Molecular catalyst data driven reaction monitoring and control in homogeneous catalysis

均相催化中催化剂失活的研究需要加强，并纳入综合催化剂设计。特别是考虑到使用可再生能源作为原料与波动的质量，催化剂失活的问题，应加以解决。对催化剂失活机理的基本理解和催化剂失活的数学描述是未来化学工业中原料替代的基础。它能够为可持续的催化化学工艺设计合适的原料/催化剂组合。 该项目的主要目的是提供更深入的了解在均相催化失活机制，以及如何避免伴随的负面影响，催化反应的连续反应过程。在本项目中，将详细讨论四种失活模式：1）长期失活（老化），2）由于连续过程的沥滤导致的催化剂损失，3）气/液传质限制导致的失活，4）杂质导致的失活。这将通过在动力学和连续实验期间使用多光谱测量结合先进的化学计量学分析来实现，包括工艺层面的催化剂分离和回收。由此产生的时间分辨的催化剂物种和反应物的分子数据将被用来开发，减少和参数化新的失活机理动力学模型。这些模型用作基于模型的过程控制和优化的基础，例如通过催化剂投配策略，作为对催化反应的负面影响的对策，其将在小型工厂的长期连续反应活动中得到验证。 因此，一个全面的方法应解决失活机制的识别、量化和基于模型的补偿/预防问题。这种方法在均相催化中仍然代表性不足，并在该项目中提出，该项目适用于涵盖以下程序：a）结合互补技术的操作性多光谱失活研究（FTIR、拉曼、NMR、GC-MS），B）动力学失活研究，应用过程动力学，解决短期分批和长期连续操作中的4种失活模式（扰动），c）失活模式的机械动力学建模以预测催化剂投配，d）在长期连续操作的小型工厂活动中的投配策略的验证，e）总工艺模拟/控制以评估催化剂失活的进一步对策。

Studies of catalyst deactivation in homogeneous catalysis need to be intensified and integrated into comprehensive catalyst design. Especially considering the use of renewables as feedstock with fluctuating quality the problem of catalyst deactivation should be addressed. A fundamental understanding of the deactivation mechanisms and the mathematical description of catalyst deactivation is the basis for a future feedstock substitution in the chemical industry. It enables to design suitable feedstock/catalyst combinations for sustainable catalyzed chemical processes. The main objective of this project is to provide a deeper understanding of deactivation mechanisms in homogeneous catalysis and how to avoid accompanying negative effects on catalyzed reactions for continuous reaction processes. Four deactivation modes will be covered in detail during this project 1) long-term deactivation (ageing), 2) catalyst losses due to leaching of continuous process, 3) deactivation induced by gas/liquid mass transport limitations, 4) impurity-induced deactivation. Methodically, this will be achieved by using multi-spectroscopic measurements combined with advanced chemometric analysis during kinetic and continuous experiments, including catalyst separation and recycling, on process level. The resulting time-resolved molecular data of catalyst species and reactants will be used to develop, reduce and parametrize new mechanistic kinetic models of deactivation. These models serve as basis for model-based process control and optimization, e.g. by catalyst dosing strategies, as a countermeasure for negative effects on catalyzed reactions that will be validated in long-term continuous reaction campaigns in miniplants. Consequently, a comprehensive approach should address deactivation mechanism identification, quantification and model-based compensation/prevention. Such an approach is still underrepresented in homogeneous catalysis and is proposed in that project applied for covering the following procedure a) operando multi-spectroscopic deactivation studies combining complementary techniques (FTIR, Raman, NMR, GC-MS), b) kinetic deactivation studies addressing 4 deactivation modes in short-term batch and long-term continuous operation applying process dynamics (perturbations), c) mechanistic kinetic modelling of deactivation modes to predict catalyst dosing, d) validation of dosing strategies in long-term, continuous operated miniplant campaigns, e) total process simulation/control to assess further countermeasures for catalyst deactivation.