Recently, the research team led by Academician Wang Weihua at the Dongguan Institute of Materials Science and Technology, Chinese Academy of Sciences, made important progress in the industrialization of amorphous and nanocrystalline materials. By combining artificial intelligence with materials design, process optimization and industrial application, the team has advanced the mass production and delivery of a self-developed high-frequency soft magnetic nanocrystalline alloy, marking a significant step toward the large-scale application of advanced soft magnetic materials.

The research team recently achieved mass production and delivery of a self-developed high-frequency soft magnetic nanocrystalline alloy. This marks a key milestone in the industrialization of amorphous materials.

The team has integrated artificial intelligence throughout the full R&D and industrialization chain, covering composition design, performance prediction, process optimization and commercial application. This AI-enabled approach has effectively addressed long-standing challenges in traditional materials development, including long R&D cycles, high trial-and-error costs and difficulties in performance optimization.

Based on its previously developed FeCoMoBSiNbCu ultra-fine nanocrystalline alloy composition, the team used an AI-assisted composition design model together with MatChat, a materials science intelligent agent, to accurately screen optimal composition ratios. AI-based simulation technologies were also applied to optimize preparation process parameters, significantly shortening the conventional trial-and-error development cycle.

The team has recently developed the JSN series of high-frequency nanocrystalline soft magnetic alloys and has fully mastered the production, preparation and post-treatment technologies for this new class of materials.

Laboratory multi-dimensional testing and pilot-scale validation have confirmed the material’s outstanding high-frequency magnetic permeability and low-loss characteristics. These properties are critical for the miniaturization and high-efficiency development of power electronic devices in the AI era. As a new-generation core material for onboard common-mode inductors in new energy vehicles, the alloy can significantly enhance electromagnetic interference resistance, enabling vehicles to operate with greater sensitivity, safety and energy efficiency.

The material has now entered large-scale mass production and has received broad market recognition. The team is actively expanding industrial cooperation with companies that have strong market and industrial advantages, including Dongguan Yumao, to promote the large-scale application of the material in key scenarios such as new energy vehicle electronic control systems and onboard power supplies. These efforts are expected to strengthen the role of advanced materials in driving the development of the industrial chain.

In addition to soft magnetic alloy ribbons, the team is also using AI technology as a core driving force to advance the development of new high-frequency, low-loss amorphous powder material systems. Supported by big data analysis and performance prediction models, the team has completed key technical preparations for this material system and has established full R&D capabilities covering composition design, powder preparation, performance evaluation and application adaptation. This lays a solid materials foundation for expanding high-end applications and overcoming future technical bottlenecks.

In my view, this progress is meaningful not only because it demonstrates the successful mass production of a high-performance nanocrystalline alloy, but also because it shows how artificial intelligence can reshape the traditional materials development process. As new energy vehicles, power electronics and AI-related devices continue to demand higher efficiency, smaller size and stronger electromagnetic reliability, AI-assisted materials innovation may become an important driving force for future industrial upgrading.

Source: Dongguan Institute of Materials Science and Technology, Chinese Academy of Sciences
Date: April 20, 2026