Harnessing Machine Learning for EMI Shielding Materials: State-of-the-Art Advances and Prospects Ahead
Year: 2025
Type: conference-paper
Abstract: The field of EMI shielding materials is undergoing rapid transformation, driven by escalating demands for high-performance shielding in modern electronics. However, the design and development of advanced shielding materials depend on empirical, trial and error methodologies. This dependance on iterative experiments not only brings up the cost but also results in longer developmental cycles presenting a significant bottleneck for innovations. The integration of machine learning (ML) in the field of EMI shielding materials drastically reduces the cost and delay in the conventional experimental method, and effectively establishes a rapid prediction model for shielding effectiveness and proper analysis and optimization of new and advanced shielding materials. This review critically examines the progress in applying ML to the field of EMI shielding materials. Furthermore, the article discusses the key challenges and emerging trends in ML to EMI shielding materials.
Institutions: University of Bristol, Amity University
Language: English
Field: Materials Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7123341604