Papers citing Advances of machine learning in materials science: Ideas and techniques
Predicting unmeasured asymmetry time spectra in μ SR experiments using Random Forest
Journal of Magnetism and Magnetic Materials · 2025
K.F. Chin, M.R. Omar, Tiem Leong Yoon, Yutaka Komiyama, Dita Puspita Sari, Wan Nurfadhilah Zaharim, Tomi Ohtsuki, Tadashi Adachi, T. Goto, Isao Watanabe
Read original paper ↗ ·Accelerating the Discovery of Low-Dielectric Polyimides Based on Interpretable Machine Learning
ACS Applied Polymer Materials · 2025
Rongrong Zheng, Wenjia Huo, Boyang Liang, Xiang Xia Wu
Read original paper ↗ ·Benchmarking optimization methods for materials research: Gradient descent and Bayesian optimization for lithium-ion battery aging diagnostics
Journal of Power Sources · 2025
Ziqing Zhao, Joseph Kubal, Daniel P. Abraham, Emily Margaret Ryan
Read original paper ↗ ·Machine learning-driven discovery of multicomponent pharmaceutical solid forms via DualNet: confidence-aware prediction and ranking of salts and cocrystals
International Journal of Pharmaceutics · 2025
Mohammad Amin Ghanavati, Bahareh Khalili, Dino Alberico, Sohrab Rohani
Read original paper ↗ ·Evaluating the use of a machine learning simulator for structure–property prediction: A case study on disordered elastic networks
The Journal of Chemical Physics · 2025
Salman N. Salman, Sergey A. Shteingolts, Ron Levie, Dan Mendels
Read original paper ↗ ·Adding machine learning to the polymer reaction engineering toolbox
Progress in Polymer Science · 2025
Kiarash Farajzadehahary, Shaghayegh Hamzehlou, Nicholas Ballard
Read original paper ↗ ·Partitioning adsorption energy: An electronegativity-based descriptor for hydrogen adsorption on group IV and III–V 2D honeycombs
The Journal of Chemical Physics · 2025
Yi Sheng Ng, Jin‐Cheng Zheng
Read original paper ↗ ·Interpretable Machine Learning for the Design of (K, Na)NbO 3 -Based Piezoceramics Using Combinatorial and Knowledge-Embedded Descriptors
ACS Applied Materials & Interfaces · 2025
Heng Hu, Bin Wang, Didi Zhang, Kang Yan, Tao Tan, Dawei Wu
Read original paper ↗ ·A survey of AI-supported materials informatics
Computer Science Review · 2025
Sanjay Chakraborty, Jonas Björk, Martin Dahlqvist, Johanna Rosen, Fredrik Heintz
Read original paper ↗ ·Robust Multiclass Pneumonia Classification via Multi-Head Attention and Transfer Learning Ensemble
Applied Sciences · 2025
Shenghua Rao, Zhuo Zeng, Jiemeng Zhang
Read original paper ↗ ·Positron annihilation and AI-technology for creation of novel biosensors
Journal of Physics Conference Series · 2025
Taras S. Kavetskyy, Andrii Tuzhykov, Dietmar W. Fink, Yuliia Kukhazh, Наталія Костянтинівна Гойванович, Ondrej Šauša, B. Zgardzińska, Helena Švajdlenková, Julia Warowna, Vladimir Soloviev, Arnold E. Kiv
Read original paper ↗ ·Hybrid Architecture Based on Siamese U-Net for Few-Shot Image Segmentation of Nanomaterials
Venue not supplied by source · 2025
Mikhail Savelev, Alexei Zakharov
Read original paper ↗ ·EcoCurrentNet an integrated DNN-CatBoost model for predicting optoelectronic material performance under varying conditions
Scientific Reports · 2025
Sun Xiaoying
Read original paper ↗ ·Enhanced prediction and optimization of thin metal film optical properties using optimized ensemble learning models
Scientific Reports · 2025
Kevin Kunjukutty Thomas, Ahasanur Rahman, Amith Khandakar, P Chelvanathan, Brahim Aïssa, Mohammad Istiaque Hossain
Read original paper ↗ ·Machine Learning Unlocks New Directions in Halide Perovskite Research
ChemElectroChem · 2025
Hyejin Choe, Heesung Yoon, Inhyang Kim, Soo Young Kim
Read original paper ↗ ·Gaining scientific understanding with small data machine learning: explainable molecule representations and their consensus
npj Materials Degradation · 2025
Can Özkan, Lisa Sahlmann, Tim Würger, Christian Feiler, Sviatlana V. Lamaka, Mikhail L. Zheludkevich, Peyman Taheri, J.M.C. Mol
Read original paper ↗ ·Accelerating Hydrogen Storage Material Discovery: Machine Learning Approach for Predicting Multi-Step Hydrogenation Energetics in Transition Metal-Doped Phosphorene
SSRN Electronic Journal · 2026
César Gabriel Vera de la Garza, Wilmer E. Vallejo Narváez, Serguei M. Fomine
Read original paper ↗ ·Accelerating Hydrogen Storage Material Discovery: Machine Learning Approach for Predicting Multi-Step Hydrogenation Energetics in Transition Metal-Doped Phosphorene
SSRN Electronic Journal · 2026
César Gabriel Vera de la Garza, Wilmer E. Vallejo Narváez, Serguei M. Fomine
Read original paper ↗ ·AI and Machine Learning: Revolutionizing Nanomaterial Research Through Synthesis, Characterization, and Applications
Springer proceedings in physics · 2026
Priyavrat, Ekta Thakur, Gargee Jain, Anup Kumar Pandey, Navneet Kumar, Jamilur R. Ansari, Kunal
Read original paper ↗ ·AI-powered OLEDs: speeding up innovation in displays
Journal of Materials Chemistry C · 2026
Monima Sarma, Tanmay Chatterjee
Read original paper ↗ ·An Exploratory Analysis of Current and Future Trends of Artificial Neural Network (ANN) Paradigms in Wind Energy Systems
Lecture notes in electrical engineering · 2026
Amandeep Gill, Shreshta Bandhu Rastogi, Beemkumar Nagappan, Savita, Tahir Khurshaid
Read original paper ↗ ·Artificial Intelligence for Science: A critical survey and outlook
Frontiers of Physics · 2026
Guangcun Shan
Read original paper ↗ ·Artificial intelligence-driven magnetic property prediction and materials discovery for next-generation spintronics
RSC Advances · 2026
R. Elilarassi, D. Sivanandakumar, N. Palaniappan, Pugazhendi Ilanchezhiyan, Vsk Venkatachalapathy, K. Velmurugan
Read original paper ↗ ·Classification of Perovskite Crystal Systems from Elemental Features Using Machine Learning
Lecture notes in networks and systems · 2026
V. Midhun, P. Navaneeth Krishna Pai, Soumya G. Nair, Pramod P Nair
Read original paper ↗ ·Machine learning approaches to quantify nanoscale variations in the mechanical properties of soft nanoparticles
Soft Matter · 2026
Benjamin Baylis, John Dutcher
Read original paper ↗ ·Machine learning molecular dynamics for aqueous systems: Structure, dynamics, and reactivity
Frontiers of Physics · 2026
Weiyu Li, Zhaoru Sun
Read original paper ↗ ·The Problem of Convergent Scientific Narratives in Single-Model Materials Regimes
Journal of Artificial Intelligence for Materials Science · 2026
Samuel Boateng, Kwesi Mensah, Kojo Asante, Linda Owusu
Read original paper ↗ ·A transferable data driven framework for electrolyte discovery
Discover Energy · 2026
Neal Kapadia, Jiaqi Ke, Laisuo Su
Read original paper ↗ ·Pairwise Neural Networks for Ranking Molecular Structures Based on Properties
ACS Omega · 2026
Renato Frazzato Viana, Juarez L. F. Da Silva, Luís Gustavo Dias, Ronaldo Cristiano Prati
Read original paper ↗ ·Machine learning techniques for estimating saturated soil hydraulic conductivity at the watershed scale: advances in pedotransfer functions
Environmental Earth Sciences · 2026
Frederico Carlos Martins de Menezes Filho, Rodrigo César Vasconcelos dos Santos, Tirzah Moreira Siqueira, Maurício Fornalski Soares, Luís Carlos Timm
Read original paper ↗ ·TopoChat: Enhancing Topological Materials Retrieval with Large Language Model and Multi-Source Knowledge
Journal of Computer Science and Technology · 2026
Huang-Chao Xu, Baohua Zhang, Zhong Jin, Tian-Nian Zhu, Quansheng Wu, Hong-Ming Weng
Read original paper ↗ ·Towards a sustainable high-quality materials data ecosystem: frameworks and strategies
National Science Review · 2026
Bing He, Kaixuan Wang, Zhou Jiang, Yueyu Zhang, Maxim Avdeev, Siqi Shi
Read original paper ↗ ·DT-MIM: A network suitable for alloy microstructure evolution prediction and characterization
Journal of Materials Research and Technology · 2026
Ze Sheng Lu, Jianli Zhou, Jiahao Li, Ao Liu, Yuefei Zhang, Ze Zhang
Read original paper ↗ ·AI-assisted characterization of piezoelectric behavior in hydroxyapatite-graphene nanocomposites for smart bioceramic applications
Diamond and Related Materials · 2026
Jilei Liu
Read original paper ↗ ·Machine Learning as a Catalyst in Advanced Materials Research and Development
IGI Global eBooks · 2026
Muhammad Akram, Waqas Uddin Choudhry
Read original paper ↗ ·Semi-Supervised Based Regression Algorithm for Limited Dataset
Proceedings of IEEE Southeastcon · 2026
Zahra Sepasi, Vahid Rafiei, Ali Aliev
Read original paper ↗ ·Roadmaps for dendrite suppression in next generation lithium-ion batteries: Toward sustainable energy solutions
Energy storage materials · 2026
Yi Li, Sachin Poudel, Kumari Sweta, Erfan Azqadan, Anil Kunwar, Nele Moelans B
Read original paper ↗ ·Transfer learning-enabled performance prediction of metallic materials: Methods, applications and prospects
International Journal of Minerals Metallurgy and Materials · 2026
Yufan Liu, Dexin Zhu, Zhihao Tian, Jiayi Liu, Xing Ran, Zhe Wang, Chengjiang Tang, Lifei Wang, Wei Ping Xu, Xin Pei Lu
Read original paper ↗ ·Machine learning prediction of multi-step hydrogenation energetics in transition metal-doped phosphorene
Computational and Theoretical Chemistry · 2026
César Gabriel Vera de la Garza, Wilmer E. Vallejo Narváez, Serguei M. Fomine
Read original paper ↗ ·Data-driven design of electrocatalysts: Machine learning workflows, paradigm shifts, and applications
Advanced Powder Materials · 2026
Ziwei Liu, Hanqing Gu, Liwei Yang, Wengcheng Wu, Zhong Huang, Haozhi Wang, Yang Wang, Yida Deng
Read original paper ↗ ·Machine Learning-Based Prediction of Polymer Properties Using Structure–Property Relationship Modeling
Polymers · 2026
Mohammod Hafizur Rahman, Md Arifuzzaman, Md. Tamjidul Haque, Ramasamy Srinivasaga Naidu, Md Enamul Hoque, Muhammad Ali Martuza
Read original paper ↗ ·MATHEMATICAL MODELING OF THE CHANGE PROCESS IN PHYSICO-MECHANICAL PROPERTIES OF POLYURETHANE FOAMS BASED ON LIMITED EXPERIMENTAL SAMPLES
Bulletin of the National Technical University «KhPI» Series Dynamics and Strength of Machines · 2026
Т.В. Фурс, Олена Аркадіївна Мікуліч, Oleksii Prykhodko
Read original paper ↗ ·Harnessing AI for Heat Transfer: The Potential of Physics-Informed Neural Networks (PINNs)
Journal of Physics Conference Series · 2026
Luca Bergamasco, Matteo Morciano, Eliodoro Chiavazzo
Read original paper ↗ ·Exploring multiscale modelling combined with machine learning: from electronic structure to pore-scale dynamics in complex materials
The European Physical Journal Special Topics · 2026
Alexsandro Kirch, Alvaro David Torrez Baptista, Wagner W. R. Araujo, Alberto Torres, Dan Ni Lin, Gustavo Moriel Oliveira, Caetano Rodrigues Miranda
Read original paper ↗ ·A Review of Recent Trends in Machine Learning Applications for Manufacturing Fiber-Reinforced Polymer Composites
Applied Composite Materials · 2026
Qian Wang, Huanyu Liu, Caixia Jia, Zhixin Li
Read original paper ↗ ·Hybrid constitutive law with machine learning for sintering of advanced ceramics
Scientific Reports · 2026
Baber Saleem, Peter Polák, Ran He, Savvaki Savva, Jonathan Phillips, Jingzhe Pan
Read original paper ↗ ·GNNeF: Enhanced GNN PDE Solver with Embedded FNO
Lecture notes in computer science · 2026
Jiyan Qiu, Jian Zhang, Yuan Wu, Xuebin Chi
Read original paper ↗ ·From Data Islands to Knowledge Networks in Tribology: Understanding the Modern Data Architecture
Tribology Letters · 2026
Nikolay Garabedian, Wilfred T. Tysoe
Read original paper ↗ ·Small-sample machine learning for plasma electrolytic oxidation process–microstructure mapping: Minimizing pore size via a multilayer perceptron and Bayesian optimization
Results in Materials · 2026
Erfan Mohammadipour, Mohammad Ghorbani
Read original paper ↗ ·Machine learning-assisted formulation design of flame-retardant polyoxymethylene composites
Review of Materials Research · 2026
周水军, Linzhe He, Jiantong Li, Xiaomin Fang, Tao Ding, Zhehong Lu
Read original paper ↗ ·