Papers citing Explainable machine learning in materials science
AI methods in materials design, discovery and manufacturing: A review
Computational Materials Science · 2024
Ioannis Papadimitriou, Ilias Gialampoukidis, Stefanos Vrochidis, Ioannis Yiannis Kompatsiaris
Read original paper ↗ ·Lanthanide-Doped ZnO Nanoparticles: Unraveling Their Role in Cytotoxicity, Antioxidant Capacity, and Nanotoxicology
Antioxidants · 2024
Jorge Luis Mejía-Méndez, Diego E. Navarro-López, Araceli Sanchez-Martinez, Oscar Ceballos-Sanchez, Luis Eduardo García-Amezquita, Naveen Tiwari, Karla Juárez‐Moreno, Gildardo Sanchez‐Ante, Edgar R. López-Mena
Read original paper ↗ ·Cationic perturbation strategy to solve the information drought in material explainable machine learning
Physical review. B./Physical review. B · 2024
Zhengxin Chen, Hange Wang, Bowen Liu, Hairui Zhou, Yingjie Cao, Yanan Wang, Peng Lin, Xiaolin Liu, Jia Horng Lin, Xianfeng Chen, Jiang Wu
Read original paper ↗ ·Learning from machine learning: the case of band-gap directness in semiconductors
Discover Materials · 2024
Elton Ogoshi, Mário Popolin Neto, Carlos Mera Acosta, Gabriel M. Nascimento, J. N. B. Rodrigues, Osvaldo N. Oliveira, Fernando V. Paulovich, Gustavo M. Dalpian
Read original paper ↗ ·Understanding the Performance of (Ni−Fe−Co−Ce)Ox‐Based Water Oxidation Catalysts via Explainable Artificial Intelligence Framework
ChemElectroChem · 2024
Paul Rossener Regonia, Christian Mark Pelicano
Read original paper ↗ ·Synthesis, properties, applications, 3D printing and machine learning of graphene quantum dots in polymer nanocomposites
Progress in Materials Science · 2024
Vimukthi Dananjaya, Sathish Marimuthu, Richard (Chunhui) Yang, Andrews Nirmala Grace, Chamil Abeykoon
Read original paper ↗ ·Machine learning assisted material development for lithography-based additive manufacturing of porous alumina ceramics
Open Ceramics · 2024
Serkan Nohut, Martin Schwentenwein
Read original paper ↗ ·Machine learning assisted prediction of the phonon cutoff frequency of ABO3 perovskite materials
Computational Materials Science · 2024
Gong Chen, Jian Liu, Siqi Dai, Hua Hao, Hanxing Liu
Read original paper ↗ ·Research on strength prediction of crack rock mass based on random forest algorithm
Bulletin of Engineering Geology and the Environment · 2024
Chao Yuan, Huimei Zhang, Lei Wang, Gengshe Yang, Xiaoyu Liu, Xiangzhen Meng, Shiguan Chen
Read original paper ↗ ·Towards interpretable machine learning for observational quantification of soil heavy metal concentrations under environmental constraints
The Science of The Total Environment · 2024
Yishan Sun, Shuisen Chen, Hao Jiang, Boxiong Qin, Dan Li, Kai Jia, Chongyang Wang
Read original paper ↗ ·Adaptable multi-objective optimization framework: application to metal additive manufacturing
The International Journal of Advanced Manufacturing Technology · 2024
Mohamed Imad Eddine Heddar, Brahim Mehdi, Nedjoua Matougui, Souheil Antoine Tahan, Mohammad Jahazi
Read original paper ↗ ·Enhancing predictive modeling of photovoltaic materials’ solar power conversion efficiency using explainable AI
Energy Reports · 2024
M. Vubangsi, Auwalu Saleh Mubarak, Fadi M. Al-Turjman
Read original paper ↗ ·Harnessing the Power of Artificial Intelligence in Materials Science: An Overview
Venue not supplied by source · 2024
Adedotun Adetunla, Esther T. Akinlabi, Tien‐Chien Jen, Samuel-Soma M. Ajibade
Read original paper ↗ ·Machine Learning to Promote Efficient Screening of Low‐Contact Electrode for 2D Semiconductor Transistor Under Limited Data
Advanced Materials · 2024
Penghui Li, Linpeng Dong, Chong Li, Yan Li, Jie Zhao, Bo Peng, Wei Wang, Shun Zhou, Weiguo Liu
Read original paper ↗ ·Machine learning for the prediction and optimization of production of cellulose nanocrystals by sulfuric acid hydrolysis
Industrial Crops and Products · 2024
Hongzhen Wang, Xiaosen Pan, Huize Ge, Qin Du, Shijie Cheng
Read original paper ↗ ·Deep learning based on small sample dataset: prediction of dielectric properties of SrTiO 3 -type perovskite with doping modification
Royal Society Open Science · 2024
Quan Luo, Hua Hao, Hanxing Liu
Read original paper ↗ ·Optimizing MOF properties for seasonal heat storage: a machine learning approach
Journal of Physics Conference Series · 2024
Giovanni Trezza, Luca Bergamasco, M Fasano, Eliodoro Chiavazzo
Read original paper ↗ ·Interpreting and generalizing deep learning in physics-based problems with functional linear models
Engineering With Computers · 2024
Amirhossein Arzani, Lingxiao Yuan, Pania Newell, Wang Bei
Read original paper ↗ ·Incorporating background knowledge in symbolic regression using a computer algebra system
Machine Learning Science and Technology · 2024
Charles Fox, Neil D. Tran, F Nikki Nacion, Samiha Sharlin, Tyler R. Josephson
Read original paper ↗ ·Machine-learning-enabled exploitation of gas-sensing descriptors: A case study of five pristine metal oxides
Chemical Engineering Journal · 2024
Yong-Chang Guo, Mingzhi Yang, Gary Huang, Yangong Zheng
Read original paper ↗ ·A framework for strategic discovery of credible neural network surrogate models under uncertainty
Computer Methods in Applied Mechanics and Engineering · 2024
Pratyush Singh, Kathryn A. Maupin, Danial Faghihi
Read original paper ↗ ·Smartphone based wearable sweat glucose sensing device correlated with machine learning for real-time diabetes screening
Analytica Chimica Acta · 2024
Nadtinan Promphet, Chusak Thanawattano, Chatchai Buekban, Thidarut Laochai, Panlop Lormaneenopparat, Wiwittawin Sukmas, Pranee Rattanawaleedirojn, Pumidech Puthongkham, Pranut Potiyaraj, Worapong Leewattanakit, Nadnudda Rodthongkum
Read original paper ↗ ·Machine Learning-Guided Performance Evaluation of an All-Liquid Electrochromic Device
ACS Applied Materials & Interfaces · 2024
Huayi Lai, Qingyue Cai, Muyun Li, Sifan Kong, Yitong Wu, Huan Yang, Yong Zhang, Honglong Ning
Read original paper ↗ ·Machine Learning Methods to Improve Crystallization through the Prediction of Solute–Solvent Interactions
Crystals · 2024
Aatish Kandaswamy, Sebastian Patrick Schwaminger
Read original paper ↗ ·Exploring the Core-shell Structure of BaTiO3-based Dielectric Ceramics Using Machine Learning Models and Interpretability Analysis
Journal of Wuhan University of Technology-Mater Sci Ed · 2024
Jiale Sun, Peifeng Xiong, Hua Hao, Hanxing Liu
Read original paper ↗ ·Beryllium-doped biphenylene network: A first-principles study
Materials Today Communications · 2024
Xiaxia Gong, Yingying Fu, Yongyi Xu, Yongyi Xu, Wei Liu, Jing Xu
Read original paper ↗ ·AI for dielectric capacitors
Energy storage materials · 2024
Run‐Lin Liu, Jian Wang, Zhong-Hui Shen, Yang Shen
Read original paper ↗ ·How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences
Earth s Future · 2024
Shijie Jiang, Lily‐belle Sweet, Georgios Blougouras, Alexander Brenning, Wantong Li, Markus Reichstein, Joachim Denzler, Wei Shangguan, Guo Yu, Feini Huang, Jakob Zscheischler A
Read original paper ↗ ·The glass transition of CuZr metallic glasses in the perspective of machine learning
Computational Materials Science · 2024
Saihua Liu, Chengqiao Yang, Rui Qi, Minhua Sun
Read original paper ↗ ·Translating strain to stress: a single-layer Bi-LSTM approach to predicting stress-strain curves in alloys during hot deformation
Materials Research Express · 2024
Sheng Xu, Jie Xiong, Tong‐Yi Zhang
Read original paper ↗ ·Accelerating Polymer Discovery with Uncertainty-Guided PGCNN: Explainable AI for Predicting Properties and Mechanistic Insights
Journal of Chemical Information and Modeling · 2024
Shuyu Wang, Hongxing Yue, Xiaoming Yuan
Read original paper ↗ ·State-of-the-Art Review on Determining One-Dimensional Consolidation Parameters Based on Compression and Distribution of Pore Water Pressure: Coefficient of Consolidation (cv), End of Primary (EOP) Consolidation
Archives of Computational Methods in Engineering · 2024
Bartłomiej Szczepan Olek
Read original paper ↗ ·Step Forward Cross Validation for Bioactivity Prediction: Out of Distribution Validation in Drug Discovery
bioRxiv (Cold Spring Harbor Laboratory) · 2024
Udit Surya Saha, Michele Vendruscolo, Anne E. Carpenter, Shantanu Singh, Andreas Bender, Srijit Seal
Read original paper ↗ ·Integrating digital chemistry within the broader chemistry community
Trends in Chemistry · 2024
David Dalmau, Juan V. Alegre‐Requena
Read original paper ↗ ·Descriptor Design for Perovskite Material with Compatible Molecules via Language Model and First-Principles
Journal of Chemical Theory and Computation · 2024
Yiru Huang, Lei Zhang
Read original paper ↗ ·Target Material Property‐Dependent Cluster Analysis of Inorganic Compounds
Advanced Intelligent Systems · 2024
Nobuya Sato, Akira Takahashi, Shin Kiyohara, Kei Terayama, Ryo Tamura, Fumiyasu Oba
Read original paper ↗ ·Accelerated discovery and formation mechanism of high-entropy carbide ceramics using machine learning based on low-cost descriptors
Journal of Alloys and Compounds · 2024
Wenjian Guo, Lingyu Wang, Li’an Zhu, Yicong Ye, Zhouran Zhang, Bin Yang, Shifeng Zhang, Shuxin Bai
Read original paper ↗ ·Active causal learning for decoding chemical complexities with targeted interventions
Machine Learning Science and Technology · 2024
Zachary Fox, Ayana Ghosh
Read original paper ↗ ·A review on machine learning-guided design of energy materials
Progress in Energy · 2024
Seongmin Kim, Jiaxin Xu, Wenjie Shang, Zhihao Xu, Eungkyu Lee, Tengfei Luo
Read original paper ↗ ·Machine Learning-Guided Cycle Life Prediction for Electrochromic Devices Based on Deuterium and Water Mixing Solvent
Micromachines · 2024
Yitong Wu, Sifan Kong, Qingxin Yao, Muyun Li, Huayi Lai, Duoyu Sun, Qingyue Cai, Zelin Qiu, Honglong Ning, Yong Zhang
Read original paper ↗ ·Synergistic N-heterocyclic carbene and C2N integration for efficient and selective metal-free photocatalytic CO reduction to C2H5OH
Applied Surface Science · 2024
Wei Liu, Yunhao Xie, Jiasheng Peng, Dian Zheng, Wenming Lu, Jing Xu
Read original paper ↗ ·ROBERT : Bridging the Gap Between Machine Learning and Chemistry
Wiley Interdisciplinary Reviews Computational Molecular Science · 2024
David Dalmau, Juan V. Alegre‐Requena
Read original paper ↗ ·Data-driven analysis on perovskite solar cell devices
Current Applied Physics · 2024
SeungUn Lee, Yang Jeong Park, Jongbeom Kim, Jino Im, Sungroh Yoon, Sang Il Seok
Read original paper ↗ ·Machine learning to enhance sustainable plastics: A review
Journal of Cleaner Production · 2024
Cátia Guarda, João F.M. Caseiro, Ana Pires
Read original paper ↗ ·Insights into Na ion adsorption and diffusion in biphenylene as an anode material for sodium-ion batteries: A first-principles study
Materials Today Communications · 2024
Yongyi Xu, Yingying Fu, Yingying Fu, Xiaxia Gong, Jing Xu, Wei Liu
Read original paper ↗ ·Unifying theory of electronic descriptors of metal surfaces upon perturbation
Physical review. B./Physical review. B · 2024
Yang Huang, Shih‐Han Wang, Mohith Kamanuru, Luke E. K. Achenie, John R. Kitchin, Hongliang Xin
Read original paper ↗ ·When Metal Nanoclusters Meet Smart Synthesis
ACS Nano · 2024
Zhucheng Yang, Anye Shi, Ruixuan Zhang, Zuowei Ji, Jiali Li, Jingkuan Lyu, Jing Qian, Tiankai Chen, Xiaonan Wang, Fengqi You, Jianping Xie
Read original paper ↗ ·Literature Review of Explainable Tabular Data Analysis
Electronics · 2024
Helen O’Brien Quinn, Mohamed Sedky, Janet Francis, Michael Streeton
Read original paper ↗ ·Towards neuromorphic computing on quantum many-body architectures : VO2 transition dynamics
Venue not supplied by source · 2024
Melissa Alzate Banguero
Read original paper ↗ ·A review of machine learning in additive manufacturing: design and process
The International Journal of Advanced Manufacturing Technology · 2024
Kefan Chen, Peilei Zhang, Hua Yan, Guanglong Chen, Tianzhu Sun, Qinghua Lu, Yu Chen, Haichuan Shi
Read original paper ↗ ·