Value chain optimization for the industrial deployment of novel photochemical synthetic pathways

光化学能够通过考虑替代、优先可再生和绿色原料来颠覆性地改变价值和供应链。采用这些原料而不是石油和天然气将改变我们所知的化学工业，正如它自工业化开始以来所发展的那样：大宗化学品通常从蒸汽裂解开始，通过多个步骤大规模生产。在许多情况下，供应链集成在一个站点（“一体化”站点）上，以改善热集成物流和管道安全。因此，将初始原料从天然气改为生物基甲醇将对供应和价值链产生重大影响。虽然这一变化在我们实现碳中和的过程中被广泛接受，但需要考虑对化学工业的技术和经济影响，以保持商业可行性和竞争力。光化学是有潜力利用生物原料进行化学转化的技术的一个主要例子。在这个项目中，我们计划通过研究技术经济方面以及价值和供应链的变化，为在大规模化学工业中实施光化学铺平道路。我们将考虑改变边界条件，包括转向可再生原料和二氧化碳税。我们将选取在帝国理工学院的巴斯夫光化学集群中进行研究的示例，包括用二氧化碳作为试剂制造用于聚酯和聚酰胺制造的二酸，以及将甲醇转化为单乙二醇 (MEG)。该项目将全面涵盖研发工作流程以及价值链和供应链，旨在对未来的加工选项进行基准测试和优化。该项目需要对化学工程的整体挑战感兴趣。它将考虑机器学习算法和理论评估，而不是实验工作。

Photochemistry is capable of disruptively changing value and supply chains by considering alternative, preferentially renewable and green feedstock. Taking these feedstocks rather than oil and natural gas will change the chemical industry as we know it and as it has developed since the onset of industrialization: Commodity chemicals are produced on large scale in multiple steps often starting from steam cracking. In many cases supply chains are integrated on a single site ("Verbund"-site) for improved heat integration logistics, and safety in pipes. Therefore, changing the initial feedstock from natural gas to bio-based methanol for example will have major implications on the supply and value chains. While this change is widely accepted on our way to carbon neutrality, the technical and economical impact on the chemical industry needs to be considered to maintain commercial viability and competitiveness. Photochemistry is a prime example of technology that has the potential to utilize biogenic feedstock for chemical conversions. In this project we plan to pave the way toward implementing photochemistry in the large scale chemical industry by investigating the technoeconomical aspects and the changes of value and supply chains. We will consider changing boundary conditions, including the shift to renewable feedstock and CO2-taxation. We will pick up examples investigated within BASF's photochemistry cluster at Imperial, including the fabrication of di-acids with CO2 as a reagent to be used in the polyester and polyamide fabrication and the conversion of methanol to mono-ethyleneglycol (MEG). The project will be holistic along the R&D workflow and along the value and supply chains and aim at benchmarking and optimizing future processing options. This project will require an interest in holistic challenges of chemical engineering. It will consider machine learning algorithms and theoretical assessments rather than experimental work.