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RESEARCH PAPER · Computers, materials & continua/Computers, materials & continua (Print) · 2025

Machine Learning-Based Methods for Materials Inverse Design: A Review

Yingli Liu, Yuting Cui, Haihe Zhou, Tao Shen, Sheng Lei, Haibin Yuan, Jiancheng Yin

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42 direct citing works

Machine Learning-Based Methods for Materials Inverse Design: A ReviewOriginalPerspective: From Prediction to Design — A Position on Optimization-Centric Workflows in Materials ML0Machine learning-driven optimization of wear-resistant high-manganese steel properties: achieving multi-property matching under specified composition2A review on mechanical metamaterials: Exploring negative Poisson's ratio, energy absorption, failure mechanisms, and current research frontiers9Artificial Intelligence for Materials Discovery, Development, and Optimization171MatPC: Prompting Large Language Model, Crystal Structure Prediction, and First-Principles for Semantic-Driven Material Design3Paths to ultimate enhanced oil recovery by chemical flooding1A machine learning based inverse design method for high-performance copper alloys0AI-Driven inverse design of 3D-printed continuous fiber composites using multiscale homogenization and dual neural networks0SIGD: symmetry and interface guided diffusion architectures for inverse design engineering of 2D semiconductor materials1Optimization of Johnson-Cook constitutive parameters of titanium alloy based on a machine learning-accelerated genetic algorithm3Convergence of Computational Materials Science and AI for Next-Generation Energy Storage Materials6Accelerating Steel Design with Multi-objective Machine Learning0A dual-descriptor machine learning framework for evaluating perovskite passivation materials0Artificial intelligence-driven nanomaterial design and applications: advances, challenges, and future directions0A machine learning framework for high-strength Mo-Re alloy design2Evolving Beyond Nature: AI-Driven Rapid Advancements of Bio-Inspired Electronic Skin1AI-Driven inverse design of 3D-printed continuous fiber composites using multiscale homogenization and dual neural networks23D truss absorbing metamaterial empowered by artificial intelligence: Reverse design and performance breakthrough0Review: Recent research progress in materials for laser ablation protection0Sensitivity and Performance Analysis of an AI Model for Virtual Prototyping of Brazed Ceramic–Metal Composite Materials0Active matter as a framework for living systems-inspired Robophysics1AI-guided design of optoelectronic molecularly modified CH 3 NH 3 PbI 3 perovskite thin films with improved aqueous stability1From High-Throughput Screening to Generative Design: Artificial Intelligence-Driven Dielectric Materials Discovery2Parametric Optimization of WEDM by Firefly Algorithm for High Manganese Steel Material0MatterMind: A User‐Friendly Material Design Platform Assisted by Large Language Model0Research on Automatic Construction and Optimization of Aircraft Knowledge Triples in Avionics0Surrogate-assisted inverse design of irregular elliptical perforated metamaterials with target nonlinear stiffness0Inverse Design of 3D-Printed Composite Material Properties via Physics-Informed Diffusion Models0Leveraging microstructure as a learnable bridge for inverse design of high-hardness alloys via deep reinforcement learning0A deep learning framework for inverse design of non-unique photonic structures: A DBSCAN-based quantitative analysis method0Research Advances Towards Machine Learning‐Driven Fabrication of Electrospun Films With Excellent Performances0Circumventing query complexity barriers in learning quantum dynamics via physics-informed kernels0Artificial Intelligence‐Driven Inverse Design of Singlet Fission Candidates in the Acene family1Machine Learning-Driven Lightweight Design of Materials for Police Protective Equipment: A Methodological Framework and Validation Study0

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  1. Perspective: From Prediction to Design — A Position on Optimization-Centric Workflows in Materials ML

    Journal of Computational and Data-Driven Materials Engineering · 2025-01-01

    Mohammed Al-Farsi, Salim Al-Harthy, Nasser Al-Rawahi

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  2. Machine learning-driven optimization of wear-resistant high-manganese steel properties: achieving multi-property matching under specified composition

    Journal of Materials Science · 2025-05-29

    Ruizhi Han, Shuai Zhao, Rong Mu, Renbo Song

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  3. A review on mechanical metamaterials: Exploring negative Poisson's ratio, energy absorption, failure mechanisms, and current research frontiers

    Proceedings of the Institution of Mechanical Engineers Part L Journal of Materials Design and Applications · 2025-07-21

    Fredrick Madaraka Mwema, Ndivhuwo Ndou

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  4. Artificial Intelligence for Materials Discovery, Development, and Optimization

    ACS Nano · 2025-07-25

    Benediktus Madika, Aditi Saha, Chaeyul Kang, Batzorig Buyantogtokh, Joshua Agar, Chris M. Wolverton, Peter W. Voorhees, P. B. Littlewood, Sergei V. Kalinin, Seungbum Hong

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  5. MatPC: Prompting Large Language Model, Crystal Structure Prediction, and First-Principles for Semantic-Driven Material Design

    ACS Applied Materials & Interfaces · 2025-07-28

    Jiacheng Zhou, Bo Xiao, Qi Liu, Lifeng Liu, Lei Zhang

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  6. Paths to ultimate enhanced oil recovery by chemical flooding

    Scientia Sinica Chimica · 2025-08-11

    Weifeng Lv, Yuan Li, Qun Zhang, Bin Ding, Zhaohui Zhou, Jianlong Xiu, Xinyuan Zou

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  7. A machine learning based inverse design method for high-performance copper alloys

    Materials Today Communications · 2025-10-01

    Yingli Liu, Yuting Cui, Jiancheng Yin, Haihe Zhou

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  8. AI-Driven inverse design of 3D-printed continuous fiber composites using multiscale homogenization and dual neural networks

    Research Square · 2025-10-06

    Tien‐Dat Hoang, Van Dam Vu, Thanh Dang Nguyen, Tien Son Bui, Binh Thanh Nguyen, Thanh Quang Nguyen

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  9. SIGD: symmetry and interface guided diffusion architectures for inverse design engineering of 2D semiconductor materials

    Machine Learning Science and Technology · 2025-10-07

    Yaofo Chen, Qing An, Weihua Yang, Zhongyuan Lai, Yu‐Hua Wen, Tundong Liu

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  10. Optimization of Johnson-Cook constitutive parameters of titanium alloy based on a machine learning-accelerated genetic algorithm

    Materials Today Communications · 2025-10-15

    Shan Li, Pengfei Hao, Shun Xu, Lin H. Yang, Qunbo Fan

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  11. Convergence of Computational Materials Science and AI for Next-Generation Energy Storage Materials

    Journal of Electronic Materials · 2025-11-21

    Xuexue Pan, Yuanlin Xie, Chujun Li, Yangyang He, Yitong Zhang, Yilin Wang, Zhichun Li, Peiyu Peng, Jun Wang

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  12. Accelerating Steel Design with Multi-objective Machine Learning

    JOM · 2025-12-22

    Jiazheng Zhao, Shengen Zhang, Jian Wang, Jun Bao Zhang, Jun Li, Jingge Dai, Fenghua Luo

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  13. A dual-descriptor machine learning framework for evaluating perovskite passivation materials

    RSC Advances · 2026-01-01

    Yao Lu, Jie Dong, Juan Meng, Yaoyao Li, Jiao Wu, Ning Meng, Xiaomin Huo, Suling Zhao, Zheng Xu, Dandan Song

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  14. Artificial intelligence-driven nanomaterial design and applications: advances, challenges, and future directions

    New Journal of Chemistry · 2026-01-01

    Yakubu Adekunle Alli, Lukman Shehu Mustapha, Francis Mekunye, Olaoluwa John Adeleke, Terfa Jude Igba, Nelson Oshogwue Etafo, Victor D. Aderibigbe, Sreedeep Dey, Haulison Kojo Yayoh, Kehinde Shola Obayomi, Malama Chisanga

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  15. A machine learning framework for high-strength Mo-Re alloy design

    Journal of Alloys and Compounds · 2026-03-01

    Guixin Chen, Yonggang Yan, Yi Fan Zhao, Hui Li, Dong Wang, Xunxiang Hu

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  16. Evolving Beyond Nature: AI-Driven Rapid Advancements of Bio-Inspired Electronic Skin

    ACS Applied Materials & Interfaces · 2026-03-24

    Domenic Quiquero, Reza Noroozi, Kaiting Wang, Rachael Conliffe, Haotian Shi

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  17. AI-Driven inverse design of 3D-printed continuous fiber composites using multiscale homogenization and dual neural networks

    The International Journal of Advanced Manufacturing Technology · 2026-03-28

    Tien Dat Hoang, Chu Van Nhat, Nguyen Thanh Dang, Bùi Tiến Sơn, Nguyen Ba Thuan, Thanh Huân Nguyễn

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  18. 3D truss absorbing metamaterial empowered by artificial intelligence: Reverse design and performance breakthrough

    Sustainable materials and technologies · 2026-04-01

    Yan Hu, Senlin Tian, Yingjie Li

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  19. Review: Recent research progress in materials for laser ablation protection

    Emergent Materials · 2026-04-01

    Haichao Yuan, Zhiyuan Jing, Tao Dong, Zhibin Zhang, Mingyu Song, Zhenfeng Hu, Xiubing Liang

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  20. Sensitivity and Performance Analysis of an AI Model for Virtual Prototyping of Brazed Ceramic–Metal Composite Materials

    International Journal of Applied Ceramic Technology · 2026-04-01

    Sunita Khod, Vinay Kamma, Ravi Kumar Varma, Mayank Goswami

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  21. Active matter as a framework for living systems-inspired Robophysics

    Europhysics Letters (EPL) · 2026-04-09

    Giulia Janzen, Gaia Maselli, Juan Francisco Jiménez Castellanos, Lia Garcia-Perez, Daniel Alejandro Matoz Fernandez, Chantal Valeriani

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  22. AI-guided design of optoelectronic molecularly modified CH 3 NH 3 PbI 3 perovskite thin films with improved aqueous stability

    AI for Science · 2026-05-09

    Lei Zhang, Youle Wang, Yinguo Zhou, Cunyu Li

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  23. From High-Throughput Screening to Generative Design: Artificial Intelligence-Driven Dielectric Materials Discovery

    ACS Applied Materials & Interfaces · 2026-05-20

    Jiayi Tang, Liang Cao, Guanghui Xu, Ming Li

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  24. Parametric Optimization of WEDM by Firefly Algorithm for High Manganese Steel Material

    Journal of The Institution of Engineers (India) Series C · 2026-05-25

    Sachindra Kumar, Om Ji Shukla, Sonu Rajak

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  25. MatterMind: A User‐Friendly Material Design Platform Assisted by Large Language Model

    Materials Genome Engineering Advances · 2026-06-01

    Kaiyang Xu, Yujun Lu, Lifeng Liu, Lei Zhang

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  26. Research on Automatic Construction and Optimization of Aircraft Knowledge Triples in Avionics

    International Conference on Electronic Engineering and Informatics (EEI) · 2026-06-01

    Sheng Feng, Zhimin Chen

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  27. Surrogate-assisted inverse design of irregular elliptical perforated metamaterials with target nonlinear stiffness

    Physica Scripta · 2026-06-30

    Yifan Zheng, Xiaotian Zhang, Chunnan Liu, Zelin Zhang, Zhenhua Zhang

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  28. Inverse Design of 3D-Printed Composite Material Properties via Physics-Informed Diffusion Models

    Unknown journal · 2026-07-01

    Shahd Mahdi, Mayasa M. Abdulrahman, Lateef Abd Zaid Qudr, Dima Haider Rasheed, Ravi Sekhar, Pritesh Shah, Bourair Al-Attar, Karam S. Khalid, Ahmed Dheyaa Radhi

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  29. Leveraging microstructure as a learnable bridge for inverse design of high-hardness alloys via deep reinforcement learning

    Materials Today Communications · 2026-07-01

    Shun-li Zhang, Qing Liu

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  30. A deep learning framework for inverse design of non-unique photonic structures: A DBSCAN-based quantitative analysis method

    Modern Physics Letters B · 2026-07-31

    Zhirui Wang, Xiaogen Yuan, Haobin Zhan, Xiaoqiao Wang, Jianping Guo

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  31. Research Advances Towards Machine Learning‐Driven Fabrication of Electrospun Films With Excellent Performances

    Polymer Engineering and Science · 2026-08-01

    Jun Tong, Ruiqi Yuan, 晓清 田, Zhifeng Wang, Min Wu, Haichen Zhang, Wei Li, Bin Lan, Minqing Liu, Siao Zeng, 陈海初, Lan Liao, Dejun Yan, Yuzhong Rao

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  32. Circumventing query complexity barriers in learning quantum dynamics via physics-informed kernels

    Quantum Science and Technology · 2026-08-12

    Youle Wang, Lei Zhang

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  33. Artificial Intelligence‐Driven Inverse Design of Singlet Fission Candidates in the Acene family

    Advanced Science · 2026-09-27

    Rafael G. Uceda, Boris Pérez‐Cañedo, Sandra Míguez‐Lago, Carlos M. Cruz, Joaquín J Torres, Omar Nuñez, Luı́s Álvarez de Cienfuegos, Antonio J. Mota, D. Miguel, Juan M. Cuerva

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  34. Machine Learning-Driven Lightweight Design of Materials for Police Protective Equipment: A Methodological Framework and Validation Study

    Research Square · 2026-10-01

    Xiang Xin, Rui Li, Fucheng Liu, Fengyun Lu

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