Automated Dynamic Flow System for Efficient Mapping of Reaction Design Spaces
Lead Research Organisation:
University of Leeds
Department Name: Chemical and Process Engineering
Abstract
The Project: has three key elements, each with its own significant academic research challenges and questions to be answered:
(i) Design of new multidimensional dynamic flow experiments utilising nonlinear gradient profiles to rapidly explore the design space. Exploration of the entire design space will be achieved by constructing dynamic profiles to pass through space-filling designs such as Latin hypercubes. Robustness testing will be built into the profiles by increasing data-density around the expected location of the optimal conditions.
(ii) Automated generation of process models via integration of new multidimensional dynamic flow experiments. The dynamic output will be collected via integration of multipoint sampling along the length of the reactor. Inline process analytical technologies (e.g., UV-Vis, IR) will enable rapid analysis for densely mapping out the design space, which will be simultaneously verified using complementary on-line tools (e.g., HPLC). The team will regularly meet with the AZ supervisor to ensure relevant exemplars are chosen, including a variety of homogeneous liquid reactions and heterogeneous reactions (e.g., gas-liquid-solid hydrogenations) with mass transfer limitations.
(iii) Demonstration of model transfer and scale-up. Applicability of the process models generated in lab-scale continuous flow systems for batch manufacturing will be evaluated in large scale equipment.
(i) Design of new multidimensional dynamic flow experiments utilising nonlinear gradient profiles to rapidly explore the design space. Exploration of the entire design space will be achieved by constructing dynamic profiles to pass through space-filling designs such as Latin hypercubes. Robustness testing will be built into the profiles by increasing data-density around the expected location of the optimal conditions.
(ii) Automated generation of process models via integration of new multidimensional dynamic flow experiments. The dynamic output will be collected via integration of multipoint sampling along the length of the reactor. Inline process analytical technologies (e.g., UV-Vis, IR) will enable rapid analysis for densely mapping out the design space, which will be simultaneously verified using complementary on-line tools (e.g., HPLC). The team will regularly meet with the AZ supervisor to ensure relevant exemplars are chosen, including a variety of homogeneous liquid reactions and heterogeneous reactions (e.g., gas-liquid-solid hydrogenations) with mass transfer limitations.
(iii) Demonstration of model transfer and scale-up. Applicability of the process models generated in lab-scale continuous flow systems for batch manufacturing will be evaluated in large scale equipment.
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/X524931/1 | 30/09/2022 | 29/09/2027 | |||
2751715 | Studentship | EP/X524931/1 | 30/09/2022 | 29/09/2026 | Gintare Petkeviciute |