Deep neural network predictions for excitation functions of 165Ho(α,xn) reactions.

HEGM: Hierarchical Ensemble Generation Model for nuclear reaction cross sections generation.

In this study; discusses the using artificial neural networks for approximation of data such as the nuclear reaction cross sections data. The rate of approximation of the fitting criteria is determined by using the experimental and evaluated data. The some reactions cross-section are calculated from data obtained using neural networks. The results show the effectiveness and applicability of this new technique in the calculation of the some nuclear reactions.

Earlier works, including a recent one at BNL, demonstrated that positron emission tomography (PET) is a potentially powerful tool for quality assurance and the treatment planning of Proton Therapy (PT). In particular, the PET images show the adequacy of the overlapping of the dose distribution with the intended target volume. Here, we present calculations of the possible variations in yields of positron emitters produced by proton beams of 250 MeV in a soft tissue, and combine the results with the Monte Carlo simulations of PET data collection from our recent work to show the effect of input data variations on the images. We demonstrate that the image results depend strongly on the available nuclear reaction cross section data.. The emphasis of this work is on determining, quantitatively, the differences in the calculated PET image yields resulting from four different sets of input nuclear reaction cross section data.

Earlier works, including a recent one at BNL, demonstrated that PET is a promising technique to verify the dose distribution of proton therapy, which is increasingly used in radiation oncology because the dose conforms more tightly to the tumor than common x-ray radiation therapy. Proton therapy produces positron-emitting isotopes along the beam path, allowing the therapy dose distribution to be imaged by PET as a form of quality assurance of the treatment. This is especially important when treating inhomogeneous organs such as the lungs or the head-and-neck, where the calculation of the expected dose distribution for treatment planning is more difficult. In this paper, we present Monte Carlo simulations of the yield of positron emitters produced by proton beams up to 250 MeV, followed by statistically realistic Monte Carlo simulation of the images expected from a clinical PET scanner. The emphasis of this study is to accurately predict the positron emitter distribution and to determine the quality of the PET signal in the region near the Bragg peak which is critical to the success of PET imaging for verification of proton beam location and dosimetry. In this paper, we also demonstrate that the image results depend strongly on the available nuclear reaction cross section data. We determine quantitatively the differences in the calculated positron emitter yields resulting from four different sets of input nuclear reaction cross section data. They are compared to the simulated distributions of positron emitter productions and absorbed proton energies.

A vast knowledge of nuclear data is available and is grouped under three headings, namely, nuclear structure, nuclear decay and nuclear reaction data. Still newer aspects are under continuous investigation. Data measurements are done using a large number of techniques, including the radiochemical method, which has been extensively worked out at Julich. This method entails preparation of high-quality sample for irradiation, isolation of the desired radioactive product from the strong matrix activity, and preparation of thin source suitable for accurate measurement of the radioactivity. It is especially useful for fundamental studies on light complex particle emission reactions and formation of low-lying isomeric states, both of which are rather difficult to describe by nuclear model calculations. The neutron induced reaction cross section data are of practical application in fusion reactor technology, particularly for calculations on tritium breeding, gas production in structural materials and activation of reactor components. The charged particle induced reaction cross section data, on the other hand, are of significance in medicine, especially for developing new production routes of novel positron emitters and therapeutic radionuclides at a cyclotron. Both neutron and charged particle data also find application in radiation therapy. A brief overview of advances made in all those areas is given, with major emphasis on nuclear reaction cross section data.

Radiochemical diagnostic signatures are well known to be effective indicators of nuclear ignition and burn reaction conditions. Nuclear activation is already a reliable technique to measure yield. More comprehensively, though, important quantities such as fuel areal density and ion temperature might be separately and more precisely monitored by a judicious choice of select nuclear reactions. This report details an initial assessment of this approach to diagnosing ignition failures on point-design cryogenic National Ignition Campaign targets. Using newly generated nuclear reaction cross section data for Scandium and Iridium, modest uniform doping of the innermost ablator region provides clearly observable reaction product differences between robust burn and failure for either element. Both equatorial and polar tracer loading yield observable, but indistinguishable, signatures for either choice of element for the preliminary cases studied.

The International Network of Nuclear Reaction Data Centres (NRDC) constitutes a worldwide cooperation of 14 nuclear data centres. The main activity of the NRDC Network is collection and compilation of experimental nuclear reaction cross section data and the related bibliographic information in the EXFOR and CINDA databases as well as dissemination of nuclear reaction data and associated documentation to users. The database contains information and numerical data from more than about 19000 experiments consisting of more than 140000 datasets. EXFOR is kept up to date by constantly adding newly published experimental information. Tools developed for data dissemination utilise modern database technologies with fast online capabilities over the Internet. Users are provided with sophisticated search options, a user-friendly retrieval interface for downloading data in different formats, and additional output options such as improved data plotting capabilities. The present status of the EXFOR database will be presented together with the latest development for data access and retrieval.

Interpretable deep learning unlocks high-fidelity prediction for medical radioisotope production.

Using artificial neural networks for an estimation of the nuclear reaction cross section data is discussed. Approximately rate of the fitting criteria is determined by the calculated experimental data obtained from using Variable Learning Rate Backpropagation (traingdx) algorithm in artificial neural networks. This method has been applied to obtain the cross section for 14–15 MeV neutron-induced (n,α) and (n,p) reactions in the fusion reactor structural materials. In comparison to the reaction cross section calculation by experimental cross sections reported in EXFOR, TALYS 1.9 and EMPIRE 3.2, the proposed method has better prediction ability when the target output has a large variation between the experimental and the calculated data. This study is substantial for the new method validation development of the nuclear model approaches with the increased prediction power of the neutron-induced reactions for fusion reactor systems.

The types of nuclear data and their quality required in the production and application of diagnostic radionuclides are outlined. The radioactive decay data determine the suitability of a radioisotope forin vivotracer studies, both from the imaging and internal radiation dose considerations. The nuclear reaction cross section data allow optimisation of production routes. Both reactors and cyclotrons are used for production purposes. The nuclear data needed in the two cases and their present status are discussed. Special attention is paid to radionuclides suitable for emission tomography (PET and SPECT). The controversy aboutreactorvscyclotronproduction of the widely used99Mo/99mTc generator system is discussed. Some special considerations in cyclotron production of radionuclides are outlined. The need of accurate data near reaction thresholds, the constraint of available particles and their energies at a small cyclotron, the influence of increasing incident particle energy, and the formation of isomeric impurities are discussed in detail. The role of nuclear model calculations in predicting unknown data is considered.

A brief introduction to nuclear data in medicine is given. The choice of a radioisotope for medical application demands an accurate knowledge of radioactive decay data. Short-lived single photon and β+-emitters are preferred for diagnostic investigations, and longer-lived corpuscular radiation emitting radioisotopes for endoradiotherapy. The nuclear reaction cross section data, on the other hand, are needed for optimising the production routes. Besides radioactive isotopes, the use of ionising radiation in therapy is discussed. External radiation therapy has achieved an important place in medicine. The role of nuclear data is briefly discussed; they are needed for radiation dose calculations. The hitherto rather neglected activation products in proton therapy are considered. The methodology of development of a nuclear data file for medical applications is outlined

Many studies have shown that the nuclear reactions of charged particles with nuclei are very important in many fields of nuclear physics. The interactions of deuterons with nuclei have been especially the subject of common research in the history of nuclear physics. Moreover, the knowledge of cross section for deuteron-nucleus interactions are required for various application such as space applications, accelerator driven sub-critical systems, nuclear medicine, nuclear fission reactors and controlled thermonuclear fusion reactors. Particularly, the future of controlled thermonuclear fusion reactors is largely dependent on the nuclear reaction cross section data and the selection of structural fusion materials. Finally, the reaction cross section data of deuteron induced reactions on fusion structural materials are of great importance for development and design of both experimental and commercial fusion devices. In this work, reaction model calculations of the cross sections of deuteron induced reactions on structural fusion materials such as Al (Aluminium), Ti (Titanium), Cu (Copper), Ni (Nickel), Co (Cobalt), Fe (Iron), Zr (Zirconium), Hf (Hafnium) and Ta (Tantalum) have been investigated. The new calculations on the excitation functions of 27Al(d,2p)27Mg, 47Ti(d,2p)47Sc, 65Cu(d,2p)65Ni, 58Ni(d,2p)58Co, 59Co(d,2p)59Fe, 58Fe(d,p)59Fe, 96Zr(d,p)97Zr, 180Hf (d,p)181Hf and 181Ta(d,p)182Ta have been carried out for incident deuteron energies up to 50 MeV. In these calculations, the equilibrium and pre-equilibrium effects for (d,p) and (d,2p) reactions have been investigated. The equilibrium effects are calculated according to the Weisskopf-Ewing (WE) Model. The pre-equilibrium calculations involve the new evaluated the Geometry Dependent Hybrid Model (GDH) and Hybrid Model. In the calculations the program code ALICE/ASH was used. The calculated results are discussed and compared with the experimental data taken from the literature.

Neutron-induced nuclear reaction cross section data on dysprosium (Dy) target material are needed for the development and design of reactors, because of using Dy such as an absorbing material for the control rods in reactors. Furthermore, these data are important in terms of improving the definition of neutron–particle interaction. In this framework, the excitation functions of 156,158,160–164Dy(n, p)156,158,160–164Tb reactions were theoretically calculated using TALYS 1.8 and EMPIRE 3.2 Malta nuclear reaction codes. In addition, effects of different level density models on the reaction cross sections were also investigated. Therefore, the obtained theoretical cross sections are compared with the experimental cross sections found in the literature. Besides, (n, p) cross section systematics, which was proposed in our previous article and in the literature, has been used for obtaining the reaction cross sections at energies of around 14 MeV.

Nuclear data are important for production and medical application of a radionuclide. This brief review concentrates on nuclear reaction cross-section data. The availability of standardized nuclear data for accelerator-based production of medical radionuclides is outlined. Some new directions in radionuclide applications, for example, theranostic approach, bimodal imaging, and radionuclide targeted therapy, are considered and the status of relevant nuclear data is discussed. The current trends in nuclear data research using accelerators are elaborated. The increasing significance of intermediate energy accelerators in production of therapeutic radionuclides is emphasized.

The standardisation of nuclear reaction cross section data is an integral part of optimisation of production routes of medical radionuclides. The production cross sections are available for the reactor and cyclotron produced radionuclides to be used for diagnostics or therapeutic procedures. The types of nuclear data needed, and the sources of their availability are summarized. The method of standardisation of charged-particle data is briefly described. A historical overview of research work in Pakistan in this direction is given. Examples of a few medically important radionuclides, such as 64Cu, 86Y, 89Zr, 103Pd, 186Re, etc., whose data were standardised and evaluated are highlighted. Calculated thick target yields from the recommended data are given. Some new directions in the nuclear data research are outlined.