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
基本信息
- 批准号:EP/X026884/1
- 负责人:
- 金额:$ 67.6万
- 依托单位:
- 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:
- 关键词:
项目摘要
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多模态 X 射线成像和散射工具,这些工具将能够可靠、精确地对材料、器件及其制造工艺的结构和形态进行纳米级自动实时表征。 RELIANCE 的关键目标之一是为所有 ESR 研究员提供使用这些工具的培训,以及开放获取科学方面的培训和可转移技能的开发。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、聚乙烯薄膜的压实热拉伸以及聚乙烯薄膜的拉挤成型。 复合材料。 RELIANCE 将显着改善复合材料中使用的各种技术材料的质量控制。通过应用机器学习集成实时数据分析和工艺参数,这些方法将适用于工业 4.0 解决方案,依靠网络物理系统,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。在不同应用中实时访问纳米结构是由专门的 X 射线仪器提供的。采用数据重建和机器学习辅助分析的共享方法,利用先验知识和结构各向异性建模,以实现与工业处理相匹配的数据缩减速度。RELIANCE 汇集了 X 射线散射、成像和散射数据自动分析、3D 重建算法以及成像数据和材料应用自动分析领域的国际领先专家组成的联盟, 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和分析领域的工业领导者。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Philip Withers其他文献
Dependence of dielectric behavior in BiFeO3 ceramics on intrinsic defects
BiFeO3 陶瓷介电行为对固有缺陷的依赖性
- DOI:
10.1016/j.jallcom.2012.06.110 - 发表时间:
2012-11 - 期刊:
- 影响因子:6.2
- 作者:
Hua Ke;Wen Wang;Yuanbin Wang;Hongjun Zhang;Dechang Jia;Yu Zhou;Xuekun Lu;Philip Withers - 通讯作者:
Philip Withers
Philip Withers的其他文献
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{{ truncateString('Philip Withers', 18)}}的其他基金
Henry Royce Institute Core Capital Award
亨利·莱斯研究所核心资本奖
- 批准号:
EP/X52850X/1 - 财政年份:2022
- 资助金额:
$ 67.6万 - 项目类别:
Research Grant
Tomographic Imaging: UK Collaborative Computational Projects
断层成像:英国协作计算项目
- 批准号:
EP/T026677/1 - 财政年份:2020
- 资助金额:
$ 67.6万 - 项目类别:
Research Grant
The Royce: Capitalising on the investment
罗伊斯:利用投资
- 批准号:
EP/S019367/1 - 财政年份:2018
- 资助金额:
$ 67.6万 - 项目类别:
Research Grant
A Reconstruction Toolkit for Multichannel CT
多通道 CT 重建工具包
- 批准号:
EP/P02226X/1 - 财政年份:2017
- 资助金额:
$ 67.6万 - 项目类别:
Research Grant
Preventing Surface Degradation in Demanding Environments
防止严苛环境中的表面退化
- 批准号:
EP/R00496X/1 - 财政年份:2017
- 资助金额:
$ 67.6万 - 项目类别:
Research Grant
Sir Henry Royce InsStitute - recurrent grant
亨利·莱斯爵士学院 - 经常性资助
- 批准号:
EP/R00661X/1 - 财政年份:2016
- 资助金额:
$ 67.6万 - 项目类别:
Research Grant
Next Generation Multi-Dimensional X-Ray Imaging
下一代多维 X 射线成像
- 批准号:
EP/M010619/1 - 财政年份:2015
- 资助金额:
$ 67.6万 - 项目类别:
Research Grant
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Immuno-Real Time PCR法精确定量血清MG7抗原及在早期胃癌预警中的价值
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