近期，佐治亚理工学院、康涅狄格大学以及清华大学的研究团队在《Nature Communications》杂志上发表了一篇题为“AI-assisted discovery of high-temperature dielectrics for energy storage”的论文，报道了一项基于人工智能（AI）的材料科学突破。这一研究成果揭示了聚降冰片烯和聚酰亚胺系列中的新材料，为静电电容器的储能性能带来了革命性的提升。
静电电容器在国防、航空、能源和交通领域的先进电力系统中扮演着关键角色。它们的品质因数，即能量密度，主要取决于所选择的介电材料。当前工业级聚合物介电材料，如柔性聚烯烃或刚性芳族化合物，虽然在高能量密度或高热稳定性方面表现出色，但往往难以同时满足这两个特性。这一研究团队通过结合AI、聚合物化学和分子工程，成功地在聚降冰片烯和聚酰亚胺系列中发现了新型电介质材料。
研究发现，这些新材料在广泛的温度范围内展现出优异的热稳定性和高能量密度。其中一种材料在200°C时的能量密度达到了8.3 J/cc，这一数值是同温度下任何现有聚合物电介质的11倍。此外，研究团队还评估了进一步优化聚降冰片烯和聚酰亚胺系列的途径，旨在使这些电容器在苛刻的应用场景（如航空航天领域）中表现出色，同时兼顾环境可持续性。
这一研究不仅拓展了静电电容器在85-200°C温度范围内的应用潜力，而且展示了AI在化学结构生成和性质预测方面的重要作用，预示着材料设计领域可能实现的突破。通过AI辅助的材料发现过程，研究团队成功地跨越了材料科学中的传统障碍，为高性能储能材料的开发开辟了新路径。
这一研究成果不仅为静电电容器技术的进步提供了重要支持，也为未来材料科学的创新应用提供了灵感，预示着人工智能在推动化学和材料科学领域发现和开发新材料方面的巨大潜力。
英语如下：
News Title: “AI-Assisted Discovery of High-Performance Energy Storage Materials, 11 Times Stronger, Applied to Advanced Power Systems”
Keywords: AI-assisted, New materials, Energy storage application
News Content: Title: Georgia Tech and Tsinghua Team Unveil AI-Driven High-Performance Energy Storage Materials in Nature Communications
In a groundbreaking development, a research team from Georgia Tech, the University of Connecticut, and Tsinghua University has reported on the discovery of novel materials for energy storage in a paper published in the journal Nature Communications. Titled “AI-assisted discovery of high-temperature dielectrics for energy storage,” the paper showcases an innovative material science achievement facilitated by artificial intelligence (AI).
This research reveals new materials within the polyperflourenes and polyimides series, which have revolutionized the energy storage capabilities of electric capacitors. These capacitors play a pivotal role in advanced power systems across sectors such as defense, aerospace, energy, and transportation. Their quality factor, or energy density, is primarily determined by the chosen dielectric material. Industrial-grade polymer dielectric materials, such as flexible polyolefins or rigid aromatic compounds, may excel in high energy density or thermal stability but often struggle to satisfy both properties simultaneously.
Through a combination of AI, polymer chemistry, and molecular engineering, the research team successfully identified new dielectric materials within the polyperflourenes and polyimides series.
The study highlights that these new materials demonstrate exceptional thermal stability and high energy density across a broad temperature range. One of the materials, for instance, boasts an energy density of 8.3 J/cc at 200°C, a figure that is 11 times higher than any existing polymer dielectric material at the same temperature. Moreover, the team evaluated avenues for further optimization of the polyperflourenes and polyimides series to ensure these capacitors excel in demanding applications (such as aerospace) while maintaining environmental sustainability.
This research not only enhances the potential applications of electric capacitors within the 85-200°C temperature range but also underscores the pivotal role of AI in chemical structure generation and property prediction. It paves the way for potential breakthroughs in material design. By leveraging AI in the material discovery process, the team successfully overcomes traditional obstacles in material science, opening new avenues for the development of high-performance energy storage materials.
This research provides significant support for advancements in electric capacitor technology and inspires future applications in material science innovation, indicating the immense potential of AI in driving the discovery and development of new materials in the fields of chemistry and materials science.
【来源】https://www.jiqizhixin.com/articles/2024-07-24-9
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