Papers citing Explainable machine learning in materials science
A Review on the Application of Superalloys Composition, Microstructure, Processing, and Performance via Machine Learning
JOM · 2024
Junhui Zhang, Haiyan Gao, Yahui Liu, Jun Wang
Read original paper ↗ ·Impact of Surface Enhanced Raman Spectroscopy in Catalysis
ACS Nano · 2024
Andrei Ştefancu, Javier Aizpurua, Ivano Alessandri, Ilko Bald, Jeremy J. Baumberg, Lucas V. Besteiro, Phillip Christopher, Miguel A. Correa‐Duarte, Bart de Nijs, Angela Demetriadou, Renee R. Frontiera, Tomohiro Fukushima, Naomi J. Halas, Prashant K. Jain, Zee Hwan Kim, Dmitry Kurouski, Holger Lange, Jian‐Feng Li, Luis M. Liz‐Marzán, Ivan T. Lucas, Alfred Johann Meixner, Kei Murakoshi, Peter J. Nordlander, William J. Peveler, Raúl Quesada-Cabrera, Emilie Ringe, George Chappell Schatz, Sebastian Schlücker, Zachary D. Schultz, Emily Xi Tan, Zhong‐Qun Tian, Lingzhi Wang, Bert Marc Weckhuysen, Wei Li Xie, Xing Yi Ling, Jinlong Zhang, Zhigang Zhao, Ru-Yu Zhou, Emiliano Cortés
Read original paper ↗ ·Introducing Materials Fingerprint (MatPrint): A novel method in graphical material representation and features compression
Computational Materials Science · 2024
Russlan Jaafreh, Surjeet Kumar, Kotiba Hamad, Jung‐Gu Kim
Read original paper ↗ ·XElemNet: towards explainable AI for deep neural networks in materials science
Scientific Reports · 2024
Kewei Wang, Vishu Gupta, C. S. George Lee, Yuwei Mao, Muhammed Nur Talha Kilic, Youjia Li, Zanhua Huang, Wei‐keng Liao, Alok Choudhary, Ankit Agrawal
Read original paper ↗ ·Enhancing photovoltaic cell design with multilayer sequential neural networks: A study on neodymium-doped ZnO nanoparticles
Chemical Engineering Journal Advances · 2024
Rogelio A. Léon-García, Ernesto Rojas-Pablos, Jorge Luis Mejía-Méndez, Araceli Sanchez-Martinez, Diego E. Navarro-López, Angélica Lizeth Sánchez-López, Luis Marcelo Lozano, Oscar Ceballos-Sanchez, Edgar R. López-Mena, Gildardo Sanchez‐Ante
Read original paper ↗ ·Intelligent Nanomaterial Image Characterizations – A Comprehensive Review on AI Techniques that Power the Present and Drive the Future of Nanoscience
Advanced Theory and Simulations · 2024
Umapathi Krishnamoorthy, Sukanya Balasubramani
Read original paper ↗ ·A Multi-Operation Mode KPI Control Method Based on Regression Rule Extraction from Deep Neural Networks
China Automation Congress (CAC) · 2024
Ran Hong, Bei Sun, Zhixuan Peng, Kong Peng, Yonggang Li, Maopeng Li
Read original paper ↗ ·Interpretable Surrogate Learning for Electronic Material Generation
ACS Nano · 2024
Zhilong Wang, Sixian Liu, Kehao Tao, An Chen, Hongxiao Duan, Yanqiang Han, Fengqi You, Gang Liu, Jinjin Li
Read original paper ↗ ·Explainable artificial intelligence for machine learning prediction of bandgap energies
Journal of Applied Physics · 2024
Taichi Masuda, Katsuaki Tanabe
Read original paper ↗ ·Classifying modified gravity and dark energy theories with Bayesian neural networks: massive neutrinos, baryonic feedback, and the theoretical error
Monthly Notices of the Royal Astronomical Society · 2024
Linus Thummel, Benjamin Bose, Alkistis Pourtsidou, Lucas Lombriser
Read original paper ↗ ·Diverse explanations from data-driven and domain-driven perspectives in the physical sciences
Machine Learning Science and Technology · 2024
Sichao Li, Xin Wang, Amanda Susan Barnard
Read original paper ↗ ·Understanding Polymers Through Transfer Learning and Explainable AI
Applied Sciences · 2024
Luis Alejandro Miccio
Read original paper ↗ ·Deep Learning Architectures Enabling Sophisticated Feature Extraction and Representation for Complex Data Analysis
International Journal of Innovative Science and Research Technology (IJISRT) · 2024
Nurudeen Yemi Hussain
Read original paper ↗ ·Impact of data bias on machine learning for crystal compound synthesizability predictions
Machine Learning Science and Technology · 2024
Ali Davariashtiyani, Busheng Wang, Samad Hajinazar, Eva Zurek, Sara Kadkhodaei
Read original paper ↗ ·Machine learning for gas–solid interaction materials and devices
Coordination Chemistry Reviews · 2024
Peiyuan Liu, Xiaoyang Zhu, Xu Ran, Hengchang Bi, Xiao Bing Huang, Ning Gu
Read original paper ↗ ·Machine Learning for Optical Anisotropy Identification of Few-Layer Black Phosphorus Based on Polarized Microscopic Images
ACS Applied Nano Materials · 2024
Zhihong Jewel Hu, Wei Chen, Hui Qiao, Zongyu Huang, Xiang Qi
Read original paper ↗ ·Toughness from Imagery: Extracting More from Failure Analysis using Deep Convolutional Neural Networks
Journal of Failure Analysis and Prevention · 2024
Nathan Bianco, Kaitlynn Fitzgerald, Dale Cillessen, Nathan Brown, Jay D. Carroll, Anthony P. Garland, Kimberly L. Bassett, Jacob B. Schroder, Brad L. Boyce
Read original paper ↗ ·Matini-Net: Versatile Material Informatics Research Framework for Feature Engineering and Deep Neural Network Design
Journal of Chemical Information and Modeling · 2024
Myeonghun Lee, Taehyun Park, Kyoungmin Min
Read original paper ↗ ·Deep Learning for Generating Phase-Conditioned Infrared Spectra
Analytical Chemistry · 2024
Gyoung S. Na
Read original paper ↗ ·Machine learning based insights for metal-organic frameworks synthesis: A comparative and explainable analysis of ZIF-8 morphology
Materials Today Communications · 2024
Yuncheng Du, Cristina Sanchez, Dongping Du
Read original paper ↗ ·Interpretable machine learning for stability and electronic structure prediction of Janus III–VI van der Waals heterostructures
Materials Genome Engineering Advances · 2024
Yudong Shi, Yinggan Zhang, Jiansen Wen, Zhou Cui, Jianhui Chen, Xiaochun Huang, Cuilian Wen, Baisheng Sa, Zhimei Sun
Read original paper ↗ ·Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategy
npj Computational Materials · 2024
Ying Zhang, Ke Ren, William Yi Wang, Xingyu Gao, Jun Wang, Yiguang Wang, Haifeng Song, Xiubing Liang, Jinshan Li
Read original paper ↗ ·Externalist XAI ?
Theoria · 2024
Anders Søgaard
Read original paper ↗ ·Machine Learning in Solid‐State Hydrogen Storage Materials: Challenges and Perspectives
Advanced Materials · 2024
Panpan Zhou, Qianwen Zhou, Xuezhang Xiao, Xiulin Fan, Yongjin Zou, Lixian Sun, Jinghua Jiang, Dan Song, Lixin Chen
Read original paper ↗ ·Exploration of the Structure and Composition of Sn(S₀.₆Te₀.₄) Thin Film as a Potential Absorber in Solar Cell Technology
Journal of Chemical Learning Innovation. · 2024
Mahmudah Setianingrum, Guluzra Bozorboeva
Read original paper ↗ ·Active and transfer learning with partially Bayesian neural networks for materials and chemicals
Digital Discovery · 2025
Sarah I. Allec, Maxim A Ziatdinov
Read original paper ↗ ·Advances in van der Waals thermoelectric materials: prospects and challenges
RSC Applied Interfaces · 2025
Marco Fronzi, Paolo Mele, Amanda V. Ellis, Catherine Stampfl
Read original paper ↗ ·Algorithmic Discovery vs. Scientific Discovery: A Conceptual Boundary for AI-Driven Materials Research
Journal of Artificial Intelligence for Materials Science · 2025
Lucas Meyer, Stefan Braun, Anna Schmid
Read original paper ↗ ·Algorithmic Simplicity as Scientific Virtue: A Conceptual Tension in Materials AI Design
Journal of Artificial Intelligence for Materials Science · 2025
Siti Rahman, Ahmad Zaki, Nurul Huda, Amir Faisal, Lim Wei
Read original paper ↗ ·An explainable “family bucket” model for simultaneous prediction of K-edge XANES for multiple light transition metals
Chemical Science · 2025
Chenyu Huang, Yunjiang Zhang, Shuyuan Li, Huimin Wang, Yaxin Wang, Shihao Wei, Shaorui Sun
Read original paper ↗ ·An improved machine learning strategy using structural features to predict the glass transition temperature of oxide glasses
Digital Discovery · 2025
Satwinder Singh, Kulvir Singh
Read original paper ↗ ·Computer vision for polymer characterisation using lasers
Digital Discovery · 2025
Seda Uyanik, Sam J. Parkinson, George Killick, Biplab Dutta, Rob Clowes, Charlotte E. Boott, Andrew Ian Cooper
Read original paper ↗ ·DetectNano: deep learning detection in TEM images for high-throughput nanostructure characterization
Nanoscale · 2025
Khalid Ferji
Read original paper ↗ ·Enhancing Copper Interconnect Reliability Based on Machine Learning: Electromigration Lifetime Prediction Via an -Interpretable Qpso-Xgboost Hybrid Model
SSRN Electronic Journal · 2025
Kai Wei Sun, MingYang Zuo, TianBo Wu, Li Tian, Ming Wang, J. Sun
Read original paper ↗ ·Enhancing energy predictions in multi-atom systems with multiscale topological learning
Journal of Materials Chemistry A · 2025
Dong Chen, Rui Wang, Guo-Wei Wei, Feng Pan
Read original paper ↗ ·Examining proton conductivity of metal–organic frameworks by means of machine learning
Physical Chemistry Chemical Physics · 2025
Ivan V. Dudakov, Sergei A. Savelev, Iurii M. Nevolin, Artem A. Mitrofanov, Vadim Korolev, Yulia G. Gorbunova
Read original paper ↗ ·Explainability Drift in Iterative Materials AI Workflows: A Conceptual Failure Analysis
Journal of Artificial Intelligence for Materials Science · 2025
Lucas Andrade, Mariana Lopes
Read original paper ↗ ·From synthesis to properties: expanding the horizons of machine learning in nanomaterials research
Materials Horizons · 2025
Shanhui Diao, Qiong Wu, Shimei Li, Gang Xu, Xiangling Ren, Longfei Tan, Guihua Jiang, Peng Song, Xianwei Meng
Read original paper ↗ ·Governance Architectures for Self-Driving Laboratories in Computational Materials Engineering
Journal of Computational and Data-Driven Materials Engineering · 2025
Hiroshi Nakamura, Yuta Kato
Read original paper ↗ ·Heterogeneity analysis of CO2 emissions driving features on road transport: New perspective from interpretive machine learning
Journal of Cleaner Production · 2025
Xing Wang, Yikun Su, Zhizhe Zheng, Wei Wang
Read original paper ↗ ·Human–AI Jurisdiction Boundaries in Computational and Data-Driven Materials Engineering
Journal of Computational and Data-Driven Materials Engineering · 2025
Wei Liu, Zhang Min
Read original paper ↗ ·Hybrid mechanics-informed machine learning models for predicting mechanical failure in graphene sponge: a low-data strategy for mechanical engineering applications
Open Engineering · 2025
Kawther K Younus, Marwah Ghazi Kareem, Hadi Hasan Mussttaf
Read original paper ↗ ·Institutional Oversight Models for AI-Directed Materials Innovation
Journal of Computational and Data-Driven Materials Engineering · 2025
Carlos Vega, Maria Hernandez
Read original paper ↗ ·Interpretable and uncertainty-informed machine learning to accelerate the design and discovery of lead-free piezoceramics with large piezoelectric constant
Journal of Materials Chemistry C · 2025
Heng Hu, Bin Wang, Didi Zhang, Kang Yan, Tao Tan, Dawei Wu
Read original paper ↗ ·Leveraging machine learning and deep learning in research: tools, algorithms, and applications
Elsevier eBooks · 2025
Jayadev Joshi
Read original paper ↗ ·Machine Learning Algorithms for Applications in Materials Science II
Challenges and advances in computational chemistry and physics · 2025
Ayushi Ayushi, Neeraj Kumar Tiwari, Terry-Elinor R. Reid, Nikita Basant
Read original paper ↗ ·Machine learning for predicting and improving perovskite properties
Semiconductors and semimetals · 2025
Xuesi Liu, Hualin Zhan
Read original paper ↗ ·MACHINE LEARNING IN NANOSCALE THERMAL TRANSPORT
Annual Reviews of Heat Transfer · 2025
Yuhan Liu, Sobin Alosious, Jiahang Zhou, Meng Jiang, Tengfei Luo
Read original paper ↗ ·Machine Learning-Based Design of Anti-Electrostatic Integrated Semiconductor Bridge initiators
SSRN Electronic Journal · 2025
Wang Lei, Feng Yuzhu, Bin Zhou
Read original paper ↗ ·Microstructure-informed performance boost in solid oxide fuel cells through multiphysical modeling and machine learning
Journal of Materials Chemistry A · 2025
Li Duan, Zilin Yan, Zehua Pan, Zheng Zhong
Read original paper ↗ ·