Papers citing Explainable machine learning in materials science
Machine learning-assisted selection of adsorption-based carbon dioxide capture materials
Journal of environmental chemical engineering · 2023-08-10
Eslam G. Al-Sakkari, Ahmed Ragab, Terry M.Y. So, Marzieh Shokrollahi, Hanane Dagdougui, Philippe Navarri, Ali Elkamel, Mouloud Amazouz
Read original paper ↗ ·Using limited neural networks to assess relative mechanistic influence on shock heating in granular solids
Physical Review Materials · 2023-08-14
Brenden W. Hamilton, Timothy Clark Germann
Read original paper ↗ ·Improving Graph Convolutional Neural Networks for q-Consistent Summary-Explanations with Application to Credit Evaluation Systems
International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) · 2023-08-18
Xinrui Dou, Peng Chen
Read original paper ↗ ·Algorithm for density of angle distribution in random sections of polyhedron
Expert Systems with Applications · 2023-08-19
Elisaveta Konstantinova, Щур Лев Николаевич
Read original paper ↗ ·Insights into the Luminescence Quantum Yields of Cyclometalated Iridium(III) Complexes: A Density Functional Theory and Machine Learning Approach
The Journal of Physical Chemistry A · 2023-08-31
Miho Hatanaka, Hiromoto Kato, Minami Sakai, Kosuke Kariya, Shunsuke Nakatani, Takayoshi Yoshimura, Taichi Inagaki
Read original paper ↗ ·CEEM: a Chemically Explainable Deep Learning Platform for Identifying Compounds with Low Effective Mass
Small · 2023-09-13
Jing Gao, Zhilong Wang, Yanqiang Han, Mingyu Gao, Jinjin Li
Read original paper ↗ ·Neural Network Models for Estimating the Impact of Physicochemical and Operational Parameters on the Specific Capacity of Activated-Carbon-Based Supercapacitors
Energy & Fuels · 2023-09-14
B.S. Reddy, A.K. Maurya, Uma Maheshwera Reddy Paturi, Jaekyung Sung, Pasupuleti Lakshmi Narayana, Hyo‐Jun Ahn, Kwon‐Koo Cho, N.S. Reddy
Read original paper ↗ ·An Effective Framework for Predicting Performance of Solid-Solution Copper Alloys Using a Feature Engineering Technique in Machine Learning
Metals · 2023-09-25
Tiehan Fan, Jianxin Hou, Jian Hu
Read original paper ↗ ·In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science
Journal of the American Chemical Society · 2023-09-27
Joshua Schrier, Alexander J. Norquist, Tonio Buonassisi, Jakoah Brgoch
Read original paper ↗ ·Machine Learning-Aided High-Throughput First-Principles Calculations to Predict the Formation Energy of μ Phase
ACS Omega · 2023-09-27
Yue Su, Jiong Wang, You Feng Zou
Read original paper ↗ ·Revolutionizing drug formulation development: The increasing impact of machine learning
Advanced Drug Delivery Reviews · 2023-09-27
Zeqing Bao, Jack Bufton, Riley J. Hickman, Alán Aspuru‐Guzik, Pauric Bannigan, Christine J. Allen
Read original paper ↗ ·From prediction to design: Recent advances in machine learning for the study of 2D materials
Nano Energy · 2023-10-04
Hua He, Yuhua Wang, Yajuan Qi, Zichao Xu, Yue Li, Yumei Wang
Read original paper ↗ ·Extracting the Synthetic Route of Pd-Based Catalysts in Methanol Steam Reforming from the Scientific Literature
Journal of Chemical Information and Modeling · 2023-10-09
Shuyuan Li, Yunjiang Zhang, Zhaolin Fang, Kong Meng, Rui Tian, Hong He, Shaorui Sun
Read original paper ↗ ·ANN-based structure peciliaties evaluation of polymer composite reinforced with unidirectional carbon fiber
Alexandria Engineering Journal · 2023-10-11
Andrey A. Stepashkin, Suresh Chavhan, S.V. Gromov, Ashish K. Khanna, Victor V. Tcherdyntsev, Deepak Kumar Gupta, Hussam Mohammad, E.V. Medvedeva, Namita Gupta, S.S. Alexandrova
Read original paper ↗ ·Process-structure multi-objective inverse optimisation for additive manufacturing of lattice structures using a physics-enhanced data-driven method
Virtual and Physical Prototyping · 2023-10-16
Keyu Shi, Dongdong Gu, He Liu, Yu‐Sheng Chen, Kaijie Lin
Read original paper ↗ ·Review of Machine Learning for Social and Behavioral Research (Methodology in the Social Sciences)
Structural Equation Modeling A Multidisciplinary Journal · 2023-11-09
Aszani Aszani, Ruslan Anwar
Read original paper ↗ ·A perspective on data-driven screening and discovery of polymer membranes for gas separation, from the molecular structure to the industrial performance
Reviews in Chemical Engineering · 2023-11-20
Eleonora Ricci, María Grazia De Angelis
Read original paper ↗ ·Advances of machine learning in materials science: Ideas and techniques
Frontiers of Physics · 2023-11-24
Sue Sin Chong, Yi Sheng Ng, Hui‐Qiong Wang, Jin‐Cheng Zheng
Read original paper ↗ ·Explainable AI for Material Property Prediction Based on Energy Cloud: A Shapley-Driven Approach
Materials · 2023-11-24
Faiza Qayyum, Murad Ali Khan, Do‐Hyeun Kim, Hyunseok Ko, Ga-Ae Ryu
Read original paper ↗ ·Sensitivity Evaluation of Enveloped and Non-enveloped Viruses to Ethanol Using Machine Learning: A Systematic Review
Food and Environmental Virology · 2023-12-05
Aken Puti Wanguyun, Wakana Oishi, Daisuke Sano
Read original paper ↗ ·Automated Machine Learning to Develop Predictive Models of Metabolic Syndrome in Patients with Periodontal Disease
Diagnostics · 2023-12-08
Ovidiu Boitor, Florin Stoica, Romeo Gabriel Mihăilă, Laura Florentina Stoica, Laura Ștef
Read original paper ↗ ·Intelligent design and synthesis of energy catalytic materials
Fundamental Research · 2023-12-10
Linkai Han, Zhonghua Xiang
Read original paper ↗ ·pudu: A Python library for agnostic feature selection and explainability of Machine Learning spectroscopic problems
The Journal of Open Source Software · 2023-12-12
Enric Grau‐Luque, Ignacio Becerril‐Romero, Alejandro Pérez-Rodríguez, Maxim Guc, Víctor Izquierdo‐Roca
Read original paper ↗ ·An interpretable deep learning strategy for effective thermal conductivity prediction of porous materials
International Journal of Heat and Mass Transfer · 2023-12-20
Qingfu Huang, Donghui Hong, Bo Niu, Donghui Long, Yayun Zhang
Read original paper ↗ ·Towards physics-informed explainable machine learning and causal models for materials research
Computational Materials Science · 2023-12-23
Ayana Ghosh
Read original paper ↗ ·A Conceptual Blueprint for “Digital Materials Twins” without Simulation: Definitions, Boundaries, and Use-Cases
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Maria Gonzalez, Javier Ruiz
Read original paper ↗ ·A Conceptual Framework for Trustworthy AI Decisions Across the Materials Design Lifecycle
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Wei Chen, Li Zhang
Read original paper ↗ ·A prediction model for CO 2 /CO adsorption performance on binary alloys based on machine learning
RSC Advances · 2024-01-01
Xiaofeng Cao, Wenjia Luo, Huimin Liu
Read original paper ↗ ·Algorithmic Consensus vs Scientific Consensus in Materials Prediction
Journal of Computational and Data-Driven Materials Engineering · 2024-01-01
Sanjay Kulkarni, Meenal Joshi, Rohan Patil
Read original paper ↗ ·Closed-World Training in an Open Materials Universe
Journal of Computational and Data-Driven Materials Engineering · 2024-01-01
Natalia Petrova, Elena Stoyanova, Ivan Dimitrov
Read original paper ↗ ·Conceptual Models of Trust in Materials AI — Frameworks, Dimensions, and Open Questions
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Victor Santos, Rafael Costa, Bruno Teixeira
Read original paper ↗ ·Data Lineage and Scientific Traceability in Computational Materials Pipelines
Journal of Computational and Data-Driven Materials Engineering · 2024-01-01
Lucas Andrade, Mariana Lopes
Read original paper ↗ ·Explainable AI for Interpretable Structure–Property Maps in Polymer Blend Systems
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Claire Martin, Julien Robert, Sophie Bernard
Read original paper ↗ ·EXplainable Artificial Intelligence (XAI)—From Theory to Methods and Applications
IEEE Access · 2024-01-01
Evandro Scudeleti Ortigossa, Thales Gonçalves, Luís Gustavo Nonato
Read original paper ↗ ·Failure Modes in Materials AI Explanations: A Conceptual Catalog and Prevention Principles
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Hiroshi Nakamura, Yuta Kato
Read original paper ↗ ·Generalization in Materials AI: A Theoretical Distinction between New Compositions, New Structures, and New Physics
Journal of Artificial Intelligence for Materials Science · 2024-01-01
浩 中村, Yuta Kato, Aiko Morita
Read original paper ↗ ·Heteroscedastic Gaussian Process Regression for Material Structure-Property Relationship Modeling
Computer Methods in Applied Mechanics and Engineering · 2024-01-01
Ozge Ozbayram, Audrey Olivier, Lori L. Graham-Brady
Read original paper ↗ ·Interpretability as Scientific Translation: A Conceptual Model for Converting AI Outputs into Materials Mechanisms
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Daniel Brooks, Amelia Carter, Ethan Moore, Olivia Grant
Read original paper ↗ ·Interpretability in Materials AI — What “Explanation” Means and How It Should Be Evaluated Conceptually
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Maria Hernandez, Carlos Vega, Lucia Torres
Read original paper ↗ ·Interpreting Materials Data with Artificial Intelligence: From Prediction to Scientific Understanding
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Fatima Zahra Amrani, Youssef Benali, Samira El-Haddad
Read original paper ↗ ·Latent Anisotropy: Directional Bias in Materials Embedding Spaces
Journal of Computational and Data-Driven Materials Engineering · 2024-01-01
Daniel Brooks, Ethan Moore, Amelia Carter
Read original paper ↗ ·Luminescent solar concentrators: Current and future applications in smart cities
Elsevier eBooks · 2024-01-01
Gonçalo Figueiredo, Sandra F. H. Correia, Lianshe Fu, V. de Zea Bermudez, Albano N. Carneiro Neto, Paulo Sérgio de Brito André, Rute A. S. Ferreira
Read original paper ↗ ·Machine Learning in Malware Analysis: Current Trends and Future Directions
International Journal of Advanced Computer Science and Applications · 2024-01-01
Safa Altaha, Khaled Riad
Read original paper ↗ ·Mechanistic vs. Predictive Success: A Theory of What “Understanding” Means for AI in Materials Science
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Ahmed El-Kholy, Nour Abdelrahman, Karim Hassan, Mona Saad
Read original paper ↗ ·Recent Advances in Machine Learning-Accelerated Materials Discovery — From Descriptors to Autonomous Experiments
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Nguyen Thanh Huy, Le Thi Bich, Pham Quang Minh
Read original paper ↗ ·The Literature on Scientific Explanation in AI-Driven Materials Science — Concepts and Criteria: A Review Study
Journal of Artificial Intelligence for Materials Science · 2024-01-01
George Papadopoulos, Eleni Georgiou
Read original paper ↗ ·Transfer Learning Across Materials Classes: Conceptual Boundaries of Reusability
Journal of Computational and Data-Driven Materials Engineering · 2024-01-01
Lucas Meyer, Stefan Braun, Anna Schmid
Read original paper ↗ ·What Counts as Knowledge in AI-Driven Materials Science? A Philosophical and Practical Reframing
Journal of Artificial Intelligence for Materials Science · 2024-01-01
Maria Hernandez, Carlos Vega
Read original paper ↗ ·Battery safety: Machine learning-based prognostics
Progress in Energy and Combustion Science · 2024-01-19
Jingyuan Zhao, Xuning Feng, Quanquan Pang, Michael William Fowler, Yubo Lian, Minggao Ouyang, Andrew F. Burke
Read original paper ↗ ·Machine learning assisted discovery of high-efficiency self-healing epoxy coating for corrosion protection
npj Materials Degradation · 2024-01-19
Tong Liu, Zhuoyao Chen, Jingzhi Yang, Lingwei Ma, J.M.C. Mol, Dawei Zhang
Read original paper ↗ ·