Papers citing Machine learning to optimize nanocomposite materials for electromagnetic interference shielding
Perspectives on absorption-dominant electromagnetic interference shielding materials with MXene and carbon-based polymer composites
Carbon · 2025-04-03
Nam Khanh Nguyen, Dae-Young Kim, Van Quan Phan, Minji Kim, Pangun Park, Junghyo Nah
Read original paper ↗ ·Machine learning-driven constructing relationship between processing and mechanical properties of TPV: A view of one stacking model
Polymer · 2025-04-07
Zhi Long Zhang, Lifeng Ma, Longhao Li, Chengyuan He, Chunxiao Li
Read original paper ↗ ·Recent innovations in EMI shielding materials for stealth technology
Synthetic Metals · 2025-04-12
Lalitha Durairaj, Malathi Murugesan
Read original paper ↗ ·Research advancements in machine learning-assisted design of reinforced composite radiation shields
Life Cycle Reliability and Safety Engineering · 2025-04-29
Ugochukwu C. Okonkwo, Christian Emeka Okafor, Shahnawaz Ahmad, Christopher Chukwuemeka Ohagwu, Michael Echeta Aronu, Imhade Princess Okokpujie, Christopher Igwe Idumah, Nelson N. Chukwu, Christian Ebele Chukwunyelu, Jiyaul Mustafa
Read original paper ↗ ·Deep Artificial Neural Network Modeling of the Ablation Performance of Ceramic Matrix Composites in the Hydrogen Torch Test
Journal of Composites Science · 2025-05-13
Jayanta Bhusan Deb, Christopher Varela, Fahim Faysal, Yiting Wang, Chiranjit Maiti, Jihua Gou
Read original paper ↗ ·A review of artificial intelligence (AI)-based applications to nanocomposites
Composites Part A Applied Science and Manufacturing · 2025-05-17
Krishna Prasath Logakannan, Ibrahim Güven, Gregory M. Odegard, Kan Wang, Chuck Zhang, Zhiyong Liang, Ashley D. Spear
Read original paper ↗ ·MXene‐Based Electromagnetic Interference Shielding Materials: A Leap From Fundamental Research to Intelligent Customization
Small · 2025-07-17
Hao Hu, Shuo Wang, Yiming Zhang, Xincai Wang, Boran Lin, Shaoxi Zhang, Wei Zhang, Pengfei Lian
Read original paper ↗ ·Investigation for the influence of Sm2O3 and CeO2 nanoparticles on the microstructure and electrochemical behavior of epoxy and prediction of mechanical characterizations of adhesive joining of CFPEEK via machine learning
Journal of Materials Research and Technology · 2025-08-30
Zummurd Al Mahmoud, Babak Safaei, Mohammed Asmael, Jana Petrů, Saeid Sahmani
Read original paper ↗ ·Electrospinning for electromagnetic interference shielding: Principles, challenges, and future directions
Carbon · 2025-09-11
Navid Keshmiri, Parisa Najmi, Abbas S. Milani, Mohammad Arjmand
Read original paper ↗ ·Ceramic-based electromagnetic interference shielding materials: Mechanisms, optimization strategies, and pathways to next-generation applications
Journal of Advanced Ceramics · 2025-10-27
Yang Li, Mengying Zhang, Jianing Chen, Xianhu Liu, Ming S. Huang, Chuntai Liu, Gang Shao, Hailong Wang, Bingbing Fan, Yuchang Qing
Read original paper ↗ ·Geometric Optimization of Passive High‐Frequency Electromagnetic Shielding Structures Based on Finite Element Analysis and Deep Learning
Energy Science & Engineering · 2025-10-30
Yuanhuang Liu, Tianchu Li, Ming Fang, Boyu Xing
Read original paper ↗ ·Harnessing Machine Learning for EMI Shielding Materials: State-of-the-Art Advances and Prospects Ahead
International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) · 2025-11-27
Reenu Elizabeth John, Suresh Babu M, Aagii Mariam Thomas, Prajina O. K, Anusree P G, Steffy Sara Varghese
Read original paper ↗ ·Artificial Intelligence-Powered prediction and optimization of compressive strength in lightweight hemp-based blocks for sustainable construction
ENGINEERING Structure and Civil Engineering · 2025-12-01
Tahera, B. J. Phanindra Babu, Sathvik Sharath Chandra, Shahaji Patil, Nikhil D. Doddamani, Pshtiwan Shakor
Read original paper ↗ ·Asymmetric multistage composite foams for high-efficient absorption-dominant electromagnetic interference shielding exploited with aid of machine learning
Carbon · 2025-12-04
Lingjun Zeng, Yu Zhang, Lan Xie, Bai Xue, Qiang Zheng
Read original paper ↗ ·Machine Learning‐Accelerated Discovery of High‐Performance Insulating Electromagnetic Interference Shielding Composites for Integrated Electronics
Advanced Materials · 2025-12-08
Yue Liu, Xinfeng Zhou, Peng Min, Bin Shen, Zhong‐Zhen Yu, Haobin Zhang
Read original paper ↗ ·Interpretable high-throughput machine learning-based screening of high-thermal-conductivity composites with experimental validation
Journal of Material Science and Technology · 2026-01-05
Yu Zhang, Yu Zhang, Bai Xue, Lingjun Zeng, Xiaoke Bu, Lan Xie, Quanwei Chen, Junhua Zhang
Read original paper ↗ ·MOPSO-Based Data Augmentation and Hardness-Assisted Interpretable Machine Learning for Accurate Prediction of Mechanical Properties of Mg Alloys
Journal of Materials Engineering and Performance · 2026-01-21
Rong Zhang, Hongxue Cui, Yongfan Li, Yongjian Wang, Junwei Pei, Chen Zhang, Liping Zhong
Read original paper ↗ ·Machine-learning for capacitive energy storage polymer dielectrics: opportunities and challenges
Progress in Materials Science · 2026-02-12
Minzheng Yang, Chaofan Wan, Runlin Liu, Junshang Zhang, Zhonghui Shen, Ce‐Wen Nan, Yang Shen
Read original paper ↗ ·Ensemble machine learning framework for predicting and optimizing electromagnetic shielding of Al 6061 hybrid metal matrix composites
Engineering Research Express · 2026-04-15
CH HIMAGIREESH, Srinu Budumuru, P V Vinay, Sankranti Srinivasa Rao, Ravi Kiran Balasa, Suribabu Naik Bhukya
Read original paper ↗ ·Deciphering peroxydisulfate vs. peroxymonosulfate activation by biochar catalysts via explainable machine learning
Journal of Hazardous Materials · 2026-05-18
Xiaochong Wang, Wei Zhang, Ruobing Cheng, Pengyuan Ma, Junhui Su, Mingyue Lin, Toru Murayama, Guangli Xiu
Read original paper ↗ ·Urban thermal evolution and baseline mapping of summer daytime land surface temperature in Chongqing, China
Urban Climate · 2026-06-23
Ao Wang, Yan Dai, Enqing Chen, Maomao Zhang
Read original paper ↗ ·Machine Learning-Empowered Electromagnetic Wave Absorbing Materials: From Forward Prediction to Generative Inverse Design
Molecules · 2026-07-08
Tongbaihui Qi, Jie Zhou
Read original paper ↗ ·Artificial intelligence and machine learning in composite materials: A comprehensive literature review and bibliometric analysis
Composites Part A Applied Science and Manufacturing · 2026-07-11
Huilong Fu, Amirali Eskandariyun, Paulina Portales Picazo, Kendall A. Johnson, Aric Morton, Mathew Wynn, Navid Zobeiry
Read original paper ↗ ·A heterogeneous ensemble AI framework for predicting dissolved sulfide in urban sewer networks
Process Safety and Environmental Protection · 2026-07-13
Mohamed Nashat, Tarek M. Zayed, Dramani Arimiyaw, Jingchao Yang
Read original paper ↗ ·Machine learning-assisted development of asymmetric melamine foam composites featuring a dendritic copper sulfide conductive skeleton and a planar conductive coating
Composites Part A Applied Science and Manufacturing · 2026-07-28
Ying Ping Zhou, Chenglei He, Lingjun Zeng, Lan Xie, Bai Xue, Qiang Zheng
Read original paper ↗ ·Rise of asymmetric structures for absorption-dominant electromagnetic interference shielding
Progress in Materials Science · 2026-08-21
Ali Dehghani, Mohammad Arjmand
Read original paper ↗ ·Data-driven prediction and experimental validation of the shielding absorption performance of polyolefin-based EMI shielding composites
Journal of Alloys and Compounds · 2026-09-01
Qi Chen, Yundan Du, Zhao Yang, Yongqiang Guo, Yali Zhang, Wei Gong
Read original paper ↗ ·Additive Manufacturing for Sustainable Electromagnetic Interference Shielding: Materials Discovery, Structural Optimization, and Machine Learning
Advanced Functional Materials · 2026-09-07
Roxana Moaref, Christopher M. Spezzano, Grace X. Gu, Uttandaraman Sundararaj
Read original paper ↗ ·Recent advances in perovskite oxide-based materials for electromagnetic interference shielding and microwave absorption
Materials & Design · 2026-09-18
Mohit Upadhyay, Shail Upadhyay
Read original paper ↗ ·3D architected carbon-based electromagnetic wave absorbers: A perspective on design and manufacturing strategies
Carbon · 2026-09-20
Dowon Noh, Hwanju Lim, Beomjun Choi, Dahyun Daniel Lim, Wonjoon Choi
Read original paper ↗ ·