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Potential Application of Machine-Learning-Based Quantum Chemical Methods in Environmental Chemistry2022 Environmental Science & Technology article Materials Science Machine Learning in Materials Science Open access
Deming Xia, Jingwen Chen, Zhiqiang Fu, Tong Xu, Zhongyu Wang, Wenjia Liu, +2 more
61citations -
Stability of Binary Precipitates in Cu-Ni-Si-Cr Alloys Investigated Through Active Learning2023 SSRN Electronic Journal preprint Materials Science Machine Learning in Materials Science Open access
Ángel Díaz Carral, Xiang Xu, Simon Gravelle, Azade YazdanYar, Siegfried Schmauder, Maria Fyta
0citations -
Stability of Binary Precipitates in Cu-Ni-Si-Cr Alloys Investigated Through Active Learning2023 SSRN Electronic Journal preprint Materials Science Machine Learning in Materials Science Open access
Ángel Díaz Carral, Xiang Qun Xu, Simon Gravelle, Azade YazdanYar, Siegfried Schmauder, Maria Fyta
0citations -
A first-principles and machine learning combined method to investigate the interfacial friction between corrugated graphene2021 Modelling and Simulation in Materials Science and Engineering article Materials Science Machine Learning in Materials Science
Zugang Liu, Xinpeng Zhao, Heyuan Wang, Yuan Ma, Lei Gao, Haiyou Huang, +3 more
9citations -
Application of Machine Learning in Nanotoxicology: A Critical Review and Perspective2024 Environmental Science & Technology article Materials Science Machine Learning in Materials Science Open access
Yunchi Zhou, Ying Wang, Willie J.G.M. Peijnenburg, Martina G. Vijver, Surendra Balraadjsing, Zhaomin Dong, +9 more
32citations -
Computing formation enthalpies through an explainable machine learning method: the case of lanthanide orthophosphates solid solutions2024 Frontiers in Applied Mathematics and Statistics article Materials Science Machine Learning in Materials Science Open access
Edoardo Di Napoli, Xinzhe Wu, Thomas Bornhake, Piotr M. Kowalski
1citations -
Accurate prediction of structural and mechanical properties on amorphous materials enabled through machine-learning potentials: a case study of silicon nitride2024 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access
Ganesh Kumar Nayak, Prashanth Srinivasan, Juraj Todt, Rostislav Daniel, Paolo Nicolini, David Holec
1citations -
Predicting Grain Boundary Segregation in Magnesium Alloys: An Atomistically Informed Machine Learning Approach2024 RWTH Publications (RWTH Aachen) article Materials Science Magnesium Alloys: Properties and Applications Open access
Zhuocheng Xie, Achraf Atila, Julien Guénolé, Sandra Korte‐Kerzel, Talal Al‐Samman, U. Kerzel
2citations -
Discovery of liquid crystalline polymers with high thermal conductivity using machine learning2025 npj Computational Materials article Materials Science Machine Learning in Materials Science Open access
Hayato Maeda, Stephen Wu, Rika Marui, Erina Yoshida, Kan Hatakeyama‐Sato, Yuta Nabae, +13 more
16citations