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RESEARCH PAPER · npj Computational Materials · 2019

A property-oriented design strategy for high performance copper alloys via machine learning

Changsheng Wang, Huadong Fu, Lei Jiang, Dezhen Xue, Jianxin Xie

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A property-oriented design strategy for high performance copper alloys via machine learningOriginalDramatically Enhanced Combination of Ultimate Tensile Strength and Electric Conductivity of Alloys via Machine Learning Screening310Machine learning in materials genome initiative: A review231Machine learning assisted design of γ′-strengthened Co-base superalloys with multi-performance optimization120Cluster-formula-embedded machine learning for design of multicomponent β-Ti alloys with low Young’s modulus78Data augmentation in microscopic images for material data mining128Current Challenges and Opportunities in Microstructure-Related Properties of Advanced High-Strength Steels257Dynamic recrystallization behavior and microstructure evolution of high‐performance Cu–3.28Ni–0.6Si–0.22Zn–0.11Cr–0.04P during hot compression12Data-driven microstructure sensitivity study of fibrous paper materials20Accelerated discovery of high-strength aluminum alloys by machine learning105Emergent Opportunities with Metallic Alloys: From Material Design to Optical Devices29Machine learning-assisted discovery of strong and conductive Cu alloys: Data mining from discarded experiments and physical features86Dirty engineering data-driven inverse prediction machine learning model24Artificial intelligence and machine learning in design of mechanical materials690Designing Al-Zn-Mg-Cu Alloys Using Machine Learning1Machine Learning Assisted Composition Effective Design for Precipitation Strengthened Copper Alloys259Machine learning-guided design and development of metallic structural materials27Discovery of Lead-Free Hybrid Organic/Inorganic Perovskites Using Metaheuristic-Driven DFT Calculations30Text mining of hypereutectic Al-Si alloys literature based on active learning9First Principle Study on Mg2X (X = Si, Ge, Sn) Intermetallics by Bi Micro-Alloying9Machine Learning-Enabled Design and Prediction of Protein Resistance on Self-Assembled Monolayers and Beyond41Multi-objective machine learning of four mechanical properties of steels14Composition-tuned lithium aluminosilicate as a new humidity-sensing ceramic material with high sensitivity9The learning of the precipitates morphological parameters from the composition of nickel-based superalloys20Machine Learning-Enabled Repurposing and Design of Antifouling Polymer Brushes55Deciphering controversial results of cell proliferation on TiO2 nanotubes using machine learning16Accelerated discovery of high-performance Cu-Ni-Co-Si alloys through machine learning84Discovery of aluminum alloys with ultra-strength and high-toughness via a property-oriented design strategy170A Property‐Driven Stepwise Design Strategy for Multiple Low‐Melting Alloys via Machine Learning26A reverse design model for high-performance and low-cost magnesium alloys by machine learning48Materials Informatics for Mechanical Deformation: A Review of Applications and Challenges67Machine learning assisted modelling and design of solid solution hardened high entropy alloys97A machine learning-based alloy design system to facilitate the rational design of high entropy alloys with enhanced hardness335Data privacy protection in microscopic image analysis for material data mining0Design of high strength and electrically conductive aluminium alloys by machine learning14Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algorithm9Review on the Use of Machine Learning Techniques to Optimize the Processing of Copper Alloys in Additive Manufacturing0Segmentation and Measurement of Superalloy Microstructure Based on Improved Nonlocal Block4Composition design of high yield strength points in single-phase Co–Cr–Fe–Ni–Mo multi-principal element alloys system based on electronegativity, thermodynamic calculations, and machine learning13Predicting the property contour-map and optimum composition of Cu-Co-Si alloys via machine learning20Vacancy dependent mechanical behaviors of high-entropy alloy48A Focused Review on Engineering Application of Multi-Principal Element Alloy45Mechanical performances and processing-property modeling for Al0.3CoCrFeNiMn high-entropy alloy17Hardness prediction of high entropy alloys with machine learning and material descriptors selection by improved genetic algorithm97Automated pipeline for superalloy data by text mining83A Vision of Materials Genome Engineering in China36Investigation of nanomachining-induced plastic behavior using machine learning-assisted high-throughput molecular dynamics simulations8Simultaneous enhancement of mechanical and electrical properties of Cu–Ni–Si alloys via thermo-mechanical process73Relative density prediction of additively manufactured Inconel 718: a study on genetic algorithm optimized neural network models27Corrosion Behaviors of Supersaturated and Peak-Aged CuNiSiCr Alloys under Salt Spray Environment1A property-oriented design strategy of high-strength ductile RAFM steels based on machine 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Alloys via Interpretive Machine Learning52Accelerating spin Hall conductivity predictions via machine learning6Accelerated composition-process-properties design of precipitation-strengthened copper alloys using machine learning based on Bayesian optimization17Advances in machine learning methods in copper alloys: a review9Multi-model integration accelerates Al-Zn-Mg-Cu alloy screening9In silico design and prediction of metastable quaternary phases in Cu–Ni–Si–Cr alloys3Physics-coupled data-driven design of high-temperature alloys12

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