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RESEARCH PAPER · Advanced Powder Materials · 2021

A machine learning accelerated distributed task management system (Malac-Distmas) and its application in high-throughput CALPHAD computation aiming at efficient alloy design

Jianbao Gao, Jing Zhong, Guangchen Liu, Shenglan Yang, Bo Song, Lijun Zhang, Zuming Liu

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A machine learning accelerated distributed task management system (Malac-Distmas) and its application in high-throughput CALPHAD computation aiming at efficient alloy designOriginalBoosting for concept design of casting aluminum alloys driven by combining computational thermodynamics and machine learning techniques32Smart work – production tasks management system0Experimental and computational investigations on the SO2 poisoning of (La0.8Sr0.2)0.95MnO3 cathode materials11High-Throughput Screening of Optimal Process Parameters for PVD TiN Coatings With Best Properties Through a Combination of 3-D Quantitative Phase-Field Simulation and Hierarchical Multi-Objective Optimization Strategy12Asymmetric atomic sites make different: Recent progress in electrocatalytic CO2 reduction79Identification of the Eutectic Points in the Multicomponent Systems with the High-Throughput CALPHAD Approach13CO2 capture, separation, and storage on MgSiP2 monolayer: A first-principles study11Computer Alloy Design of Ti Modified Al-Si-Mg-Sr Casting Alloys for Achieving Simultaneous Enhancement in Strength and Ductility24Development of an accurate “composition-process-properties” dataset for SLMed Al-Si-(Mg) alloys and its application in alloy design21High-Entropy Materials Design by Integrating the First-Principles Calculations and Machine Learning: a Case Study in the Al-Co-Cr-Fe-Ni System0Multiscale modelling of irradiation damage behavior in high entropy alloys35Accelerated discovery of high-performance Al-Si-Mg-Sc casting alloys by integrating active learning with high-throughput CALPHAD calculations40Additive manufacturing of Ti–6Al–4V/Al–Cu–Mg multi-material structures with a Cu interlayer63Corrosion of Eutectic High-Entropy Alloys: A Review37On the Possibility of Replacing Scheil-Gulliver Modeling with Machine Learning and Neural Network Models3CAROUSEL: An Open-Source Framework for High-Throughput Microstructure Simulations4Mass uptake during oxidation of metallic alloys: Literature data collection, analysis, and FAIR sharing2Prediction of delta-ferrite formation in 17-4 PH steel using zero-inflated Gaussian process1Perspective: Bridging ML and CALPHAD for Multicomponent Alloy Design — A Position on Hybrid Workflows0Machine Learning Design for High-Entropy Alloys: Models and Algorithms53A CALPHAD thermodynamic model for multicomponent alloys under pressure and its application in pressurized solidified Al–Si–Mg alloys17Alloys innovation through machine learning: a statistical literature review14High-Entropy Materials Design by Integrating the First-Principles Calculations and Machine Learning: A Case Study in the Al-Co-Cr-Fe-Ni System7Multi-scale computational study of high-temperature corrosion and the design of corrosion-resistant alloys33Interfacial bonding mechanism of graphene nanoplatelets reinforced AZ91D magnesium alloy prepared by semi-solid injection molding17Enhancing classical Scheil–Gulliver model calculations by predicting generated phases and corresponding compositions through machine learning techniques4Data-driven design of novel lightweight refractory high-entropy alloys with superb hardness and corrosion resistance85Lattice-inspired NiTi-based metamaterials with widely tunable mechanical-superelastic synergy11An efficient microstructure simulation framework by integrating phase-field model, general coupling schema and parallelism: Demo in Ni-based superalloys3Phase diagram construction and prediction method based on machine learning algorithms8Accelerated discovery of near-zero ablation ultra-high temperature ceramics via GAN-enhanced directionally constrained active learning9High entropy alloy property predictions using a transformer-based language model27Design methods of high-entropy alloys: Current status and prospects21The synergy of machine learning and CALPHAD: Revitalizing traditional approaches16An additively manufactured near-eutectic Al–Ce–Ni–Ti–Zr alloy: microstructure, mechanical properties and heat resistance12Machine learning-driven insights into the microstructure and properties of high-entropy alloys14Review: Recent progress in titanium alloys development via machine learning and high-throughput preparation4Machine learning assisted quality control in metal additive manufacturing: a review30A computational framework for interface design using lattice matching, machine learning potentials, and active learning: A case study on LaCoO3/La2NiO42Artificial Intelligence for Microstructural and Functional Materials Assessment0Computational design of ultra-high thermal conductivity, crack-free aluminum alloys for additive manufacturing0Effects of Laser Scanning Speed on Sc‐Modified AlSi7Mg Alloy Fabricated by Selective Laser Melting: Microstructure and Nanomechanical Properties0Uncovering High-Dimensional Phase Diagram Through the Mixture of Experts Approach and Machine Learning0Machine learning-driven accelerated discovery of high-entropy alloys: From composition engineering to multifunctional property prediction0

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  1. Boosting for concept design of casting aluminum alloys driven by combining computational thermodynamics and machine learning techniques

    Journal of Materials Informatics · 2021-01-01

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  2. Smart work – production tasks management system

    Informatyka Ekonomiczna · 2021-01-01

    Krzysztof Chojnacki, Ewa Walaszczyk, Aleksandra Markowska, Marcin Hernes, Marcin Fojcik

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  3. Experimental and computational investigations on the SO2 poisoning of (La0.8Sr0.2)0.95MnO3 cathode materials

    Advanced Powder Materials · 2022-06-08

    Rui Wang, Lucas R. Parent, Srikanth Gopalan, Yu Zhong

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  4. High-Throughput Screening of Optimal Process Parameters for PVD TiN Coatings With Best Properties Through a Combination of 3-D Quantitative Phase-Field Simulation and Hierarchical Multi-Objective Optimization Strategy

    Frontiers in Materials · 2022-06-13

    Rao Dai, Shenglan Yang, Tongdi Zhang, Jing Zhong, Li Chen, Chunming Deng, Lijun Zhang

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  5. Asymmetric atomic sites make different: Recent progress in electrocatalytic CO2 reduction

    Nano Energy · 2022-09-16

    Yuchao Wang, Qichen Wang, Jiao Wu, Xin Zhao, Yu Xiong, Fenghua Luo, Yongpeng Lei

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  6. Identification of the Eutectic Points in the Multicomponent Systems with the High-Throughput CALPHAD Approach

    Journal of Phase Equilibria and Diffusion · 2022-10-25

    Jize Zhang, Rui Wang, Yu Zhong

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  7. CO2 capture, separation, and storage on MgSiP2 monolayer: A first-principles study

    Vacuum · 2022-11-21

    Jiahui Yu, Chaozheng He, Jinrong Huo, Chenxu Zhao, Lingmin Yu

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  8. Computer Alloy Design of Ti Modified Al-Si-Mg-Sr Casting Alloys for Achieving Simultaneous Enhancement in Strength and Ductility

    Materials · 2022-12-28

    Shaoji Zhang, Yi Wang, Jing Zhong, Jianbao Gao, Zhao Lu, Lijun Zhang

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  9. Development of an accurate “composition-process-properties” dataset for SLMed Al-Si-(Mg) alloys and its application in alloy design

    Journal of Materials Informatics · 2023-01-01

    Tianchuang Gao, Jianbao Gao, Jinliang Zhang, Bo Song, Lijun Zhang

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  10. High-Entropy Materials Design by Integrating the First-Principles Calculations and Machine Learning: a Case Study in the Al-Co-Cr-Fe-Ni System

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    Yu Zhong, Guangchen Liu, Songge Yang

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  11. Multiscale modelling of irradiation damage behavior in high entropy alloys

    Advanced Powder Materials · 2023-02-13

    Fusheng Tan, Li Li, Jia Li, Jia Li, Jia Li, Peter Kaehuei Liaw, Qihong Fang

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  12. Accelerated discovery of high-performance Al-Si-Mg-Sc casting alloys by integrating active learning with high-throughput CALPHAD calculations

    Science and Technology of Advanced Materials · 2023-04-11

    Jianbao Gao, Jing Zhong, Guangchen Liu, Shaoji Zhang, Jiali Zhang, Zuming Liu, Bo Song, Lijun Zhang

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  13. Additive manufacturing of Ti–6Al–4V/Al–Cu–Mg multi-material structures with a Cu interlayer

    International Journal of Mechanical Sciences · 2023-05-24

    Jinliang Zhang, Xiaobo Wang, Jianbao Gao, Lei Zhang, Bo Song, Lijun Zhang, Yonggang Yao, Jian Lü, Yusheng Shi

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  14. Corrosion of Eutectic High-Entropy Alloys: A Review

    Crystals · 2023-08-09

    Kaiyang Li, Yunlong Zhai, Minjie Lai, Min Jung Song, Shanfang Zou, Guojie Huang, Khurram Yaqoob, Zhangwei Wang, Naiqiang Zhang

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  15. On the Possibility of Replacing Scheil-Gulliver Modeling with Machine Learning and Neural Network Models

    Diffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2023-08-24

    Ziyu Li, He Tan, Lucia Lattanzi, Anders E. W. Jarfors, Per Jansson

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  16. CAROUSEL: An Open-Source Framework for High-Throughput Microstructure Simulations

    Integrating materials and manufacturing innovation · 2023-10-23

    Sebastian Carrion Ständer, Nora Barschkett, Evgeniya Kabliman

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  17. Mass uptake during oxidation of metallic alloys: Literature data collection, analysis, and FAIR sharing

    Computational Materials Science · 2023-12-01

    Saswat Mishra, Sharmila Karumuri, Vincent Mika, Collin Scott, C. L. Choy, Kenneth H. Sandhage, Ilias Bilionis, Michael S. Titus, Alejandro H. Strachan

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  18. Prediction of delta-ferrite formation in 17-4 PH steel using zero-inflated Gaussian process

    Materials Today Communications · 2023-12-24

    Nandana Menon, Derek J. Shaffer, Todd A. Palmer, Amrita Basak

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  19. Perspective: Bridging ML and CALPHAD for Multicomponent Alloy Design — A Position on Hybrid Workflows

    Journal of Computational and Data-Driven Materials Engineering · 2024-01-01

    Emily Johnson, Robert Smith, Laura Brown, Kevin Miller

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  20. Machine Learning Design for High-Entropy Alloys: Models and Algorithms

    Metals · 2024-02-15

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  21. A CALPHAD thermodynamic model for multicomponent alloys under pressure and its application in pressurized solidified Al–Si–Mg alloys

    Advanced Powder Materials · 2024-02-27

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  22. Alloys innovation through machine learning: a statistical literature review

    Science and Technology of Advanced Materials Methods · 2024-03-04

    Alireza Valizadeh, Ryoji Sahara, Maaouia Souissi

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  23. High-Entropy Materials Design by Integrating the First-Principles Calculations and Machine Learning: A Case Study in the Al-Co-Cr-Fe-Ni System

    High Entropy Alloys & Materials · 2024-07-04

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  24. Multi-scale computational study of high-temperature corrosion and the design of corrosion-resistant alloys

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  25. Interfacial bonding mechanism of graphene nanoplatelets reinforced AZ91D magnesium alloy prepared by semi-solid injection molding

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  26. Enhancing classical Scheil–Gulliver model calculations by predicting generated phases and corresponding compositions through machine learning techniques

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  27. Data-driven design of novel lightweight refractory high-entropy alloys with superb hardness and corrosion resistance

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  28. Lattice-inspired NiTi-based metamaterials with widely tunable mechanical-superelastic synergy

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  29. An efficient microstructure simulation framework by integrating phase-field model, general coupling schema and parallelism: Demo in Ni-based superalloys

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  30. Phase diagram construction and prediction method based on machine learning algorithms

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  31. Accelerated discovery of near-zero ablation ultra-high temperature ceramics via GAN-enhanced directionally constrained active learning

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  35. An additively manufactured near-eutectic Al–Ce–Ni–Ti–Zr alloy: microstructure, mechanical properties and heat resistance

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  37. Review: Recent progress in titanium alloys development via machine learning and high-throughput preparation

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  38. Machine learning assisted quality control in metal additive manufacturing: a review

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  39. A computational framework for interface design using lattice matching, machine learning potentials, and active learning: A case study on LaCoO3/La2NiO4

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  44. Machine learning-driven accelerated discovery of high-entropy alloys: From composition engineering to multifunctional property prediction

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