Automated reactor platforms for accelerated discovery of next generation polymers

用于加速发现下一代聚合物的自动化反应器平台

• 批准号: 2911012
• 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: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2911012
• 关键词: Automated; reactor; platforms; accelerated; discovery

The application of digital technologies is transforming the discovery and manufacturing process within small-molecule chemistry. However, the polymer chemistry community is yet to embrace these technologies and still relies on laborious laboratory techniques for polymer discovery and development. These approaches are not sufficient for developing the next generation of sustainable polymer materials. This project will involve designing and programming a reactor capable of conducting several consecutive reactions and automatically analysing the products. The reactor will use machine learning algorithms to direct experimentation, allowing exploration of parameter space which comprise multiple conflicting variables. Within the group, technologies have already been developed which can optimise the synthesis of model polymers (see Polymer Chemistry, 2022, 13, 1576) but a similar approach is now required to develop more applicable materials. The project will target controlled structure polymers, where the chemical composition and molecular weight properties are tailored for a specific application - in this case alongside an industrial partner. This partner are keen to develop more sustainable products and processes in order to meet future sustainability needs.

数字技术的应用正在改变小分子化学的发现和制造过程。然而，聚合物化学界尚未接受这些技术，并且仍然依赖于费力的实验室技术来发现和开发聚合物。这些方法不足以开发下一代可持续聚合物材料。该项目将涉及设计和编程一个能够进行多个连续反应并自动分析产物的反应器。该反应堆将使用机器学习算法来指导实验，从而允许探索包含多个冲突变量的参数空间。在该小组内，已经开发出可以优化模型聚合物合成的技术（参见 Polymer Chemistry, 2022, 13, 1576），但现在需要类似的方法来开发更适用的材料。该项目将针对受控结构聚合物，其中化学成分和分子量特性是针对特定应用量身定制的 - 在本例中是与工业合作伙伴一起。该合作伙伴热衷于开发更具可持续性的产品和流程，以满足未来的可持续性需求。