Please use this identifier to cite or link to this item:
https://hdl.handle.net/1889/4291
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Zappettini, Andrea | - |
dc.contributor.author | Sarzi Amadè, Nicola | - |
dc.date.accessioned | 2021-04-22T13:23:31Z | - |
dc.date.available | 2021-04-22T13:23:31Z | - |
dc.date.issued | 2021-04 | - |
dc.identifier.uri | https://hdl.handle.net/1889/4291 | - |
dc.description.abstract | Room Temperature Semiconductor Detectors based on CdZnTe have been widely used in X- and γ-ray spectroscopy in the energy range 10–10000 keV owing to their compactness, high energy resolution and high stopping power. These detectors do not require any cooling which enables their applicability in various fields such as medical imaging, environmental monitoring, astrophysics, decommissioning, nuclear power plants monitoring and homeland security. The related advancements in material science (crystal growth and processing, contact deposition) and technology (low-noise pre-amplifier, signal processing) are undoubtedly consolidated. Nonetheless, the measurements obtained with such devices are still affected by spectral distortions, which are mainly related to partial transfer of the photon energy, incomplete charge collection and excessive noise. Therefore, a straightforward interpretation of experimental data is not always possible. The development of powerful data analysis methods has always accompanied experimental science, and hence also this sector. Nowadays, the extensive knowledge of the physical mechanisms underlying the functioning of CdZnTe- based detectors can be combined with the tremendous progresses of the last decade in data science to push further the performances of these devices. This thesis is focused on the development of algorithms and techniques to correct spectral distortions affecting CdZnTe-based devices and to extract reliable information from measurements. | en_US |
dc.language.iso | Inglese | en_US |
dc.publisher | Università degli Studi di Parma. Dipartimento di Scienze chimiche della vita e della sostenibilità ambientale | en_US |
dc.publisher | Consiglio Nazionale delle Ricerche. Istituto dei Materiali per l’Elettronica e il Magnetismo | en_US |
dc.relation.ispartofseries | Dottorato di ricerca in Scienza e tecnologia dei materiali | en_US |
dc.rights | © Nicola Sarzi Amadè, 2021 | en_US |
dc.rights | Attribuzione - Non commerciale - Non opere derivate 3.0 Italia | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/it/ | * |
dc.subject | Gamma detector | en_US |
dc.subject | Cadmium zinc telluride | en_US |
dc.subject | Room temperature semiconductor detector | en_US |
dc.subject | Machine learning | en_US |
dc.title | Correction of X- and γ-ray spectra acquired by CZT-based detectors | en_US |
dc.type | Doctoral thesis | en_US |
dc.subject.miur | FIS/03 | en_US |
Appears in Collections: | Scienza e tecnologia dei materiali, Tesi di dottorato |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
PhD Report finale.pdf Restricted Access | Relazione finale | 197.58 kB | Adobe PDF | View/Open Request a copy |
Tesi_PhD_Definitiva_pdfa.pdf | Tesi | 30.46 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License