Quantum Dot synthesis in Continuous Flow via Self-Optimising Nanoscale Manufacturing Platforms

通过自优化纳米级制造平台在连续流中合成量子点

• 批准号: 2783323
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 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=studentship-2783323
• 关键词: Quantum; Dot; synthesis; Continuous; Flow

This project will build platform technologies, comprising advanced chemical reactors underpinned by computational intelligence, which can scale up production of advanced nanoparticle products (quantum dots) without loss in the precise control over structural dimensions which are achieved in research laboratories. It will build laboratory reactors which can be programmed to monitor the nanoparticle formation process in real time and relate formation conditions to the final product particle's properties. It will incorporate and optimise machine learning algorithms which will direct the reactors towards achieving the desired specification through 'self-optimisation' of conditions. The optimised laboratory nanoparticle formation processes will be transferred to several manufacturing environments, including R&D process laboratories and manufacturing facilities at industrial sites and scale up will be demonstrated. The position will be based at the School of Chemistry and the Institute of Process Research and Development at Leeds. It aligns directly with the EPSRC Digital Manufacturing theme and there will be interaction with partners of the EPSRC grant NanoMan, DeepMatter and CPI, to develop automated reactor platforms for quantum dot generation and work with collaborators at the University of Sheffield in the integration of machine learning algorithms.

该项目将建立平台技术，包括由计算智能支撑的高级化学反应器，该反应器可以扩大对高级纳米颗粒产品（量子点）的生产，而不会在研究实验室实现的结构尺寸的精确控制中而不会损失。它将构建实验室反应器，可以对其进行编程以实时监视纳米颗粒形成过程，并将形成条件与最终产物粒子的性质相关联。它将结合并优化机器学习算法，该算法将通过条件的“自动化”来指导反应堆实现所需的规范。优化的实验室纳米颗粒形成过程将被转移到几个制造环境中，包括研发工艺实验室和工业场所的制造设施，并将展示扩大规模。该职位将设在化学学院和利兹进程研究与发展研究所。它直接与EPSRC数字制造主题保持一致，并将与EPSRC Grant Nanoman，DeepMatter和CPI的合作伙伴进行互动，以开发自动反应堆平台，以生成量子点生成，并与谢菲尔德大学的合作者在机器学习算法的集成中与合作者合作。