# name
Machine learning for iron oxide identification from oxygen K edge in EELS spectra

# metadata.dc.description[].value
Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2021, Tutors: Sònia Estradé, Daniel Del Pozo Bueno

# metadata.dc.description.abstract[].value
In this work we test machine learning tools such as the Support Vector Machine algorithm and neural network models on the task of Electron Energy-Loss Spectroscopy (EELS) spectra classification. Given many sample spectra of EELS applied on wüstite and magnetite nanocubes, we train both models to determine the oxidation state of iron. We show that SMV exhibits a good performance on classifying clean data, and we demonstrate the capability of neural networks of producing robust results given shifted data

# metadata.dc.subject.classification[].value
Espectroscòpia de pèrdua d'energia d'electrons

# metadata.dc.title[].value
Machine learning for iron oxide identification from oxygen K edge in EELS spectra