Fusion Applications Research Articles

Electrical conductivity of warm dense hydrogen from Ohm’s law and time-dependent density functional theory

Abstract Understanding the electrical conductivity of warm dense hydrogen is critical for both fundamental physics and applications in planetary science and inertial confinement fusion. We demonstrate how to calculate the electrical conductivity using the continuum form of Ohm’s law, with the current density obtained from real-time time-dependent density functional theory. This approach simulates the dynamic response of hydrogen under warm dense matter conditions, with temperatures around 30,000 K and mass densities ranging from 0.02 to 0.98 g/cm³. We systematically address finite-size errors in real-time time-dependent density functional theory, demonstrating that our calculations are both numerically feasible and reliable. Our results show good agreement with other approaches, highlighting the effectiveness of this method for modeling electronic transport properties from ambient to extreme conditions.

Maize Hybrids Performance Evaluation with Data Fusion by Matrix Factorization Algorithm

ABSTRACT Crop breeders often face challenges due to limited data availability when making crucial decisions, such as selecting top-performing varieties/hybrids for further experiments, registration, and commercialization. Evaluating all varieties/hybrids across all fields is impractical due to high experimental and time costs, as well as the limited number of locations for planting. This article aims to evaluate the performance of various maize hybrids in untested locations using historical data. The problem is approached through a matrix framework, where hybrids and fields correspond to rows and columns, respectively, with entries representing the yield of a specific hybrid at a given location. As this matrix is typically sparse, the task is to fill in missing data. Agronomists are primarily interested in the performance of top hybrids at specific locations for smart seed selection. To address this, we introduce a novel application of the Data Fusion by Matrix Factorization (DFMF) algorithm for predicting crop yields using maize data from the 2019 Syngenta Crop Challenge. The DFMF results are compared with the Random Forest (RF) algorithm as a benchmark, focusing on model performance for smart seed selection. Our analysis highlights the advantages of the DFMF approach over the traditional RF method in this context.

Full 3D thermal-hydraulic and electric modelling of quench propagation in HTS conductors

Abstract A fully three-dimensional multi-physics model to simulate quench propagation in HTS conductors for fusion applications is presented. It accounts for thermal, electric and fluid dynamics throughout the entire transient. The need for high-fidelity models for quench simulations comes from the bulky layouts of many HTS conductors that are being proposed. The model is then validated against experimental data, showing a good agreement on all the relevant quentities (local voltage and temperatures). It is shown that the detailed model improves the quality of the agreement with the measured data with respect to more simplified models. It also allows an insight on the temperature distributions in the conductor cross-section, which can be relevant for the interpretation of experimental data as well as to support the design of quench detection strategies which rely on local temperature variations.

An intelligence enhancement method for USV navigation visual measurement based on variable gradient soft-threshold correction

Maritime image enhancement is crucial in marine engineering for applications like unmanned surface vessels (USV) visual measurement and path planning. This paper proposes an image enhancement algorithm based on variable gradient soft-threshold correction (VGSC), tailored for USV intelligent navigation. By calculating the gradient of the two-dimensional difference quotient function of the pixels, we determine the pixel distribution and threshold. An innovative dynamic equalization function is applied to compress maximum pixel values and stretch minimum ones, allowing for adaptive adjustment of the threshold. The results indicate that the VGSC algorithm effectively suppresses background noise, thereby facilitating the extraction of target contour pixel information. When evaluated using four image assessment indicators, the VGSC algorithm enhances the image quality by 20.09 % and 28.92 % compared to bilateral filtering and Gamma correction, respectively. This method excels in enhancing image details and suppressing noise, promising robust application in multi-modal data fusion and precise maritime target detection.

A Parametric Study on the L-PBF Process of an AlSi10Mg Alloy for High-Speed Productivity of Automotive Prototype Parts

The AlSi10Mg alloy has garnered significant attention for its application in laser powder bed fusion (L-PBF), due to its lightweight properties and good printability using L-PBF. However, the low production speed of the L-PBF process is the main bottleneck in the industrial commercialization of L-PBF AlSi10Mg alloy parts. Furthermore, while L-PBF AlSi10Mg alloy exhibits excellent mechanical properties, the properties are often over-specified compared to the target properties of parts traditionally fabricated by casting. To accelerate production speed in L-PBF, this study investigated the effects of process parameters on the build rate and mechanical properties of the AlSi10Mg alloy. Guidelines are proposed for high-speed additive manufacturing of the AlSi10Mg alloy for use in automotive parts. The results show a significant increase in the build rate, exceeding the conventional build rate by a factor of 3.6 times or more, while the L-PBF AlSi10Mg alloy met the specifications for automotive prototype parts. This strategy can be expected to offer significant cost advantages while maintaining acceptable mechanical properties of topology-optimized parts used in the automobile industry.

Neighborhood entropy guided by a decision attribute and its applications in multi-source information fusion and attribute selection

The existing methods for information fusion and attribute selection typically require a computationally intensive grid search to determine the optimal parameter. This grid search can significantly impact the efficiency of these processes. To tackle this issue, this paper introduces the concept of neighborhood entropy, which incorporates both the neighborhood and decision classes, and delves into its applications in multi-source information fusion and attribute selection. First, the concept of a δ-neighborhood based on a predefined distance is introduced. Then the neighborhood entropy based on the δ-neighborhood is defined. The optimal parameters for information fusion and attribute selection are determined by minimizing the neighborhood entropy. Furthermore, an information fusion method and an attribute selection algorithm based on the neighborhood entropy, conditional information entropy (CIE), and belief functions are developed. Finally, we demonstrate the effectiveness of our approach through experiments and Wilcoxon tests on 12 datasets, including a large-scale gene dataset. The experimental results show that the optimal parameter determined by the neighborhood entropy aligns with that obtained through grid search and the neighborhood entropy reduces the computational burden of information fusion and attribute selection compared to grid search. When compared to other state-of-the-art algorithms, our approach based on the neighborhood entropy and CIE demonstrates superior classification performance and time efficiency. These findings demonstrate the efficiency and effectiveness of neighborhood entropy and pave the way for applying granular-computing-based information fusion methods to large-scale datasets.

Full van der Waals Ambipolar Ferroelectric Configurable Optical Hetero-Synapses for In-Sensor Computing.

The rapid development of visual neuromorphic hardware can be attributed to their ability to capture, store and process optical signals from the environment. The main limitation of existing visual neuromorphic hardware is that the realization of complex functions is premised on the increase of manufacturing cost, hardware volume and energy consumption. In this study, we demonstrated an optical synaptic device based on a three-terminal van der Waals (vdW) heterojunction that can realize the sensing functions of light wavelength and intensity as well as short-term and long-term synaptic plasticity. In the image recognition task, we constructed an optical reservoir neural network (ORNN) and a visible light communication system (VLC) composed of this optical synaptic device. The ORNN has a recognition rate of up to 84.9% for 50 000 color images in 10 categories in the CIFAR-10 color image dataset, and the VLC system can achieve high-speed transmission with an ultra-low power consumption of only 0.4 nW. This work shows that through reasonable design, vdW heterojunction structures have great application potential in low-power multifunctional fusion application tasks such as visual bionics.

Evaluation of rural tourism development level using BERT-enhanced deep learning model and BP algorithm

To address the insufficient expressive capabilities of traditional methods in assessing the development level of rural tourism, this study explores the fusion application of the Bidirectional Encoder Representations from Transformers (BERT) and the Back Propagation (BP) algorithm to enhance the accuracy and comprehensiveness of rural tourism development assessment. Firstly, this study introduces the BERT deep learning model and its applications in natural language processing, alongside the role of the BP algorithm in pattern recognition and predictive analysis. Subsequently, a framework for assessing rural tourism development levels, integrating BERT and the BP algorithm, is proposed. This framework collects multidimensional rural tourism-related data and utilizes the BERT model for sentiment analysis and topic extraction from textual data. Empirical analysis of rural tourism development in a specific region validates the effectiveness of the proposed approach. Experimental results demonstrate: (1) The model achieves an accuracy of 84.33% and an F1 score of 85.33% on the publicly available Laptop dataset, with a processing time of 20 s, significantly outperforming other methods. Compared to traditional approaches, the proposed method accurately captures correlations between textual information and numerical data, thereby enhancing the credibility and accuracy of assessment results. (2) From the ablation study results, it is evident that removing any component from the model leads to performance degradation. Specifically, removing the Bidirectional Gated Recurrent Unit (BiGRU) reduces accuracy and F1 scores to 78.21% and 76.33% on the Laptop dataset, and to 85.10% and 70.45% on the Tourist_F dataset. Removing Text Convolutional Neural Network (CNN) reduces accuracy and F1 scores to 79.34% and 77.56% on the Laptop dataset, and to 86.25% and 72.11% on the Tourist_F dataset. The most significant performance decline occurs upon removing BERT, with accuracy and F1 scores decreasing to 70.14% and 66.43% on the Laptop dataset, and to 78.45% and 60.33% on the Tourist_F dataset. These results indicate that BiGcRU, TextCNN, and BERT each contribute significantly to the model’s performance. This study provides substantial support for advancing sustainable development in rural tourism, offering significant practical and innovative value.

Theories and Methods for Indoor Positioning Systems: A Comparative Analysis, Challenges, and Prospective Measures.

In the era of the Internet of Things (IoT), the demand for accurate positioning services has become increasingly critical, as location-based services (LBSs) depend on users' location data to deliver contextual functionalities. While the Global Positioning System (GPS) is widely regarded as the standard for outdoor localization due to its reliability and comprehensive coverage, its effectiveness in indoor positioning systems (IPSs) is limited by the inherent complexity of indoor environments. This paper examines the various measurement techniques and technological solutions that address the unique challenges posed by indoor environments. We specifically focus on three key aspects: (i) a comparative analysis of the different wireless technologies proposed for IPSs based on various methodologies, (ii) the challenges of IPSs, and (iii) forward-looking strategies for future research. In particular, we provide an in-depth evaluation of current IPSs, assessing them through multidimensional matrices that capture diverse architectural and design considerations, as well as evaluation metrics established in the literature. We further examine the challenges that impede the widespread deployment of IPSs and highlight the potential risk that these systems may not be recognized with a single, universally accepted standard method, unlike GPS for outdoor localization, which serves as the golden standard for positioning. Moreover, we outline several promising approaches that could address the existing challenges of IPSs. These include the application of transfer learning, feature engineering, data fusion, multisensory technologies, hybrid techniques, and ensemble learning methods, all of which hold the potential to significantly enhance the accuracy and reliability of IPSs. By leveraging these advanced methodologies, we aim to improve the overall performance of IPSs, thus paving the way for more robust and dependable LBSs in indoor environments.

Study of the Pure Deuterium Fuel Burning Rate in Z-Pinch Devices with Magneto-Inertial Confinement

The burning rate of pure deuterium (D-D) fuel in Z-pinch devices with magneto-inertial confinement was studied in this paper. The system of particle and energy balance equations for D-D fuel burning with a mixed D-T-3He fusion cycle (D-D, D-T, and D-3He reactions) was solved numerically, taking into account the densities of all reacted and produced ions (protons, deuterium, tritium, helium-3, and alpha-particles). The obtained results indicate that effective D-D fusion in Z-pinch devices can be successfully achieved under conditions of a hot, dense plasma with an initial temperature of 31 keV or higher. The initial ion density of deuterium and electron density were equal due to quasi-neutrality condition of the plasma, with both reaching 1024 m−3. Although the obtained results show that the burning rate of D-D fuel is approximately 2.3 times slower and its power density notably lower than that of D-T fuel, pure deuterium plasma can be considered as a promising alternative to well-studied deuterium–tritium plasma, with potential future applications in magneto-inertial fusion (MIF) facilities.

From Knowledge Transfer to Capability Development: The Future of PBL + CBL Teaching Method in Operating Room Nursing Education

Concomitant with the advancement of contemporary medical technology, the significance of perioperative nursing has been increasingly accentuated, necessitating elevated standards for the pedagogy of perioperative nursing. Presently, the PBL (problem-based learning) pedagogical approach, when integrated with CBL (case-based learning), has garnered considerable interest. An extensive literature review has been conducted to analyze the application of the PBL-CBL fusion in the education of perioperative nursing. Findings indicate that this integrative teaching methodology not only enhances students’ theoretical knowledge, practical competencies, and collaborative skills but also contributes to the elevation of teaching quality. In conclusion, the PBL-CBL teaching approach holds immense potential for broader application in perioperative nursing education. Nevertheless, it is imperative to continually refine this combined pedagogical strategy to further enhance the caliber of perioperative nursing instruction and to cultivate a greater number of exceptional nursing professionals in the operating room setting.

A novel plasma source concept for negative ion generation in neutral beam injectors for fusion applications

Abstract A low-temperature plasma can very well be confined by a simple magnetic dipole, such as in the Van Allen belts of Earth’s magnetoshpere. This configuration can be reproduced in laboratory as a small experimental device, designed in such a way that the magnetic field lines remain within a vacuum-tight container and are virtually not intercepted by the container wall. In this paper we propose to use a dipole field for the realization of an efficient negative Ion source. To this purpose, we analyze the plasma confinement capabilities of such plasma source, in order to assess the equilibrium pressure and estimate the particle trajectories and drifts.

Thermal properties of MB2-WC (M = Ti, Zr, Hf) and tungsten and their stability after deuterium plasma exposure

The thermal properties of ultra-high temperature ceramics (UHTCs) in the MB2-WC (M = Ti, Zr, Hf) system and tungsten were studied for potential application as plasma-facing materials in fusion power plants. The sintered UHTC and tungsten samples were subjected to deuterium plasma or protons irradiation. Thermal diffusivity was measured using the laser flash method, and superficial thermal conductivity was analyzed through atomic force microscopy. Results showed that the thermal properties did not degrade when exposed to relevant environments and remained stable over a range of temperatures, unlike the reference tungsten material. Thermal conductivity ranged from 61 to 68 W m−1 K−1 for TiB2-2(WC-6Co), from 53 to 63 W m−1 K−1 for ZrB2-6WC, from 67 to 75 W m−1 K−1 for HfB2-6WC, and from 180 to 119 W m−1 K−1 for tungsten across the temperature range from room temperature to 1200 °C. The increasing trend of thermal effusivity, over 19000 J s−0.5 m−2 K−1 at 1200 °C, justifies further testing and of UHTC materials for fusion applications.

Experimental insights on iron-based alloys corrosion in water cooled loops

This paper presents experimental findings on the behavior of iron-based alloys in environmental conditions typical of nuclear fusion technology, specifically focusing on material degradation, which is a critical aspect for the water cooling system of EU DEMO breeding blankets. The experimental campaign investigates potassium hydroxide’s role as an alkalizing agent, testing various concentrations to assess its impact on corrosion resistance. Additionally, it examines how oxygen levels affect localized corrosion development, which is crucial for mitigating corrosion risks in fusion applications. Seven 1000-hour tests were conducted to determine optimal conditions for corrosion reduction. Findings include identifying an oxygen concentration threshold to prevent piping cracking on EUROFER97 specimens.

Intervertebral osteointegration and biomechanical performance of bioactive lithium disilicate glass-ceramic scaffold fabricated by digital light processing

The high strength of lithium disilicate (LD) glass-ceramic makes it difficult to form complex orthopaedic scaffolds using traditional methods. In addition, the osteointegration behavior of LD has also not been well studied in vivo. This study aimed to investigate the procedure of digital light processing (DLP) for fabricating porous LD glass-ceramic scaffolds and to assess the intervertebral osteointegration and biomechanical performance of the scaffolds. The phase formation, fracture morphology, flexural strength and density of LD glass-ceramics fabricated by DLP were evaluated to optimize the manufacturing process. Cell proliferation, cell differentiation and mineralization on the optimized glass-ceramics were recorded for comparison with traditional cast glass-ceramics (CG). The porous LD glass-ceramics scaffold was implanted into rabbits for 7 w and 14 w and then assessed using micro-CT and histological staining. Compression testing was also used to understand the scaffold’s mechanical properties. Furthermore, the scaffold was inserted into a validated finite element model of a human lumbar spine to study the stress distribution during physiological motions. The results indicated that LD glass-ceramics with step-by-step crystallization formed principal phases of Li2Si2O5 and Li3PO4, which had the highest flexural strength. Cell proliferation, cell differentiation and mineralization on the glass-ceramics formed by DLP were similar to the results of glass-ceramics formed by casting. The porous LD glass-ceramic scaffold promoted osseointegration in rabbits and was capable of withstanding physiological loads that would be experienced in a human lumbar spine. In conclusion, the bioactive LD glass-ceramic developed in this study showed good osteogenesis with sufficient mechanical performance, potentially making it suitable for applications in intervertebral fusion.

Quantifying the effects of neutron fluence on proton signal retention in CR-39.

This paper reports on investigations on the impact of higher neutron fluences on the detection efficiency of protons with CR-39, a charged particle track detector. CR-39 is widely used as a diagnostic for inertial fusion applications and is an integral component of numerous particle diagnostics at the OMEGA laser facility and National Ignition Facility. As experiments continue to produce higher and higher yields, existing diagnostics are impacted by higher particle fluences than they were originally designed for. This paper presents data from experiments measuring proton signal on pieces of CR-39 with different levels of neutron fluence with two different etch times. The experiments show a decrease in signal recovery with increased neutron fluence, which is exacerbated at longer etch times. At 3h etch time, data suggest a 17% ± 7% signal loss at 1.3 × 105 neutron-induced tracks per cm2 and a 67% ± 21% loss at 6h etch time. Careful signal isolation techniques can recover most of the proton tracks even with moderate neutron fluence.

Corrosion resistance of HiPIMS tungsten and tungsten-aluminium coatings in contact with liquid Sn

Pure‑tungsten and tungsten-aluminium films deposited by high power impulse magnetron sputtering (HiPIMS) on copper‑chromium‑zirconium substrates were investigated as protective coatings against liquid tin corrosion, a critical issue for nuclear fusion applications. The growth of pure‑tungsten coatings was controlled by using a negative substrate bias synchronized to the HiPIMS pulse onset, resulting in columnar films with various degree of compactness and crystallinity according to the set bias amplitude (0, 400 and 800 V). Differently, the co-sputtering of W and Al favored the formation of an amorphous layer with a compact morphology. During liquid tin corrosion experiments at 400 °C for up to 600 min, all produced coatings were not dissolved, but different protective performances were observed after localized liquid tin interaction. Pure-W coated samples suffered from tin penetration after brittle failure of the protective layer. On the contrary, under the same experimental condition, WAl coatings proved to be effective in limiting liquid tin attack.

Recent progress in the development of liquid metal plasma facing components for magnetic fusion devices

One of the most critical challenges for future fusion reactors is to develop longevity plasma-facing components (PFCs) exposed to extremely high heat and neutron loads. As opposed to those employing solid metals, PFCs with flowing liquid metals (LM) have shown self-healing, heat removal and good impurity control capabilities, all essential to fusion devices. Recently, significant progress in LM-PFC development has been reported globally, with data from several magnetic fusion devices. These studies reveal that LM-PFCs can endure extreme heat fluxes while maintaining plasma compatibility. New design concepts have been proposed and numerically analyzed, advancing models for liquid PFCs in future reactors. Despite existing technical challenges, these developments suggest that LM-PFCs hold promise for future fusion applications.

A thorough experimental assessment of THz-TDS plasma diagnostic techniques for nuclear fusion applications.

In this paper, the study of a plasma diagnostic system based on the THz time domain spectroscopy technique is presented. Such a system could potentially probe a large part of the electromagnetic spectrum currently covered by several other diagnostics in a single measurement. This feature, keeping in mind the basic requirements for plasma diagnostics in nuclear fusion experiments, such as robustness and hard environment applicability, as well as durability and low maintenance, makes the diagnostic of great interest. A conceptual design of the THz-TDS diagnostic has been developed, starting from the well-established classical microwave and far infrared plasma diagnostics landscape. The physical constraints and required instrumental characteristics have been studied and are described in detail here, together with the solutions available for each type of plasma measurement. Specific experimental laboratory tests of the different experimental configurations have been carried out, evaluating the capacity and potential of the novel diagnostic, together with the instrumental constraint, within the diagnostic parameter space.

Characterization of irradiation-induced dislocation loops in Vanadium at 25-500 °C

Vanadium-based alloys have emerged as promising candidates for structural materials in fusion applications. However, as its base metal, the response of V to irradiation has received limited attention in prior studies. To gain a fundamental understanding of the irradiation damage in V, its microstructure evolution under 6 MeV Ti ion irradiation at 25–500 °C is investigated in the present study, with the focus on the detailed and comprehensive characterization of the behavior of the irradiation-introduced dislocation loops. Under room temperature irradiation, the “black dot” dislocation loops agglomerate linearly into rafts, during which their Burgers vectors are well aligned. With the temperature increases to 300 °C, the size of rafts increases and the density decreases, while the size of small loops maintains similar to the room temperature irradiation condition. As the irradiation temperature reaches 500 °C, the defects become highly mobile, resulting in the formation of extended dislocation loops or lines with hundreds of nanometers in size, with the rafts vanishing. All the observable loops under this irradiation temperature range exhibit the Burgers vectors of a/2 < 111>. All the loops observed in the displacement region are identified to be interstitial-type, while a small portion of loops observed in the diffusion region under elevated temperatures are vacancy-type.