Core Insights - A Chinese scientific team has discovered a new structure of one-dimensional charged domain walls in ferroelectric materials, which challenges traditional understandings and lays a scientific foundation for developing high-density artificial intelligence devices [1] Group 1: Research Breakthrough - The research was led by a team from the Chinese Academy of Sciences, including Academician Jin Kuijuan and researchers Ge Chen and Zhang Qinghua, who successfully created self-supporting fluorite-structured ferroelectric films using laser methods [1] - The findings were published in the international journal "Science" on January 23 [1] Group 2: Characteristics of Ferroelectric Materials - Ferroelectric materials consist of tiny "electrical compass" structures that spontaneously separate positive and negative charges, indicating their potential in information storage, sensing, and artificial intelligence applications [2] Group 3: Innovations in Research - The research team has been studying fluorite-structured ferroelectric materials since 2018, utilizing laser molecular beam epitaxy to grow films that are only about 5 nanometers thick, allowing for atomic-level observation of the crystal structure [6][7] - The discovery of the one-dimensional charged domain wall structure represents a significant shift in understanding, revealing the intrinsic coupling between polarization switching and oxygen ion transport in fluorite ferroelectrics [7] Group 4: Application Potential - The precise control of polarization "switches" and domain walls in ferroelectric materials is crucial for creating next-generation high-performance devices, particularly in the context of national strategic needs for information storage and artificial intelligence [8] - The one-dimensional charged domain wall is expected to increase storage density by several hundred times, potentially reaching 20 terabytes per square centimeter, which could store thousands of high-definition movies on a device the size of a postage stamp [8]
【中国新闻网】中国团队发现铁电材料新结构 将助力极限密度人工智能器件开发
Zhong Guo Xin Wen Wang·2026-01-23 05:54