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Published on: December 27, 2012
Machine Learning-Guided Additive Manufacturing of Multilayer Aerogels for Ultrabroadband, Ultralow-Reflection
Jin Zhou1,2, Wei Liu2, Mingrui Han1
1State Key Laboratory of Coatings for Advanced Equipment, Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, School of Materials Science and Engineering, Shandong University, Jinan, P.R. China.
Advanced Materials (Deerfield Beach, Fla.)
|August 9, 2026
Summary
Researchers developed advanced electromagnetic interference (EMI) shielding aerogels using machine learning and additive manufacturing. These novel materials offer superior broadband performance, significantly reducing electromagnetic pollution.
Area of Science:
- Materials Science
- Nanotechnology
- Electromagnetics
Background:
- Secondary electromagnetic pollution necessitates advanced broadband, low-reflection electromagnetic interference (EMI) shielding materials.
- Existing materials often struggle to meet the demands for effective and broad-spectrum EMI suppression.
Purpose of the Study:
- To develop a machine learning (ML)-guided additive manufacturing strategy for fabricating multilayer gradient MXene-based aerogels.
- To achieve precise control over electrical conductivity and optimize EMI shielding performance.
Main Methods:
- Integration of cellulose nanofibers with MXene dispersion.
- Genetic algorithm-enabled structural optimization.
- Direct-ink writing for precise fabrication of gradient aerogels.
Main Results:
- Achieved benchmark EMI shielding with ultralow average reflectivity (R=0.045).
- Sustained high absorptivity (A>0.9) over an ultrabroad bandwidth (9.7-40.0 GHz).
- ML predictions closely agreed with simulations and experimental results.
Conclusions:
- Demonstrated a powerful data-driven paradigm for materials development.
- Established a blueprint for ML-accelerated development of intelligent electromagnetic protection systems.
- Highlighted the potential of lightweight, absorption-dominant aerogels for next-generation EMI shielding.
