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材料创新的未来愿景以及如何通过服务快速跟踪它
1School of Natural Sciences, Technical University Munich, 85748 Munich, Germany.
ACS physical chemistry Au
|September 30, 2024
概括
本文介绍了多变量材料分析实体 (EMMA),这是一个将实验室测量与材料科学软件集成的服务. 埃马的目标是通过将实验数据与数字双胞胎连接起来来加速材料创新,以实现人工智能驱动的发现.
科学领域:
- 材料科学 材料科学 材料科学
- 计算科学 计算科学
- 人工智能的人工智能
背景情况:
- 将实验室硬件集成到材料科学的数字工作流中是一个重大挑战.
- 现有的计算实验方法有助于机器可读数据,但实验室数据集成仍然是一个障碍.
- 人工智能 (AI) 提供了材料发现的潜力,但需要可访问的,机器可读的实验数据.
研究的目的:
- 提出一种使用测量服务的新方法,以弥合材料科学中实验室实验和数字工作流之间的差距.
- 引入多变量材料分析实体 (EMMA) 的概念,作为材料数据的集中服务.
- 概述EMMA如何促进人工智能在材料发现和创新的使用.
主要方法:
- 探索测量服务的概念,以降低将实验室硬件集成到数字工作流中的障碍.
- 设想EMMA是一个集中服务,为共同的研究需求提供量身定制的测量包.
- 设计EMMA与数据处理,模拟和存储的软件生态系统,将测量与其模拟密切整合在一起.
主要成果:
- 欧洲药物管理协会 (EMMA) 的综合方法产生了与数字双胞胎相关的富含元数据的实验数据.
- 拟议的框架在物理样本和其数字表示之间创建了一个自相一致的联系.
- 连接到数字双胞胎的实验数据数据库可以为基于物理的机器学习模型提供燃料.
结论:
- 通过提供综合测量和软件服务,EMMA提供了一条加速材料创新的途径.
- 将实验数据与数字双胞胎连接起来,可以提高物质财产预测的可靠性.
- 通过利用综合数据的统计见解,EMMA的方法有助于识别特殊材料.
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