RELIANCE: REaL-tIme characterization of ANisotropic Carbon-based tEchnological fibres, films and composites

可靠性：各向异性碳基技术纤维、薄膜和复合材料的实时表征

• 批准号: EP/X026884/1
• 负责人: Philip Withers
• 金额: $ 67.6万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX026884%2F1
• 关键词: RELIANCE; REaL; tIme; characterization; ANisotropic

RELIANCE will develop and implement depth-resolved multimodal X-ray imaging and scattering tools that will enable the automatedreal-time characterization at the nano-scale of the structure and morphology of materials, devices and their manufacturing processes,reliably and with precision. Providing training in the use of these tools, as well as training in open-access science and development oftransferable skills for all ESR fellows is one of the key objectives of RELIANCE.The methodologies developed by RELIANCE will be implemented for optimizing and controlling the processing of high-performancepolymeric materials and composites, i.e. solution-spinning of aramid fibres, compaction-heat stretching of polyethylene film, andpultrusion of composites. RELIANCE will significantly improve quality control of a wide range of technological materials used incomposite materials. Through integration of real-time data analysis and process parameters by application of machine learning, themethods will lend themselves to Industry 4.0 solutions relying on cyber physical systems for decentralized decisions based on actual,current structural properties observed during processing.The real-time access to nanostructure in the diverse applications is provided by specialized X-ray instrumentation. A sharedmethodology for data reconstruction and machine-learning assisted analysis exploiting prior knowledge and modelling of structuralanisotropy, is applied to enable the data reduction speed required to match industrial processing.RELIANCE brings together a consortium of leading international experts in X-ray scattering, imaging and automatized analysis ofscattering data, 3D reconstruction algorithms and automatized analysis of imaging data and Materials Applications, with industrialleaders in manufacturing and application of high-performance polymer materials, and in highly specialized X-ray instrumentation andscientific data acquisition and analysis.

RELIANCE将开发和实施深度分辨的多模态X射线成像和散射工具，这些工具将能够在纳米尺度上对材料、设备及其制造过程的结构和形态进行可靠和精确的自动实时表征。RELIANCE的主要目标之一是为所有ESR研究员提供使用这些工具的培训，以及开放获取科学和发展可转移技能的培训。RELIANCE开发的方法将用于优化和控制高性能聚合物材料和复合材料的加工，即芳纶纤维的溶液纺丝，聚乙烯薄膜的预聚-热拉伸，以及复合材料的制浆。RELIANCE将显著改善复合材料中使用的各种技术材料的质量控制。通过应用机器学习将实时数据分析和工艺参数集成，这些方法将有助于工业4.0解决方案，该解决方案依赖于网络物理系统，根据加工过程中观察到的实际当前结构特性进行分散决策。利用结构各向异性的先验知识和建模，采用数据重建和机器学习辅助分析的共享方法，以实现与工业处理相匹配的数据简化速度。RELIANCE汇集了X射线散射，散射数据成像和自动化分析，3D重建算法和成像数据自动化分析以及材料应用方面的领先国际专家联盟，与高性能聚合物材料的制造和应用以及高度专业化的X射线仪器和科学数据采集与分析领域的行业领导者合作。