Application of TENIS and artificial neural networks in neutron spectroscopy for BNCT beams in IRT-T and TRR: additional research

Application of TENIS and artificial neural networks in neutron spectroscopy for BNCT beams in IRT-T and TRR: additional research

Detalles Bibliográficos
Parent link:European Physical Journal Plus.— .— New York: Springer Science+Business Media LLC.
Vol. 140.— 2025.— Article number 462, 8 p.
Otros Autores: Kazemi Z. Zeinab, Rahmani F. Faezeh, Ghal-Eh N. Nima, Bedenko S. V. Sergey Vladimirovich
Sumario:Title screen
In boron neutron capture therapy (BNCT), it is crucial to accurately measure the neutron energy spectra within the therapeutic range. To achieve this, a variety of instrumentations, both real-time and passive, has been utilized for energy spectrum measurement during or prior to the treatment. However, a significant challenge arises from the abundance of epithermal neutrons in the BNCT neutron energy spectrum, coupled with the narrow therapeutic energy interval. To overcome this challenge, dedicated systems need to be designed to ensure precise measurements. This article focuses on a comprehensive study that explores the feasibility of designing and optimizing a cylindrical multi-moderator neutron spectrometer. Ultimately, this study is able to improve the results of previous efforts by 56.6%. The study utilizes a LiI(Eu) thermal neutron detector, which is based on the thermal beam derived from the beam shaping assembly of the Tehran Research Reactor, which serves as the exclusive neutron source for the BNCT in Iran. Also, the AFITBUNKI code is employed for neutron energy spectrum unfolding
Текстовый файл
AM_Agreement
Lenguaje:inglés
Publicado: 2025
Materias:
электронный ресурс
труды учёных ТПУ
Acceso en línea:https://doi.org/10.1140/epjp/s13360-025-06390-1
Formato: Electrónico Capítulo de libro
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=682924

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