Molecular catalyst data driven reaction monitoring and control in homogeneous catalysis

均相催化中分子催化剂数据驱动的反应监测和控制

• 批准号: 537105915
• 负责人: Professor Dr.-Ing. Christof Hamel
• 金额: --
• 依托单位: Max-Planck-Institut für Chemische Energiekonversion (CEC)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/537105915?language=en
• 关键词: Molecular; catalyst; data; driven; reaction

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.

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。特别是考虑到使用可再生能源作为质量波动的原料，应解决催化剂失活问题。对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过程设计合适的原料/催化剂组合。本项目的主要目的是为均相催化的失活机理提供更深入的了解，以及如何避免对连续反应过程的催化反应产生伴随的负面影响。本项目将详细介绍四种失活模式：1)长期失活（老化），2)连续过程浸出导致的催化剂损失，3)气/液质量输运限制引起的失活，4)杂质引起的失活。系统地，这将通过在动力学和连续实验中使用多光谱测量结合先进的化学计量学分析来实现，包括催化剂分离和回收，在工艺水平上。由此得到的催化剂种类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，例如通过催化剂的剂量策略，作为对催化反应的负面影响的对策，将在小型工厂的长期连续反应活动中得到验证。因此，一个综合的方法应该解决失活机制的识别、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代表，并在申请的项目中提出，用于涵盖以下程序a)结合互补技术（FTIR，拉曼，NMR, GC-MS）的操作多光谱失活研究，b)应用过程动力学（扰动）解决短期批量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，以预测催化剂的投药；d)在长期、连续运行的小型工厂活动中验证投药策略；e)全过程模拟/控制，以评估催化剂失活的进一步对策。