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BACH SICHES NURIA.pdf (1.23 MB)

Document type

Bachelor thesis

Publication date

2024-06

Publication license

cc-by-nc-nd (c) Bach, 2024
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/215509

4D STEM data analysis with KMeans clustering

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Abstract

When using 4D STEM methods to study various material characteristics, large amounts of diffraction images are created for each sample studied. To determine different characteristics of the material locally from the data obtained from the diffraction patterns, it has been considered to use clustering machine learning algorithms that will be able to quickly read and classify all diffraction images. A KMeans algorithm has been adapted to classify this type of data. The method has been found to work satisfactorily when applied to an experimental example

Description

Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2024, Tutores: Vanessa Costa, Sònia Estradé

Subject

Difracció, Algorisme k-means, Treballs de fi de grau

Subject (English)

Diffraction, k-means clustering, Bachelor's theses

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Treballs Finals de Grau (TFG) - Física

Citation

BACH SICHES, Núria. 4D STEM data analysis with KMeans clustering. [consulted: 8 of August of 2026]. Available at: https://hdl.handle.net/2445/215509

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