Multiscale modelling and artificial intelligence for the digitalization of the pharmaceutical, food and personal-care industries
keywords ARTIFICIAL INTELLIGENCE, ARTIFICIAL NEURAL NETWORK, COMPUTATIONAL FLUID DYNAMICS, DISSIPATIVE PARTICLE DYNAMICS, MACHINE LEARNING, MOLECULAR DYNAMICS
Reference persons ANTONIO BUFFO, DANIELE MARCHISIO
Research Groups AA - Multiscale modelling for materials science and process engineering
Thesis type MODELING AND SIMULATION
Description Many processes of the pharmaceutical, food and personal-care industries can be simulated by using multiscale modelling and artificial intelligence. Their simulation allows to optimize the process in order to reduce energy consumption, environmental impact and use of raw materials, making them more sustainable. In this thesis particular emphasis is given to structured fluids, such as food and pharmaceutical emulsions, concentrated surfactants solutions and colloidal systems for controlled drug delivery (including m-RNA medicine). The techniques employed include: full-atom and coarse-grained molecular dynamics, computational fluid dynamics and population balances, as well as artificial intelligence.
Deadline 21/07/2023 PROPONI LA TUA CANDIDATURA