-
reactors and the study of sonochemical reaction engineering. We excel at controlled experiments aimed at determining the driving forces for optimally efficient sonochemistry across different reactor scales
-
manufacturing. AI methods will then be applied to this large database to inform optimal processing parameters that will produce components with reliable material properties. The process will be validated in a
-
in the design of bespoke sonochemical reactors and the study of sonochemical reaction engineering. We excel at controlled experiments aimed at determining the driving forces for optimally efficient
-
advanced numerical simulation and/or optimization tools to the design and characterization of the facility; interact with other technical groups working on the Diamond-II design (e.g. Engineering
-
optimality with computational efficiency. Reinforcement Learning through Stochastic Control. We will develop methods from stochastic control, which will provide a mathematically grounded approach that has a