Polina Yaseneva

Continuous flow Buchwald–Hartwig amination of a pharmaceutical intermediate

A flow process for direct amination of a pharmaceutically relevant substrate using a Pd-NHC based catalyst was demonstrated in a lab-scale mini-plant and in a pilot-scale plant. The lab-scale mini-plant was used to determine catalyst stability under recycling conditions. Results in the mini-plant have shown the maximum space–time yield between the three types of reactor systems: a batch reactor, a mini-plant and a pilot plant. A comprehensive life-cycle assessment study of the synthesis of organometallic catalysts and their impact on the overall LCA of flow vs. batch syntheses was developed. Combined with a simplified economic analysis, the LCA study confirmed the benefits of switching to flow.

A Multiobjective Optimization Including Results of Life Cycle Assessment in Developing Biorenewables-Based Processes.

A decision support tool has been developed that uses global multiobjective optimization based on 1) the environmental impacts, evaluated within the framework of full life cycle assessment; and 2) process costs, evaluated by using rigorous process models. This approach is particularly useful in developing biorenewable-based energy solutions and chemicals manufacturing, for which multiple criteria must be evaluated and optimization-based decision-making processes are particularly attractive. The framework is demonstrated by using a case study of the conversion of terpenes derived from biowaste feedstocks into reactive intermediates. A two-step chemical conversion/separation sequence was implemented as a rigorous process model and combined with a life cycle model. A life cycle inventory for crude sulfate turpentine was developed, as well as a conceptual process of its separation into pure terpene feedstocks. The performed single- and multiobjective optimizations demonstrate the functionality of the optimization-based process development and illustrate the approach. The most significant advance is the ability to perform multiobjective global optimization, resulting in identification of a region of Pareto-optimal solutions.