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n_TOF Collaboration(Tarrio, D. et al), Domingo-Pardo, C., Plag, R., Plompen, A., & Tain, J. L. (2011). High-energy Neutron-induced Fission Cross Sections of Natural Lead and Bismuth-209. J. Korean Phys. Soc., 59(2), 1904–1907.
Abstract: The CERN Neutron Time-Of-Flight (n_TOF) facility is well suited to measure small neutron-induced fission cross sections, as those of subactinides. The cross section ratios of (nat)Pb and (209)Bi relative to (235)U and (238)U were measured using PPAC detectors. The fragment coincidence method allows to unambiguously identify the fission events. The present experiment provides the first results for neutron-induced fission up to 1 GeV for (nat)Pb and (209)Bi. A good agreement with previous experimental data below 200 MeV is shown. The comparison with proton-induced fission indicates that the limiting regime where neutron-induced and proton-induced fission reach equal cross section is close to 1 GeV.
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n_TOF Collaboration(Weiss, C. et al), Domingo-Pardo, C., Tain, J. L., & Tarifeño-Saldivia, A. (2015). The new vertical neutron beam line at the CERN n_TOF facility design and outlook on the performance. Nucl. Instrum. Methods Phys. Res. A, 799, 90–98.
Abstract: At the neutron Lime-of-flight facility n_TOF at CERN a new vertical beam line was constructed in 2014, in order to extend the experimental possibilities at this facility to an even wider range of challenging cross-section measurements of interest in astrophysics, nuclear technology and medical physics. The design of the beam line and the experimental hall was based on FLUKA Monte Carlo simulations, aiming at maximizing the neutron flux, reducing the beam halo and minimizing the background from neutrons interacting with the collimator or back-scattered in the beam dump. The present paper gives an overview on the design of the beam line and the relevant elements and provides an outlook on the expected performance regarding the neutron beam intensity, shape and energy resolution, as well as the neutron and photon backgrounds.
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Perkowski, J. et al, Babiano-Suarez, V., Balibrea-Correa, J., Domingo-Pardo, C., Ladarescu, I., & Lerendegui-Marco, J. (2024). Multi-section fission ionization chamber for measurement of 239Pu(n, γ) reaction in fission tagging method. Nucl. Instrum. Methods Phys. Res. A, 1067, 169649–8pp.
Abstract: The Pu-239(n, gamma) reaction cross section is very important for operation of both thermal and fast reactors, when loaded with MOX fuels. According to the NEA/OECD High Priority Request List the precision of cross section data for this reaction should be improved. The cross section of (n, f) reaction is much higher compared to (n, gamma) for this isotope. In such conditions the fission tagging technique could be applied to identify the fission background. In the past, this technique was successfully used for capture measurements at the nTOF facility at CERN. The multi-section fission ionization chamber was constructed and used in the combination with Total Absorption Calorimeter (TAC) for detecting gamma rays for the precise measurement of Pu-239(n, gamma) reaction cross section at the nTOF facility.
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Zugec, P., Sabate-Gilarte, M., Bacak, M., Vlachoudis, V., Casanovas, A., & Garcia-Infantes, F. (2025). Machine learning based parametrization of the resolution function for the first experimental area of the n_TOF facility at CERN. Nucl. Sci. Tech., 36(12), 235–13pp.
Abstract: This study addresses a challenge of parametrizing a resolution function of a neutron beam from the neutron time of flight facility nTOF at CERN. A difficulty stems from a fact that a resolution function exhibits rather strong variations in shape, over approximately ten orders of magnitude in neutron energy. To avoid a need for a manual identification of the appropriate analytical forms-hindering past attempts at its parametrization-we take advantage of the versatile machine learning techniques. Specifically, we parametrized it by training a multilayer feedforward neural network, relying on a key idea that such network acts as a universal approximator. The proof-of-concept is presented for a resolution function for the first experimental area of the nTOF facility from the third phase of its operation. We propose an optimal network structure for a resolution function in question, which is also expected to be optimal or near-optimal for other experimental areas and for different phases of n_TOF operation. To reconstruct several resolution function forms in common use from a single parametrized form, we provide a practical tool in the form of a specialized C++ class encapsulating the computationally efficient procedures suited to the task.
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