Personale docente

Fabrizio Bezzo

Professore ordinario

ICHI-02/A

Indirizzo: VIA F. MARZOLO, 9 - PADOVA . . .

Telefono: 0498275468

E-mail: fabrizio.bezzo@unipd.it

Dr. Fabrizio Bezzo is Professor of Chemical Engineering at the Department of Industrial engineering, where he co-leads the CAPE-Lab research group. He received his degree in Chemical Engineering at the University of Padova and his PhD at Imperial College London (UK). His research interests comprise process design and supply chain optimization of production systems for renewable energy and sustainable industrial processes, and the modeling and optimization of chemical and biological processes. He has published over 200 scientific papers in international research journals and conference proceedings. He co-chaired the Energy Section of the European Federation of Chemical Engineering in years 2017-2022. He is the Director of the professional Master programme "GMP compliance quality expert for pharmaceutical operations". He coordinates the H2020 ITN project " DigitAlgaesation - A knowledge-based training network for digitalisation of photosynthetic bioprocesses".

A list of publications can be found in the attached file.

Download Pubblicazioni_Bezzo.pdf

Fabrizio Bezzo's research interests comprise:

Design and analysis of energy systems:
- optimal design of supply chains for carbon capture, transport, utilization and sequestration (CCUS)
- design and optimization of processes for biofuels production
- modelling and optimization of microalgae production systems

Experiment design for model identification:
- development of advanced model-based experiment design techniques
- design of clinical tests for identification of physiological models
- development and identification of biosystems models

Statistical process control:
- data-driven modelling for process and product quality control in the fine chemicals industry
- design space characterization and process scale-up in the pharmaceutical industry

Fabrizio Bezzo co-leads the CAPE-Lab research group.

The titles of some recent Master's theses are listed in the following:

- Optimization of a food regeneration climatic chamber via computational fluid dynamics
- Recycling of critical materials for the renewable energy sectors: technology analysis and supply chain modelling
- From conventional to surrogate-based flexibility assessment: application to a bio-methanol process under uncertainty
- Bioprocessing of genetically engineered microalga Nannochloropsis gaditana for lipid production: upstream and downstream operations
- Conceptual design of a green-ammonia production process: cost and safety assessment
- Optimization of the design and operation of outdoor microalgae production in industrial-scale tubular photobioreactors
- CFD-based design and optimization of a mixing impeller for enhanced viscosity and pH measurements in hand dish-washing liquid products
- Development of a test method to study grease-on-plastic cleaning through hand wash
- Experimental investigation of the combined effect of light and temperature on microalgae growth in milli-photobioreactors
- Experimental and model-based analysis for optimizing Chromochloris zofingiensis growth from laboratory to plant scale
- An optimisation framework to define maximum parametric uncertainty guaranteeing acceptable model fidelity
- Development of a model for temperature control in an industrial batch reactor
- Study of the main parameters affecting the rinsing speed of hand dish washing products
- Environmental optimization of the Northern Italy supply chain for the treatment of residual plastic packaging waste considering waste-to-energy and chemical recycling technologies
- Alternative sustainable routes to methanol production: Techno-economic and environmental assessment
- Fluid dynamics modelling and process optimization of a flashing light photobioreactor for enhancing microalgae cultivation
- Design and optimization of membrane processes for carbon capture purposes
- Optimal design of experiments for kinetic model structure identification using reinforcement learning methodologies
- Economic optimization of the Northern Italian supply chain for the treatment of residual plastic packaging waste considering waste-to-energy and chemical recycling technologies
- Experimental analysis of the effect of different light conditions on microalgal growth in small-scale continuous photobioreactors
- Advanced process control with surrogate models based on finite impulse response neural networks
- Identification of a multi-vial primary drying model for process optimization in the presence of limited industrial data
- Assessing mass transfer in a polymer dissolution process via test method development and CFD simulations
- Economic optimisation of carbon capture and sequestration from Italian industrial sources under seismic risk constraints
- Design of a chemical looping reactor for the production of syngas from CO2
- Process design and optimization of protein extraction from sunflower meal
- Identification of lyophilization models via sensitivity analysis and optimal design of experiments
- Optimization of the carbon capture and sequestration supply chain for the Italian cement industry
- Coupling artificial neural networks and optimal design of experiments for fast recognition of kinetic models from experimental data
- Hybrid modelling of batch bioreactors for mammalian cell cultures