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，并整合到全面的催化剂设计中。特别是考虑到可再生能源作为原料的质量起伏不定，催化剂失活问题应予以解决。对催化剂失活机理的基本了解和对催化剂失活的数学描述是未来化工原料替代的基础。它能够为可持续的催化化学过程设计合适的原料/催化剂组合。该项目的主要目的是加深对均相催化失活机理的理解，以及如何避免对连续反应过程中的催化反应产生负面影响。本项目将详细讨论四种失活模式：1)长期失活(老化)；2)连续过程中的浸出造成的催化剂损失；3)气液传质限制引起的失活；4)杂质引起的失活。有条不紊地，这将通过在动力学和连续实验期间使用多光谱测量和先进的化学计量分析来实现，包括在工艺层面上的催化剂分离和回收。由此得到的催化剂物种和反应物的时间分辨分子数据将用于开发、简化和参数化新的失活机理动力学模型。这些模型作为基于模型的过程控制和优化的基础，例如通过催化剂添加策略，作为对催化反应的负面影响的对策，这些负面影响将在微型工厂的长期连续反应活动中得到验证。因此，综合办法应涉及停用机制的确定、量化和基于模型的补偿/预防。这种方法在均相催化中仍未得到充分体现，并在项目中被提出，该项目适用于a)结合互补技术(FTIR、拉曼、核磁共振、GC-MS)的操作多光谱失活研究，b)应用过程动力学(扰动)解决短期间歇和长期连续操作中的4种失活模式的动力学失活研究，c)失活模式的机械动力学建模以预测催化剂的用量，d)在长期、连续操作的微型工厂活动中验证加药策略，e)全过程模拟/控制，以评估进一步的催化剂失活对策。

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.