人工智能赋权:建立人工智能和电磁屏蔽材料研究之间的协同作用
Shuaimin Zheng1, Junting Lei1, Peitao Xie2
1Key Laboratory of Materials Processing and Mold (Zhengzhou University), Ministry of Education, National Engineering Research Center for Advanced Polymer Processing Technology, Zhengzhou University, Zhengzhou 450002, China.
iScience
|February 2, 2026
概括
人工智能 (AI) 通过克服传统研究局限性,加速了先进的电磁屏蔽材料的开发. 这种方法整合了数据和物理,创建了专门的模型和数据库,以提高材料设计效率.
科学领域:
- 材料科学 材料科学 材料科学
- 计算科学 计算科学
- 电磁学 电磁学 电磁学 电磁学
背景情况:
- 由于智能电子系统,对高性能电磁屏蔽材料的需求日益增加.
- 传统的研发面临瓶:多参数合,高成本和多规模的设计挑战.
- 现有的人工智能 (AI) 方法有希望,但受到有限的跨学科合作的阻碍.
研究的目的:
- 为推进人工智能驱动的电磁屏蔽材料设计提出解决方案.
- 为了解决目前用于材料开发的AI应用程序的局限性.
- 为了促进高效和高性能材料创新.
主要方法:
- 开发数据物理综合神经网络模型.
- 为电磁屏蔽创建特定领域的大型语言模型 (LLM).
- 建立全面的材料数据库.
- 促进数据共享和标准化的协议.
主要成果:
- 人工智能为克服研发瓶提供了一个变革性的范式.
- 提出的解决方案旨在增强人工智能在材料设计中的作用.
- 专注于数据集成,专业模型和协作框架.
结论:
- 人工智能集成,特别是与数据物理模型和LLM集成,对于下一代电磁屏蔽材料至关重要.
- 建立强大的数据库和促进数据共享是释放人工智能的全部潜力的关键.
- 跨学科的合作对于克服系统障碍和推进人工智能支持的材料设计至关重要.
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