Chemical processes and industrial plants

Prof. Bianchi
Mass and energy balances
Homogeneous and heterogeneous chemical kinetics
Study and design of batch reactors
Study and design of continuous reactors (PFR and CSTR) Reactors for biphasic and triphasic kinetics.
Optimization of times, sizes, and costs of chemical reactors

Prof. Rossetti
The students will be guided through a base introduction on the numerical methods needed to solve simple or advanced kinetic modelling and on the best ways to express kinetic rate equations for use in the design equations of ideal reactors.
Numerical methods will be introduced with the basic algorithm, followed by exercises, to be solved either manually or with the aid of Excel/Matlab/Phyton scripts. Basic understanding of the meaning and implementation modes of preconstructed scripts will be required to all students. Those aiming to become expert users will be guided (on request) to the development of an own-written script.
Correlated to the fundamental part on applied kinetics and reactors, numerical examples will be given in order to gain a practical insight into the reactor design activity (ideal batch reactor, continuous PFR and CSTR reactors).
Introductory concepts will be given on the issues raising with non ideal reactors. Computational fluid dynamics (CFD) will be introduced for these general concepts, with examples on reacting media in continuous flow reactors. COMSOL Multiphysics will be used as computational tool.
Finally, AI implementations have proven to dramatically reduce design and experimental efforts by enabling laboratory automation, predicting bioactivities of new drugs, suggesting synthetic routes to complex target molecules, predicting properties of materials and new molecules, optimizing reaction conditions, select the most appropriate plant configuration among thousands and discriminating among thousands of scenarios during fault, risks or lifecycle assessments. The potential and best practices for these emerging technologies will be introduced to the students with a comparison between different approaches of Machine Learning in cyber-chemical systems.