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Electrochemistry Group @PoliTO
Experimental design/Machine learning methods in the energy field
keywords BATTERY, CHEMIOMETRICS, ENERGY, ENERGY STORAGE, FUEL CELL, MACHINE LEARNING, PHOTOVOLTAICS
Reference persons FEDERICO BELLA, DIEGO PUGLIESE
Research Groups Electrochemistry Group @PoliTO
Thesis type BIBLIOGRAPHIC
Description Batteries, photovoltaic cells, fuel cells, and supercapacitors represent the devices by which man manages (and will manage more and more) his daily life. These devices work through an excellent optimization of different components and engineering from a chemical, materials and energy points of view. In the academic field, the study of the various parameters that influence the performance of the aforementioned devices is done through experimental design techniques, organizing experiments and prototypes tests using commercial (or developed in universities) softwares.
This bibliographic thesis involves the drafting of a document in English starting from a collection of scientific articles (provided by the supervisor) on the topic of experimental design applied in the energy field. A device among the 4 mentioned above will be chosen (together with the student) and the student will be asked to develop a document that summarizes the studies made on the chosen device and how the experimental design approach was used to optimize the energy device.
See also https://en.wikipedia.org/wiki/Design_of_experiments
Required skills Capacità di leggere e scrivere in inglese. Volontà di concludere la tesi entro 6 mesi dall'inizio.
Deadline 15/01/2025
PROPONI LA TUA CANDIDATURA