Chiara Angiolillo
AI-based orchestration of photochemical reactions for solar fuel production.
Rel. Eliodoro Chiavazzo, Giulio Barletta. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Energetica E Nucleare, 2025
|
|
PDF (Tesi_di_laurea)
- Tesi
Accesso limitato a: Solo utenti staff fino al 28 Novembre 2028 (data di embargo). Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (2MB) |
Abstract
Since the Industrial Revolution, and particularly in recent decades, growing attention has been devoted to environmental issues and global warming. Scientific and technological progress has therefore increasingly focused on developing new processes and technologies capable of mitigating the rise in global temperature by reducing the concentration of Greenhouse Gases (GHG) in the atmosphere. Among the major GHGs, carbon dioxide (CO2) represents the gas with the greatest overall climatic impact, due to both its high atmospheric concentration and its long residence time. For this reason, recent research has concentrated on the development of Carbon Capture, Utilization, and Storage (CCUS) technologies, which have shown promising results at the experimental level.
This work focuses on the optimization of a photocatalytic process for the reduction of CO2 to CH4, employing three newly synthesized porphyrins as catalysts
Tipo di pubblicazione
URI
![]() |
Modifica (riservato agli operatori) |
