About
Federico Raffone is a Fixed-term Researcher at the Department of Applied Science and Technology (DISAT) within the Polytechnic University of Turin, where he contributes to the College of Chemical and Materials Engineering as a teaching staff member.
- Teaching roles include: Main teacher for Computational Materials Science (2023/24, 2025/26), Course Collaborator for Quantum Condensed Matter Physics/Quantum Devices, and Nanomaterials Engineering in multiple academic years.
- Research focuses on computational materials science, quantum engineering, and machine learning applications for electrochemical systems and nanomaterials.
His recent publications highlight work in:
- CO2 emission energy harvesting via ionic liquid capacitors
- Pharmaceutical contaminant removal using metal-organic frameworks
- Osmotic energy conversion through functionalized graphene oxide membranes
- Machine learning-driven catalyst surface optimization
- Quantum conductance in memristive nanowires
As a PhD supervisor for Mattia Salomone, he explores machine learning applications in electroreduction catalysts. Research is conducted under the Institute of Fundamental Physics and Materials for Nanotechnology (DISAT).
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