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数字双胞胎的应用用于基于模拟的定制激光诱导的石墨烯

José Carlos Santos-Ceballos¹, Foad Salehnia², Alfonso Romero¹

¹Universitat Rovira i Virgili, Microsystems and Nanotechnologies for Chemical Analysis (MINOS), Tarragona, Spain.

Scientific reports

|May 6, 2024

概括

数字双胞胎通过模拟CO2激光过程来增强激光诱导石墨烯 (LIG) 制造. 这种方法使用机器学习来预测LIG属性,降低实验成本和优化生产.

科学领域:

材料科学材料科学材料科学
制造业工程制造工程
计算机建模计算建模

背景情况:

数字双胞胎为现实世界的系统提供虚拟表示,从而实现了增强的交互和理解.
将高质量的石墨烯整合到制造业中面临着由于复杂的材料整合而面临的挑战.
对石墨烯类材料的可扩展的现场制造技术对于推进电子设备至关重要.

研究的目的:

探索数字双胞胎在增强激光诱导石墨烯 (LIG) 制造中的应用.
开发一种通用的CO2激光模拟器,用于计算光能流量.
利用机器学习来预测和控制LIG导电性,形态和电阻.

主要方法:

使用数字双胞胎进行二氧化碳激光诱导聚胺涂的激光模拟.
使用机器学习算法来分析复杂的参数相互作用和非线性术语.
通过集成模拟和机器学习开发单步LIG模式过程.

主要成果:

该研究提出了一种方法,可以为二氧化碳激光器创建通用模拟,从而实现精确的光能流量计算.
机器学习模型用于预测和控制LIG导电性,形态和电阻.
数字双胞胎的整合大大减少了LIG生产中初步测试的需要.

结论:

数字双胞胎和机器学习提供了一种强大的方法来优化激光诱导的石墨烯制造.
这种综合方法简化了生产过程,减少了时间和成本.
开发的程序提高了生产定制石墨烯电子设备的效率和可扩展性.

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