survey of machine learning applications for Mg alloys: A promising prospect for current trends and future directions2Recent Advancements in Aluminum Alloy Research: Integrating Traditional Metallurgy with Machine Learning and Data-Driven Approaches3Review: next-generation metal hydride systems for sustainable hydrogen storage—kinetics, nanostructuring, and intelligent materials discovery4Application and challenges of artificial intelligence technology in ODS steel research: A review0Advancing breakthrough design of superior strength-ductility synergy of lead-free solder alloys via interpretable machine learning and iterative optimization0Multimodal adaptive machine learning to assist design of non-heat treatable high pressure die-casting Al-Si alloys0Intelligent visualization-driven materials design via two-dimensional symbolic feature generation0Data-driven design of lightweight alloys: A comprehensive review and a challenge0Multi-model structure-agnostic framework for enhanced materials discovery in engineering informatics1Transfer learning-enabled high-precision prediction and multi-objective design of cryogenic aluminum alloys with enhanced strength-ductility synergy0Data-driven multi-objective optimization for corrosion-resistant Fe-Cr-Ni-Al system multi-principal element alloys and its corrosion behavior0Inclusion-microstructure-hydrogen trap synergy in pipeline steels: From hydrogen trapping kinetics to microalloying design against hydrogen-induced damage: A critical review0Utilizing hybrid BIGRU-LIGHTGBM model for mechanical characteristics prediction in aluminium alloys0Machine learning-driven accelerated discovery of high-entropy alloys: From composition engineering to multifunctional property prediction0Synchronously enhancing the corrosion resistance and hardness of novel Zn-Al alloy via an improved interpretable machine learning framework0Machine Learning for Structural Steels: Materials Design, Property Prediction, Durability, and Future Directions0Data-Driven Phase Prediction of BCC Refractory High-Entropy Alloys for Advanced Engineering Applications0Data-driven modeling on design and frictional response of high-entropy alloys through material composition variation0

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