Papers citing The mastery of details in the workflow of materials machine learning
Machine Learning Meets Photocatalytic Water Splitting for Sustainable Hydrogen Production
ChemPhotoChem · 2026-08-01
Heesung Yoon, Jin Hyuk Cho, Wee‐Jun Ong, Soo Young Kim
Read original paper ↗ ·Mapping coupled composition-processing effects on the strength and ductility of magnesium alloys with interpretable machine learning
Physics Letters A · 2026-08-16
Xinchen Chen, Shuhang Zhao, Yao Zhou, Bin Zhou, Xianfeng Ma, Jishen Jiang
Read original paper ↗ ·Machine Learning for Structural Steels: Materials Design, Property Prediction, Durability, and Future Directions
Materials · 2026-08-25
Guomin Wei, Minghe Li, Bo Cui, Wencui Xiu, Asmawan Mohd Sarman
Read original paper ↗ ·Mechanism-informed machine learning for intelligent design of rare-earth-containing magnesium-based alloys
Journal of Magnesium and Alloys · 2026-09-02
LI Jiangwei, Haoran Shen, Tong Li, Huan Liu, Yuna Wu, Dan Song, Aibin Ma, Feng Xue, Panpan Zhou, Panpan Zhou
Read original paper ↗ ·Interpretable Tg prediction for polyurethane elastomers under restricted-distribution conditions
Chemical Engineering Journal · 2026-09-11
Lu Jin, Zhiyan Wei, Zihan Zhuang, Jialu Shang, Shuping Sun, Dichang Xue, 傅德彪, Yindi Zhu, Xiaodong Li, Hao Jiang, Meishuai Zou
Read original paper ↗ ·Machine learning-accelerated discovery and optimization of thermoelectric materials for energy conversion
Applied Energy · 2026-09-22
Siyu Han, Yucheng Lin, Naihua Miao, Yu Shu, Zhen Li, Linggang Zhu, Jian Xin Zhou, Zhimei Sun
Read original paper ↗ ·FC-Transformer multiple features fusion for predicting porosity and ILSS in CFRP autoclave processing
Journal of Composite Materials · 2026-09-26
Xiaobo Yang, Yuchen Zhang, Zhen Guo, He Xiang, Wenhan Cao, Lihua Zhan, Xintong Wu
Read original paper ↗ ·Machine Learning of Band Gaps and Thermodynamic Stability in A2BB′X6 (X = F, Cl, Br, I) Double Perovskites with Uncertainty-Aware Multi-Objective Screening
Nanomaterials · 2026-09-26
Qilin Wei, Haiyan Zhang, Chengyu Peng, Ye Tian, Yan Zhang, Yongmeng Yang, Menghong Liu, Nianxi Xu
Read original paper ↗ ·Machine Learning‐Driven Rational Design of Organic Electro‐Oxidation Catalysts: A Mechanism‐Embedded Approach to Selectivity Engineering
Small · 2026-09-27
Haiyi Jiang, Yanjie Ren, Lang Gan, Jingxi Zhang, Wei Chen, Wei Qiu, Zhaoling Ma
Read original paper ↗ ·Interpretable machine learning reveals morphology-mediated performance pathways in organic solar cells
Physica Scripta · 2026-09-29
Darya Rasul Ahmed, Fahmi Fariq Muhammedsharif
Read original paper ↗ ·Language-model-guided pre-screening of porous carbon electrodes: Overcoming data fragmentation for reliable capacitance prediction
Chemical Engineering Journal · 2026-09-30
Rui Luo, Xinwei Dong, Xiangbo Lin, Xiong He, Sisi Liu, Jinghua Liu, Guofu Wang
Read original paper ↗ ·Integrated classical/quantum–classical neural networks, DFT, and experiments for predicting bandgap and color of CrxSbxTi1−2xO2 yellow-orange pigments
Scientific Reports · 2026-10-01
Seyed Yousof Vaselnia, Mohsen Khajeh Aminian, Reza Dehghan Banadaki
Read original paper ↗ ·Experimental investigation of multiaxial fatigue behavior and life prediction using Transformer-PINN in Q355E steel welded joints
International Journal of Fatigue · 2026-10-02
Peipeng Wang, Zichen Liu, Lin Xu, Yan Lu, Jintao Cui, Yuhao Yan, Yang Li, Guipu Wang
Read original paper ↗ ·Special Issue on Design, Development, and Characterization of Advanced Materials for Modern Industry
Applied Sciences · 2026-10-09
Mădălina Simona Bălțatu
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