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RESEARCH PAPER · Journal of Physics Condensed Matter · 2024

Discovery of novel materials through machine learning

Akinwumi Akinpelu, Mangladeep Bhullar, Yansun Yao

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42 direct citing works

Discovery of novel materials through machine learningOriginalPerovskite Ceramics: Promising Materials for Solar Cells (Photovoltaics)2Design of Flexible Fins and Drive Mechanism of Bionic Butterfly Flapping Wing Flyer2Experimental and Numerical Characterization of Electrospun Piezoelectric Polyvinylidene Fluoride Nanocomposites Reinforced with Silver Nanoparticles9Predicting the Viscosity of CaF2-Based Slag and Reverse Design of Electroslag Systems Using Explainable Machine Learning13Bio-inspired hybrid materials for sustainable energy: Advancing bioresource technology and efficiency35A guided review of machine learning in the design and application for pore nanoarchitectonics of carbon materials85Experimentally validated inverse design of FeNiCrCoCu MPEAs and unlocking key insights with explainable AI11Melt-based additive manufacturing of refractory metals and alloys: Experiments and modeling11Pressure-induced reactions in minerals: a condensed matter physics perspective1Materials informatics: A review of AI and machine learning tools, platforms, data repositories, and applications to architectured porous materials41A survey of AI-supported materials informatics7AI-based accurate and efficient flash point prediction for structurally diverse hydrocarbons via Bayesian-optimized deep neural networks0A Computational Renaissance in High-Energy Density Materials (HEDMs) Research38Research on the Variation Law of Resistivity of Composite Insulating Materials under Multiple Physical Fields0Advances and prospects of lead-free metal halide perovskites for solar hydrogen fuel generation2Predicting the mechanical properties of $\:{Li}_{2}Ti{O}_{3}$ using machine learning process: linear regression, random forests and XGBoost models0Artificial intelligence shaping the future of hydrogen technologies6Discovering Hidden Relationships of Alloy Properties with Manifold Learning0A computational approach to discovering high-performance, lead-free perovskite solar cells using physics-informed neural networks1A hybrid machine learning approach for high throughput screening of thermodynamically stable double perovskites with optimal band gap0ALiBERT: Transformer-Based NLP and Hybrid Ensemble Learning Framework for Predicting Material Properties0Data-augmented machine learning framework for rational design Na3V2(PO4)3 cathodes0A Hybrid SCAPS-1D–Machine Learning Framework for Electron Transport Layer Optimization in CH3NH3SnI3 -Based Perovskite Solar Cells0RACE: A Modular and Interpretable Radial–Angular Correlation Descriptor for Atomistic Machine Learning0

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24 direct citing papers saved.

  1. Perovskite Ceramics: Promising Materials for Solar Cells (Photovoltaics)

    IntechOpen eBooks · 2024-10-31

    Shah Aarif Ul Islam, Edson L. Meyer

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  2. Design of Flexible Fins and Drive Mechanism of Bionic Butterfly Flapping Wing Flyer

    International Conference on Computer, Artificial Intelligence and Control Engineering (CAICE) · 2025-01-10

    Xiangdong Yang, Fangyu Zhang, Xingzu Ming

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  3. Experimental and Numerical Characterization of Electrospun Piezoelectric Polyvinylidene Fluoride Nanocomposites Reinforced with Silver Nanoparticles

    Materials · 2025-03-26

    Strahinja Milenković, Fatima Živić, Nenad Grujović, Katarina D. Virijević, Aleksandar S. Bodić, Denis Petrović

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  4. Predicting the Viscosity of CaF2-Based Slag and Reverse Design of Electroslag Systems Using Explainable Machine Learning

    Metallurgical and Materials Transactions B · 2025-04-14

    Xi Chen, Yanwu Dong, Zhouhua Jiang, Yuxiao Liu, Jia Wang, Xin Sun, Junze Cao, Weiji Zhou, Yudong Yao

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  5. Bio-inspired hybrid materials for sustainable energy: Advancing bioresource technology and efficiency

    Materials Today Communications · 2025-04-24

    Damian Christopher Selvam, Yuvarajan Devarajan

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  6. A guided review of machine learning in the design and application for pore nanoarchitectonics of carbon materials

    Materials Science and Engineering R Reports · 2025-05-02

    Chuang Wang, Xingxing Cheng, Kai Luo, K. Nandakumar, Zhiqiang Wang, Meng Ni, Xiaotao Tony Bi, Jiansheng Zhang, Chunbo Wang

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  7. Experimentally validated inverse design of FeNiCrCoCu MPEAs and unlocking key insights with explainable AI

    npj Computational Materials · 2025-05-15

    Fangxi Wang, Allana G. Iwanicki, Abhishek T. Sose, Lucas A. Pressley, Tyrel M. McQueen, Sanket A. Deshmukh

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  8. Melt-based additive manufacturing of refractory metals and alloys: Experiments and modeling

    Journal of Materials Research and Technology · 2025-06-07

    mohammad younes araghi, Ali Dashti, Mahshad Fani, Iman Ghamarian, César Ruiz, Shuozhi Xu

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  9. Pressure-induced reactions in minerals: a condensed matter physics perspective

    Journal of Physics Condensed Matter · 2025-06-25

    John S. Tse, Huiyao Kuang, Yansun Yao

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  10. Materials informatics: A review of AI and machine learning tools, platforms, data repositories, and applications to architectured porous materials

    Materials Today Communications · 2025-08-07

    Fatima Živić, Ana M. Kaplarevic-Malisic, Nenad Grujović, Boban S. Stojanovic, Milos R. Ivanovic

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  11. A survey of AI-supported materials informatics

    Computer Science Review · 2025-10-17

    Sanjay Chakraborty, Jonas Björk, Martin Dahlqvist, Johanna Rosen, Fredrik Heintz

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  12. AI-based accurate and efficient flash point prediction for structurally diverse hydrocarbons via Bayesian-optimized deep neural networks

    Journal of Thermal Analysis and Calorimetry · 2025-10-21

    Fanzhi Meng, Wei Xu, Yanan Qian, Feng Sun, Bing Sun, Zhe Yang

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  13. A Computational Renaissance in High-Energy Density Materials (HEDMs) Research

    Chemical Reviews · 2025-11-03

    Haixiang Gao, Jane S. Murray, Jean’ne M. Shreeve

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  14. Research on the Variation Law of Resistivity of Composite Insulating Materials under Multiple Physical Fields

    Journal of Electronic Materials · 2025-12-03

    Shuai Zhou, Shanghe Liu, Xiaofeng Hu, Hongfei Li, Ming Wei, Jianping Zhang, Lei Wang, Yingying Wang

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  15. Advances and prospects of lead-free metal halide perovskites for solar hydrogen fuel generation

    Transition Metal Chemistry · 2026-02-10

    Alberto A. Boretti

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  16. Predicting the mechanical properties of $$\:{Li}_{2}Ti{O}_{3}$$ using machine learning process: linear regression, random forests and XGBoost models

    Euro-Mediterranean Journal for Environmental Integration · 2026-02-17

    Housna Dari, Achraf Chahbi, Fatima Zahra Krimech, Ahmed Hader, Iliass Tarras, Rachida Moultif, Mohammed Tanasehte, Y. Boughaleb

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  17. Artificial intelligence shaping the future of hydrogen technologies

    Cell Reports Physical Science · 2026-04-01

    Gaurav Sharma, Nahid Tyagi, Virendra K. Vijay, Pradeep Kumar Singh, Sreedevi Upadhyayula, Rohit Srivastava, Ranjith Krishna Pai

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  18. Discovering Hidden Relationships of Alloy Properties with Manifold Learning

    Integrating materials and manufacturing innovation · 2026-05-07

    Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang

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  19. A computational approach to discovering high-performance, lead-free perovskite solar cells using physics-informed neural networks

    Materials Today Communications · 2026-06-01

    Mohamed Moustafa, Abdelrahman M. Al-Atrash, Mahmoud S. Ghanem, Saad H. Elzoheery

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  20. A hybrid machine learning approach for high throughput screening of thermodynamically stable double perovskites with optimal band gap

    Materials Science and Engineering R Reports · 2026-06-23

    Zia Ur Rehman, Zijing Lin

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  21. ALiBERT: Transformer-Based NLP and Hybrid Ensemble Learning Framework for Predicting Material Properties

    Arabian Journal for Science and Engineering · 2026-07-21

    M. Subramanian, N. Arunkumar, M. Diviya, T. Balasubramanian

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  22. Data-augmented machine learning framework for rational design Na3V2(PO4)3 cathodes

    Journal of Energy Storage · 2026-09-15

    Yuting Chen, Zheng Hu, Yuxin Ran, Wenxuan Xu, Xusheng Wang, Shan Yin, Wenjie Mai, Jinliang Li

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  23. A Hybrid SCAPS-1D–Machine Learning Framework for Electron Transport Layer Optimization in CH3NH3SnI3 -Based Perovskite Solar Cells

    Physica B Condensed Matter · 2026-10-01

    Ammar Sehili, Nora Oulmi

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  24. RACE: A Modular and Interpretable Radial–Angular Correlation Descriptor for Atomistic Machine Learning

    Journal of Chemical Theory and Computation · 2026-10-08

    Raphael M. Tromer, Jhionathan de Lima, Cristiano Francisco Woellner, Paola Ferreira Barbosa, Roberto Ventura Santos, Luiz Antônio Ribeiro

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