**Abstract:** In a significant advancement for materials science and electronics, a team of researchers from the Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences (CAS) has successfully utilized artificial intelligence (AI) to design a new series of Fe-based amorphous alloys. These alloys are characterized by their exceptional magnetic properties, specifically ultra-high saturation magnetization (Bs) and ultra-low coercivity (Hc), which are crucial for enhancing the performance and energy efficiency of high-frequency, high-power electronic devices. The development, detailed in a recent publication in Advanced Functional Materials, marks a pivotal step in the integration of AI into the material design process, promising to accelerate the discovery and optimization of materials for advanced technological applications. **Key Events:** 1. **AI-Driven Design:** The researchers employed machine learning algorithms and AI techniques to predict and design the composition of Fe-based amorphous alloys. This approach allowed them to bypass the traditional trial-and-error methods, significantly reducing the time and resources required to develop materials with specific properties. 2. **Material Properties:** The newly designed Fe-based amorphous alloys exhibit ultra-high saturation magnetization (Bs) and ultra-low coercivity (Hc). These properties are essential for the efficient operation of high-frequency and high-power electronic devices, such as transformers and inductors, which are integral components in power electronics and telecommunications. 3. **Performance Enhancements:** The improved magnetic properties of these alloys are expected to lead to better energy efficiency, reduced heat generation, and enhanced overall performance in electronic devices. This could have far-reaching implications for industries that rely on high-power electronics, including renewable energy, electric vehicles, and data centers. 4. **Publication and Impact:** The findings were published in Advanced Functional Materials, a prestigious journal in the field of materials science. The publication highlights the potential of AI in materials research and development, suggesting that this method could be applied to other materials to achieve similar breakthroughs. **Key People:** - **Researchers from NIMTE:** The team at the Ningbo Institute of Materials Technology and Engineering, led by experts in materials science and AI, conducted the research and development of the new Fe-based amorphous alloys. **Key Locations:** - **Ningbo, China:** The research was carried out at the Ningbo Institute of Materials Technology and Engineering, a leading institution under the Chinese Academy of Sciences. **Time Elements:** - **Recent Publication:** The findings were recently published in Advanced Functional Materials, indicating that the research is current and relevant to ongoing developments in materials science and electronics. **Summary:** The Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences (CAS) has made a groundbreaking contribution to the field of materials science by using artificial intelligence (AI) to design a new series of Fe-based amorphous alloys. These alloys possess ultra-high saturation magnetization (Bs) and ultra-low coercivity (Hc), which are critical for the performance of high-frequency and high-power electronic devices. The AI-driven approach to material design has not only accelerated the development process but also yielded materials with properties that could significantly enhance the energy efficiency and operational capabilities of devices used in industries such as renewable energy, electric vehicles, and data centers. The publication of these findings in Advanced Functional Materials underscores the potential of AI in materials science, suggesting that this method could be a game-changer for future material innovations.