New technologies are continually advancing, which can make fusion devices less costly and more efficient, thereby strengthening the pathway toward viable nuclear fusion commercialization. In tokamak systems, Central Solenoid (CS) magnet will generate a high-rate magnetic flux change, which induces and heats the toroidal plasma current. We have developed a variety of new materials and technologies to maximize the plasma current drive capability of CS magnet under stringent spatial constraints. A key enabler is the adoption of High-Temperature Superconducting (HTS) Cable-in-Conduit Conductors (CICCs), which support peak magnetic field up to 18.8 T in the CS system. Complementary innovations include the development of specialized materials for structural components, particularly the conductor jacket and tie plate. In particular, the tie plate design has been iteratively optimized in parallel with advances in novel material development, leading to a substantial improvement in the performance of the CS magnet. This work begins with a comprehensive description of the CS magnet’s structural configuration. Next, a high-fidelity 3D global finite element model is constructed to assess the tie plate’s mechanical behavior across three representative operational stages: initial preloading at ambient temperature, thermal contraction during cooldown to 4.2 K, and electromagnetic loading under realistic current waveforms. Simulation outcomes confirm that the tie plate meets all structural design requirements; notably, the use of Incoloy 908 m (a tailored variant of Incoloy 908) is essential. Validation through mechanical testing further confirms that the Incoloy 908 m tie plate delivers the required performance under design-relevant loading conditions.
Reliable cross sections are essential for reactor design, transmutation performance, and nuclear data evaluation, yet significant discrepancies persist among experimental datasets, evaluated libraries, and theoretical models. This work provides a systematic assessment of the fission cross section in the fast-energy range by integrating EXFOR measurements, TALYS-2.0 calculations using five fission barrier formulations, evaluated libraries (ENDF/B-VIII.0 and TENDL-2019), and machine-learning-based predictions. A physically informed feature set including separation energies, deformation parameters, and fission barrier characteristics was used to train six regression models: CatBoost, Gradient Boosting Machine, Random Forest, Support Vector Regression, k-Nearest Neighbours, and XGBoost. GBM delivered the highest predictive accuracy and generalization, closely reproducing the experimental excitation function up to 20 MeV. TALYS results showed strong sensitivity to the barrier model. Comparative analysis demonstrates that advanced machine learning approaches can reduce high energy uncertainties and complement reaction model calculations. The findings highlight the value of data driven methodologies for improving nuclear data related to long-lived minor actinides and for supporting next generation fuel cycle and transmutation applications.
A multi-ray tracing code LHDGauss has been developed to analyze and predict the electron cyclotron resonance (ECRH) deposition profile in the LHD. The original LHDGauss had been developed so that the injected ECRH elliptical Gaussian beam is modeled by multi-ray for O or X mode, and the ray behavior and power deposition profile are calculated for a given density and temperature profile on a given fixed flux surface structure. As the LHD experiment progressed toward higher density, higher injection power, mode conversion/mixing caused by the peripheral density and strong magnetic shear became important. LHDGauss is upgraded to implement this mode conversion/mixing effect precisely. Another upgrade is automating the execution of LHDGauss using plasma parameters and configurations provided by AutoAna system to meet the large and frequent demand of ECRH power deposition profile for the confinement and transport analysis.
Tritium self-sufficiency is one of the central requirements for deuterium-tritium fusion energy. In conventional magnetic-confinement fusion systems, tritium breeding is mainly determined by the composition and geometry of the external breeding blanket, because fusion neutrons traverse the low-density plasma with negligible spectral modification. In laser-driven inertial confinement fusion, however, neutrons are born inside a highly compressed deuterium-tritium fuel assembly and may undergo significant scattering in the dense residual fuel before escaping. Here we establish a quantitative physical link between the fuel areal density, the emergent neutron spectrum, and the effective tritium-production cross section of the ⁶Li(n,α)T reaction. Using high-fidelity Monte Carlo neutron transport calculations, we show that increasing the fuel areal density from 0.3 to 5.0 g/cm² causes pronounced neutron spectral softening through elastic scattering in the compressed deuterium-tritium fuel. The average emergent neutron energy decreases from 13.74 to 8.67 MeV, while the spectrum-averaged ⁶Li(n,α)T cross section increases from 0.030 to 2.071 barn, corresponding to an approximately 69-fold enhancement. These results reveal a strong nonlinear link between microscopic fuel compression and the tritium-breeding potential. The compressed inertial-fusion target therefore acts not only as a fusion-energy source but also as an intrinsic neutron spectral shaper, which may provide a favorable spectral effect for tritium breeding and potentially benefit tritium self-sufficiency in inertial fusion energy systems.
Li4SiO4 (Lithium orthosilicate) is considered one of the most promising tritium breeder materials for next-generation fusion reactors. In reactor system, Li4SiO4 is planned to use in form of ceramic pebbles packed into the breeding blanket. The successful fabrication of these pebbles begins with material synthesis, which necessitates a comprehensive understanding of the reaction kinetics. In the present study, Li4SiO4 was synthesized using Li2CO3 and SiO2 precursor material in a 2:1 molar ratio. The synthesis of Li4SiO4 was carried out at four different temperatures of 773 K, 943 K, 1073 K, and 1173 K using a muffle furnace. The X-ray diffraction patterns confirmed the Li4SiO4 with monoclinic crystal structure at 1173 K. To further investigate the reaction mechanism, thermogravimetric studies were conducted on the mixed raw materials by five different heating rates ranging from 300 to 1173 K. The activation energies for different reaction steps were determined by using FWO, KAS, Friedman, and Vyazovkin method. The reaction model’s evaluation by Malek method indicated the reactions followed D3-diffusion controlled mechanism. Additionally, pre-exponential factors were calculated for multiple step reactions, providing deeper insight into the reaction kinetic behavior.
