Nuclear Reactions Research Articles

Validity analysis of γ-ray strength function models for radiative capture reactions of heavy nuclei

Accurate simulation of radiative capture reactions (RCRs) requires precise modeling of [Formula: see text]-ray strength functions (GSF). Various GSF models exist but need normalization based on experimental total radiative width (TRW) data. This study found that current normalization methods fail for neutron-induced RCRs in [Formula: see text]U and [Formula: see text]Th nuclei. In this regard, re-normalization values are proposed in order to improve model consistency at low energies. The standard Lorentzian (SLO) model fits experimental data best with minimal normalization.

17O Destruction Rate in Stars

In recent years, several laboratory studies of CNO cycle-related nuclear reactions have been carried out. Nevertheless, extant models of stellar nucleosynthesis still adopt CNO reaction rates reported in old compilations, such as NACRE or CF88. In order to update these rates, we performed new calculations based on a Monte Carlo R-Matrix analysis. In more detail, a method was developed that is based on the collection of all the available data, including recent low-energy measurements obtained by the LUNA collaboration in the reduced background environment of the INFN-LNGS underground laboratory, on R-Matrix cross-section calculations with the AZURE2 code and on uncertainty evaluations with a Monte Carlo analysis. As a first scientific benchmark case, the reactions 17O(p,γ)18F and 17O(p,α)14N were investigated. Among the different stellar scenarios they can influence, the 16O/17O abundance ratio in RGB and AGB stars is the one that can be directly confirmed from spectroscopic measurements. The aim is to reduce the nuclear physics uncertainties, thus providing a useful tool to constrain deep mixing processes eventually taking place in these stars. In this work, we present the procedure we followed to calculate the 17O(p,γ)18F and the 17O(p,α)14N reaction stellar rates and preliminary comparisons with similar rates reported in widely used nuclear physics libraries are discussed.

Erratum to: Catalysis As a Quark-Cumulative Mechanism for Initiating Low-Energy Nuclear Chemical Processes: Phenomenology

Erratum to: Catalysis As a Quark-Cumulative Mechanism for Initiating Low-Energy Nuclear Chemical Processes: Phenomenology

Investigation of the poloidal magnetic flux at the PF-3 plasma focus within the framework of the program of laboratory simulation of astrophysical jets

Astrophysical jets are collimated plasma outflows observed in diverse astrophysical settings covering seven decades of spatial scale and twenty decades of power, which, nevertheless, share many common features. This similarity over wide range of scales indicates a common core of physics underlying this phenomenon, leading to considerable interest in observational, theoretical and numerical studies. Laboratory astrophysics experiments for simulating astrophysical jets are premised on this common core of physics responsible for multi-scale similarity of jets remaining valid down to laboratory spatial scales of millimeters. Jets formed after the disassembly of the non-cylindrical z-pinch formed in a plasma focus installation have recently been subjects of observational studies. They offer an important complementarity to the main lines of investigations in two respects. Firstly, the multi-faceted role of gravity, radiation, nuclear reactions and related astrophysics is eliminated retaining only a rapid implosion of a compact plasma object in a magnetohydrodynamic environment as a common feature. Secondly, observations can be made using techniques of laboratory plasma diagnostics. In this paper, we report preliminary results regarding presence of poloidal magnetic flux associated with the jets lasting long after the pinch disassembly. This is significant in the context of uncertainty regarding the origin of poloidal magnetic field postulated in several MHD models of astrophysical jet phenomena. Evidence indicating presence of a radial component of electric field suggests existence of plasma rotation as well. These results suggest that more refined experiments can provide insights into the astrophysical jetting phenomena not available from observational astronomy techniques.

Analytic continuation of differential cross-sections as a way to determine asymptotic normalization coefficients. Application to the 16O(d,p)17O reaction

Asymptotic normalization coefficients (ANC) are important nuclear characteristics. This paper discusses a method for determining ANC values from experimental data on differential cross-sections of nuclear transfer reactions. The method is based on the use of the analytic continuation of these cross-sections to the pole point of the reaction amplitude with respect to the variable [Formula: see text], where [Formula: see text] is the center-of-mass scattering angle. The method under consideration is used to determine the ANC for the channel [Formula: see text]O(1/2[Formula: see text]; 0.871[Formula: see text]MeV) [Formula: see text]O(0[Formula: see text]; 0[Formula: see text]MeV) [Formula: see text] from the data on the [Formula: see text]O(0[Formula: see text]; 0[Formula: see text]MeV)[Formula: see text]O (1/2[Formula: see text]; 0.871[Formula: see text]MeV) reaction. When determining the ANC, the corrections caused by the Coulomb interaction in the initial, final and intermediate states of the reaction were taken into account. It is shown that these corrections have a great impact on the extracted ANC value.

Machine learning-based new classification for immune infiltration of gliomas.

Glioma is a highly heterogeneous and poorly immunogenic malignant tumor, with limited efficacy of immunotherapy. The characteristics of the immunosuppressive tumor microenvironment (TME) are one of the important factors hindering the effectiveness of immunotherapy. Therefore, this study aims to reveal the immune microenvironment (IME) characteristics of glioma and predict different immune subtypes using machine learning methods, providing guidance for immune therapy in glioma. We first performed unsupervised cluster analysis on the genes and arrays of 693 gliomas in CGGA database and 702 gliomas in TCGA database. Then establish and verify the classification model through Machine Learning (ML). Then, use DAVID to perform functional enrichment analysis for different immune subtypes. Next step, analyze the immune cell distribution, stemness maintenance, mesenchymal phenotype, neuronal phenotype, tumorigenic cytokines, molecular and clinical characteristics of different immune subtypes of gliomas. Firstly, we divide the IME of gliomas in the CGGA database into four different subtypes, namely IM1, IM2, IM3, and IM4; similarly, the IME of gliomas in the TCGA database can also be divided into four different subtypes (IMA, IMB, IMC, and IMD). Next, based on ML, we developed a highly reliable model for predicting different immune subtypes of glioma. Then, we found that Monocytic lineage, Myeloid dendritic cells, NK cells and CD8 T cells had the highest enrichment in the IM1/IMD subtypes. Cytotoxic lymphocytes were highest expressed in the IM4/IMA subtypes. Next step, Enrichment analysis revealed that the IM1-IMD subtypes were mainly closely related to the production and secretion of IL-8 and TNF signaling pathway. The IM2-IMB subtypes were strongly associated with leukocyte activation and NK cell mediated cytotoxicity. The IM3-IMC subtypes were closely related to mitotic nuclear division and mitotic cell cycle process. The IM4-IMA subtypes were strongly associated with Central Nervous System (CNS) development and striated muscle tissue development. Afterwards, Single sample gene set enrichment analysis (ssGSEA) showed that stemness maintenance phenotypes were mainly enriched in the IM4/IMA subtypes; Neuronal phenotypes were closely associated with the IM2/IMB subtypes; and mesenchymal phenotypes and tumorigenic cytokines were highly correlated with the IM2 /IMB subtypes. Finally, we found that compared with patients in the IM2/IMB and IM4/IMA subtypes, the IM1/IMD and IM3/IMC subtypes have the highest proportion of GBM patients, the shortest average overall survival of patients and the lowest proportion of patients with IDH mutation and 1p36/19q13 co-deletion. We developed a highly reliable model for predicting different immune subtypes of glioma by ML. Then, we comprehensively analyzed the immune infiltration, molecular and clinical features of different immune subtypes of gliomas and defined gliomas into four subtypes: immunogenic subtype, adaptive immune resistance subtype, mesenchymal subtype, and immune tolerance subtype, which represent different TMEs and different stages of tumor development.

Measurement of gamma field inside the biological concrete shielding of VVER-1000 Mock-Up at the LR-0 reactor

The long-term operation of existing nuclear power reactors is a crucial concern due to the complexities and expenses associated with replacing key components, such as the reactor pressure vessel and reactor internals. Gamma radiation, a byproduct of nuclear reactions and radioactive decay, significantly influences the lifetime of these components. This radiation is responsible for various degradation pathways leading to void swelling in steel reactor components and cracking or other radiation damage in concrete structures.A study conducted at a full-scale mock-up of the VVER-1000 reactor at the LR-0 zero-power reactor employed HPGe and stilbene measurements to analyze gamma spectra behind the reactor pressure vessel and within concrete biological shielding. While simulations behind the reactor pressure vessel aligned with measurements, notably, amarked overestimation of stilbene spectrum calculations occurred deep in concrete, suggesting potential inaccuracies in radiation predictions for power plant structures.

Ab initio computing of light nuclei structure and nuclear reaction experiment

Ab initio computing of light nuclei structure and nuclear reaction experiment

Sustainable production of radionuclidically pure antimony-119

BackgroundRadiopharmaceutical therapy (RPT) uses radionuclides that decay via one of three therapeutically relevant decay modes (alpha, beta, and internal conversion (IC) / Auger electron (AE) emission) to deliver short range, highly damaging radiation inside of diseased cells, maintaining localized dose distribution and sparing healthy cells. Antimony-119 (119Sb, t1/2 = 38.19 h, EC = 100%) is one such IC/AE emitting radionuclide, previously limited to in silico computational investigation due to barriers in production, chemical separation, and chelation. A theranostic (therapeutic/diagnostic) pair can be formed with 119Sb’s radioisotopic imaging analogue 117Sb (t1/2 = 2.80 h, Eγ = 158.6 keV, Iγ = 85.9%, β+ = 262.4 keV, Iβ+ = 1.81%).ResultsWithin, we report techniques for sustainable and cost-effective production of pre-clinical quality and quantity, radionuclidically pure 119Sb and 117Sb, novel low energy photon measurement techniques for 119Sb activity determination, and physical yields for various tin target isotopic enrichments and thicknesses using (p, n) and (d, n) nuclear reactions. Additionally, we present a two-column separation providing a radioantimony yield of 73.1% ± 6.9% (N = 3) and tin separation factor of (6.8 ± 5.5) x 105 (N = 3). Apparent molar activity measurements for deuteron produced 117Sb using the chelator TREN-CAM were measured at 42.4 ± 25 MBq 117Sb/µmol (1.14 ± 0.68 mCi/µmol), and we recovered enriched 119Sn target material at a recycling efficiency of 80.2% ± 5.5% (N = 6) with losses of 11.6 mg ± 0.8 mg (N = 6) per production.ConclusionWe report significant steps in overcoming barriers in 119Sb production, chemical isolation and purification, enriched target material recycling, and chelation, helping promote accessibility and application of this promising therapeutic radionuclide. We describe a method for 119Sb activity measurement using its low energy gamma (23.87 keV), negating the need for attenuation correction. Finally, we report the largest yet-measured 119Sb production yields using proton and deuteron irradiation of natural and enriched targets and radioisotopic purity > 99.8% at end of purification.

Assessment of Nuclear Fusion Reaction Spontaneity via Engineering Thermodynamics.

This work recalls the basic thermodynamics of chemical processes for introducing the evaluation of the nuclear reactions' spontaneity. The application and definition of the thermodynamic state functions of the nuclear processes have been described by focusing on their contribution to the chemical potential. The variation of the nuclear binding potentials involved in a nuclear reaction affects the chemical potential through a modification of the internal energy and of the other state functions. These energy changes are related to the mass defect between reactants and products of the nuclear reaction and are of the order of magnitude of 1 MeV per particle, about six orders of magnitude larger than those of the chemical reactions. In particular, this work assesses the Gibbs free energy change of the fusion reactions by assuming the Qvalue as the nuclear contribution to the chemical potential and by calculating the entropy through the Sackur-Tetrode expression. Then, the role of the entropy in fusion processes was re-examined by demonstrating the previous spontaneity analyses, which assume a perfect gas of DT atoms in the initial state of the fusion reactions, are conservative and lead to assessing more negative ΔG than in the real case (ionized gas). As a final point, this paper examines the thermodynamic spontaneity of exothermic processes with a negative change of entropy and discusses the different thermodynamic spontaneity exhibited by the DT fusion processes when conducted in a controlled or uncontrolled way.

A critical analysis of the role of artificial intelligence and machine learning in enhancing nuclear waste management

Abstract Controlling and managing nuclear waste is a significant challenge due to the harmful effects of radioactive materials on human health. To address this, long-term storage solutions are essential. Artificial Intelligence (AI) and Machine Learning (ML) are being utilized to make nuclear waste management safer, more effective, and efficient. This paper evaluates various applications of AI and ML in the field of nuclear waste, covering aspects such as predictive maintenance, waste sorting, and classification. AI and ML enhance real-time monitoring of storage conditions and optimize waste handling procedures through advanced data processing capabilities. Implementing cutting-edge solutions is crucial to protect public health and the environment from radioactive waste. The purpose of this evaluation is to examine how AI and ML improve nuclear waste management processes. These technologies can reduce human exposure to harmful materials and increase the safety and efficiency of managing nuclear waste through advanced predictive capabilities. The introduction of AI and ML in nuclear waste management is driving significant changes and innovations, addressing current issues, and establishing new guidelines for future policies.

The triton lifetime from nuclear lattice effective field theory

In this work, we present a calculation of the triton β-decay lifetime using Nuclear Lattice Effective Field Theory (NLEFT) at next-to-next-to-next-to-leading order in the chiral expansion. By incorporating a non-perturbative treatment of the higher-order corrections, we achieve consistent predictions for the Fermi and Gamow-Teller matrix elements, which are crucial for determining the triton lifetime. Our results are consistent with earlier theoretical calculations, confirming the robustness of our approach. This study marks a significant advancement in the systematic application of NLEFT to nuclear β-decay processes, paving the way for future high-precision calculations in more complex nuclear systems. Additionally, we discuss potential improvements to our approach, including the explicit inclusion of two-pion exchange mechanisms and the refinement of three-nucleon forces. These developments are essential for extending the applicability of NLEFT to a broader range of nuclear phenomena, including neutrinoless double-β decay.

Survival probability of Selenium-induced fusion reactions

In this paper, we investigated every potential scenario for selenium-induced heavy ion fusion reactions using astatine isotopes as the target. In this context, we examined [Formula: see text]Se projectiles and [Formula: see text]At targets having longer half-lives of comprising 21 fusion reactions for the synthesis of superheavy element [Formula: see text]. We assessed fusion cross-sections ([Formula: see text]), compound nucleus formation probability ([Formula: see text]), and survival probability ([Formula: see text]) for [Formula: see text]Se projectiles on [Formula: see text]At targets. The evaporation residue cross-sections ([Formula: see text]) is found to be larger for the fusion reaction of [Formula: see text]At of about 14.1[Formula: see text]fb. Hence, these striking results are useful in the synthesis of superheavy element [Formula: see text].

Technical note: Altitude scaling of 36Cl production from Fe

Abstract. Cosmogenic nuclide production rates depend on the excitation functions of the underlying nuclear reactions and the intensity and energy spectrum of the cosmic-ray flux. The cosmic-ray energy spectrum shifts towards lower average energies with decreasing altitude (increasing atmospheric depth), so production rate scaling will differ for production reactions that have different energy sensitivities. Here, we assess the possibility of the unique scaling of 36Cl production from Fe by modeling changes in the 36ClFe/36ClK and 36ClFe/10Beqtz production ratios with altitude. We evaluate model predictions against measured 36Cl concentrations in magnetite and K-feldspar and 10Be concentrations in quartz from granitic rocks exposed across an elevation transect (ca. 1700–4300 ma.s.l.) in western North America. The data are broadly consistent with model predictions. The null hypothesis that 36ClFe/10Beqtz and 36ClFe/36ClK production ratios are invariant with altitude can be rejected at the 90 % confidence level. Thus, reaction-specific scaling factors will likely yield more accurate results than non-reaction-specific scaling factors when scaling 36Cl production in Fe-rich rocks and minerals.

Aptamer-Based Electrochemical Biosensing Platform for Analysis of Cardiac Biomarkers.

Monitoring biomarkers secreted by cardiomyocytes is critical to evaluate anticancer drug-induced myocardial injury (MI). Cardiac troponin I (cTnI) is considered the gold standard biomarker for MI. Herein, an electrochemical aptasensor is engineered for cTnI detection based on lanthanide europium metal-organic frameworks (Eu-MOFs) and a hybridization chain reaction-directed DNAzyme strategy. Three types of Eu-MOF morphologies were easily synthesized by changing the solvent, and the Eu-MOF modulated by mixing the solvent of dimethylformamide and H2O (D-Eu-MOF) exhibited the best performance compared to other morphologies of the Eu-MOFs. Multifunctional nanoprobes were constructed from D-Eu-MOF@Pt loaded with natural horseradish peroxidase and combined with an aptamer-initiated nuclear acid hybridization chain reaction to form G-quadruplex/hemin DNAzymes for signal amplification. A novel capture probe is constructed on the basis of DNA nanotetrahedrons modified on screen-printed gold electrodes to enhance the capture of the target and multifunctional nanoprobes for signal amplification. It exhibits a detection limit of 0.17 pg mL-1 and a linear range from 0.5 pg mL-1 to 15 ng mL-1. The practicality of the platform is evaluated by measuring cTnI in real samples and secreted by cardiomyocytes after drug treatment, which provides great potential in drug-induced MI evaluation for clinical application.

Verification of direct coupling code system using FRENDY version 2 and GENESIS for light water reactor lattices

ABSTRACT This study newly established a direct coupling code system consisting of the nuclear data processing code FRENDY version 2, and the three-dimensional heterogeneous transport code GENESIS (FRENDY-V2/GENESIS) for easy implementation of the random-sampling-based uncertainty quantification considering the implicit effect due to nuclear cross-section (XS) perturbations. The multi-group macroscopic XSs prepared for GENESIS were generated by FRENDY version 2, where the Dancoff factor was calculated by the neutron current method. Then the background XSs were evaluated based on the Carlvik two-term rational approximation. The infinite multiplication factor (k-infinity) and the fission reaction rate distribution in UO2 and MOX lattice geometries were compared with MVP3 to verify the calculation accuracy of FRENDY-V2/GENESIS. The sensitivity analyses on the discretization conditions such as the ray tracing of the method of characteristics were also carried out. Through several comparisons between FRENDY-V2/GENESIS and MVP3, FRENDY-V2/GENESIS with the SHEM 361-group structure calculates the k-infinity within approximately 50 pcm and the fission reaction rate distribution within approximately 0.1% by the root mean square, respectively. Consequently, the applicability of FRENDY-V2/GENESIS was verified, and FRENDY-V2/GENESIS can be used to discuss the implicit effect due to multi-group XS perturbations.

Expression of Myeloperoxidase in Patient-Derived Endothelial Colony-Forming Cells-Associations with Coronary Artery Disease and Mitochondrial Function.

Myeloperoxidase (MPO) plays a critical role in the innate immune response and has been suggested to be a surrogate marker of oxidative stress and inflammation, with elevated levels implicated in cardiovascular diseases, such as atherosclerosis and heart failure, as well as in conditions like rheumatoid arthritis and cancer. While MPO is well-known in leukocytes, its expression and function in human endothelial cells remain unclear. This study investigates MPO expression in patient-derived endothelial colony-forming cells (ECFCs) and its potential association with CAD and mitochondrial function. ECFCs were cultured from the peripheral blood of 93 BioHEART-CT patients. MPO expression and associated functions were examined using qRT-PCR, immunochemistry, flow cytometry, and MPO activity assays. CAD presence was defined using CT coronary angiography (CACS > 0). We report MPO presence in patient-derived ECFCs for the first time. MPO protein expression occurred in 70.7% of samples (n = 41) which had nuclear co-localisation, an atypical observation given its conventional localisation in the granules of neutrophils and monocytes. This suggests potential alternative roles for MPO in nuclear processes. MPO mRNA expression was detected in 66.23% of samples (n = 77). CAD patients had a lower proportion of MPO-positive ECFCs compared to non-CAD controls (57.45% vs. 80%, p = 0.04), a difference that persisted in the statin-naïve sub-cohort (53.85% vs. 84.62%, p = 0.02). Non-CAD patients with MPO expression showed upregulated mitochondrial-antioxidant genes (AIFM2, TXNRD1, CAT, PRDX3, PRDX6). In contrast, CAD patients with MPO gene expression had heightened mROS production and mitochondrial mass and decreased mitochondrial function compared to that of CAD patients without MPO gene expression. MPO is present in the nucleus of ECFCs. In non-CAD ECFCs, MPO expression is linked to upregulated mitochondrial-antioxidant genes, whereas in CAD ECFCs, it is associated with greater mitochondrial dysfunction.

Potential for suprathermal chain reactions in degenerate deuterium plasmas at high densities

Abstract It is argued that fusion chain reactions in the D-D system are feasible with
supra-thermal deuterons in the MeV regime, with new generations of deuterons being
generated either via neutron-deuteron and proton-deuteron collisions, provided that fuel
densities in excess of 1000 gcm −3 are reached. The propagation of supra-thermal deuterons
in an infinite, dense deuterium target was studied using a Monte Carlo method that includes
multiple nuclear reactions, electron and ion stopping, along with neutron and proton
knock-ons. Prior studies into this system are extended and it is shown that : (a)dense
pure deuterium may be more supportive of chain reactions via refinements to the ion-ion
stopping number, (b) such chain reactions can be supported even when the target is electron
degenerate, and (c) the D-T reaction plays a critical role in sustaining these chain reactions.

Low energy nuclear reactions through weak interactions

Low energy nuclear reactions through weak interactions

Simplified efficiency calibration methods for scintillation detectors used in nuclear remediation

Our study introduces innovative methods to address waste reduction and enhance resource efficiency in nuclear cleanup processes. We focus on sustainable nuclear technology, aligning with goals for cleaner production and environmental protection. We developed two novel methods, termed “oversimplified” and “simplified,” for easily determining the photopeak efficiency of NaI(Tl) scintillation detectors. These methods, along with a “general” solution method, were validated with calibrated radioactive sources such as 241Am, 57Co, 133Ba, 137Cs, and 60Co, and were used to commission a NaI(Tl) scintillation detector system at Chalk River Laboratories (CRL) for nuclear remediation. The system demonstrated high accuracy, making it suitable for screening unstable isotopes at contaminated sites. This screening tool significantly reduces the number of soil samples requiring detailed characterization, thereby lowering operational costs. The NaI(Tl) detector system was calibrated for near-contact geometry, which is commonly used at CRLs. Detection limits were established for this configuration. By improving the efficiency calibration of scintillation detectors, our study advances sustainable nuclear remediation practices, promoting environmental sustainability and cleaner production processes.