Performance Limitations Research Articles

Referral Facilitators & Barriers to OT Services Identified by Oncology Referral Sources: A Qualitative Study

Abstract Date Presented 03/23/24 Individuals living with and beyond cancer are rarely referred to OT despite their occupational performance limitations. This study explored cancer health care professionals’ perspectives on the supports and barriers to OT referral in cancer care. Primary Author and Speaker: Katie M. Polo Additional Authors and Speakers: Khawla Loubani Contributing Authors: Olivia Witteborg, Korrin Schalhamer, Morgan Jones, Cara Murphy Polo, Taylor Brown, Rachel Graves

Mechanically Robust Biopolymer Optical Fibers with Enhanced Performance in the Near-Infrared Region.

Polymer optical fibers (POFs) are lightweight, fatigue-tolerant, and suitable for local area networks, automobiles, aerospace, smart textiles, supercomputers, and servers. However, commercially available POFs are exclusively fabricated using synthetic polymers derived from nonrenewable resources. Recently, attempts have been made to fabricate biocompatible and biopolymeric optical fibers. However, their limitations in mechanical performance, thermal stability, and optical properties foil practical applications in waveguiding. Here, we report a comprehensive study of the preparation of biopolymer optical fibers with tailored mechanical strength, thermal properties, and their short-distance applications. Specifically, we use alginate as one of the key components with methylcelluloses to promote readily scalable wet spinning at ambient conditions to fabricate 21 combinations of composite fibers. The fibers display high maximum strain (up to 58%), Young's modulus (up to 11 GPa), modulus of toughness (up to 63 MJ/m3), and a high strength (up to 195 MPa), depending on the composition and fabrication conditions. The modulus of toughness is comparable to that of glass optical fibers, while the maximum strain is nearly 15 times higher. The mechanically robust fibers with high thermal stability allow rapid humidity, touch sensing, and complex shapes such as serpentine, coil, or twisted structures without losing their light transmission properties. More importantly, the fibers display enhanced optical performance and sensitivity in the near-infrared (NIR) region, making them suitable for advanced biomedical applications. Our work suggests that biobased materials offer innovative solutions to create short-distance optical fibers from fossil fuel-free resources with novel functionalities.

Telemedicine ultrasound in intensive care unit: A pilot diagnostic accuracy study

Introduction: Digital health is an opportune way of facilitating the implementation of point-of-care ultrasound (POCUS) in intensive care units (ICUs) of the Brazilian Unified Health System (SUS) through remote tele-mentored ultrasound (RTMUS). Therefore, this pilot diagnostic accuracy study aims to evaluate the sensitivity and specificity of RTMUS, using POCUS as the gold standard for the diagnosis of pulmonary oedema. As a secondary objective, these metrics will be assessed for pneumonia, chronic obstructive pulmonary disease (COPD), pneumothorax, pulmonary embolism, and cardiac tamponade. Methods: The study was conducted in three adult ICUs, monitored by the TeleUTI project, and included 23 patients who underwent POCUS carried out by an ICU medical professional and RTMUS carried out by a tele-intensivist from the institution that proposed the project. Results: The accuracy in diagnosing pulmonary oedema was 71.43%, COPD 89.96%, and for pneumonia, the results showed an accuracy of 65.22%. Analyses demonstrated that RTMUS has the same capability as POCUS for detecting true positive cases of pulmonary oedema, the same results of true negative cases for COPD, and a limitation in performance for pneumonia. Conclusions: For COPD and pulmonary oedema, remote examination can support healthcare teams, suggesting that RTMUS has the potential to be a substitute for POCUS. We emphasise that the results should be interpreted within the context of the study, which is considered small and should be validated on a larger scale to consolidate the conclusions.

Distinct alterations in probabilistic reversal learning across at-risk mental state, first episode psychosis and persistent schizophrenia

We used a probabilistic reversal learning task to examine prediction error-driven belief updating in three clinical groups with psychosis or psychosis-like symptoms. Study 1 compared people with at-risk mental state and first episode psychosis (FEP) to matched controls. Study 2 compared people diagnosed with treatment-resistant schizophrenia (TRS) to matched controls. The design replicated our previous work showing ketamine-related perturbations in how meta-level confidence maintained behavioural policy. We applied the same computational modelling analysis here, in order to compare the pharmacological model to three groups at different stages of psychosis. Accuracy was reduced in FEP, reflecting increased tendencies to shift strategy following probabilistic errors. The TRS group also showed a greater tendency to shift choice strategies though accuracy levels were not significantly reduced. Applying the previously-used computational modelling approach, we observed that only the TRS group showed altered confidence-based modulation of responding, previously observed under ketamine administration. Overall, our behavioural findings demonstrated resemblance between clinical groups (FEP and TRS) and ketamine in terms of a reduction in stabilisation of responding in a noisy environment. The computational analysis suggested that TRS, but not FEP, replicates ketamine effects but we consider the computational findings preliminary given limitations in performance of the model.

Hybrid dual-mode high-output triboelectric nanogenerator for achieving alternating current/direct current collaborative output

The large-scale practical application of triboelectric nanogenerators (TENGs) mainly depends on the limitations of output performance. On the basis of previous theory, this paper proposes a comprehensive strategy on the coupling of triboelectrification, corona discharge, volume effect, and space volume utilization of charge capture to enhance TENGs’ output. Thereby, a hybrid dual-mode high-output TENG (HDH-TENG) is proposed to efficiently harvest natural mechanical energy through a rotation-driven sliding-TENG (RS-TENG) and a magnetic-driven contact-separation TENG (MC-TENG). The simplified sliding-TENG with the combination of PU foam and vertical-radial electrodes achieves AC/DC collaborative output with charge density of 173.3 and 175.2 µC m−2, respectively. The simplified contact-separation TENG with the PU foam achieves AC output with charge density of 108.8 µC m−2. Furthermore, the integrated RS-TENG and MC-TENG achieve efficient collaborative output of DC with power density of 6.4 W m−2 Hz−1 and AC with power density of 128.6 mW m−2 Hz−1 through persistent directional sliding and contact separation, respectively, where a record-high constant current density output reached 1.9 mA m−2 Hz−1. The HDH-TENG can drive 6575 LEDs and 12 incandescent lamps, and continuously and stably power 52 hygrothermographs. This work further provides a new strategy for charge density enhancement of TENGs.

Experimental investigation on the influence of gasoline injection pressure on the hydrogen knock limit and performance of a hydrogen–gasoline dual fuel engine

This study experimentally investigated the influence of gasoline injection pressure (GIP) on the performance and hydrogen knock limit of a gasoline direct-injection hydrogen–gasoline dual-fuel engine. The GIP was varied from 50 to 140 bar, and hydrogen was introduced at a step size of 2 LPM until knock onset at spark timings of 4° and 12° CA before top dead center (BTDC). The hydrogen knock limit was extended at a higher GIP, with maximum hydrogen flow rates of 10 and 16 LPM at 12° CA and 4° CA BTDC, respectively. Increasing the GIP and retarding the spark timing negatively affected brake thermal efficiency, brake mean effective pressure, and in-cylinder pressure. The CO2 and NOx emissions decreased, and the CO emissions increased with an increase in the GIP. The cyclic variation increased considerably with GIP. However, hydrogen blending exhibited a completely opposite trend to that of GIP.

The probabilistic performance-based seismic assessment of concrete bridge piers with SMASC reinforcing bars: Effect of pulse-like ground motion and vertical load-to-capacity ratio

Concrete bridge piers are critical components of bridge structures and their performance under seismic loading is of utmost importance. Traditional reinforced concrete bridge piers have shown limitations in terms of residual deformations and seismic resilience. This has led researchers to explore alternative reinforcement materials, such as Shape Memory Alloy (SMA) coupled with steel reinforcing bars, which have demonstrated promising attributes like energy dissipation as well as self-centering capacity. This study aims to fill this gap by evaluating the performance of concrete bridge piers with SMA-Steel coupled (SMASC) reinforcing bars under various intensities of vertical gravity loads and the action of pulse-like ground motion components, throughout a probabilistic framework. To this end, a group of bridge piers with different reinforcement types, including pure steel and SMASC are considered. These piers are subjected to 55 near-fault (NF) pulse-like records as well as 32 far-fault (FF) ground motions, throughout the Incremental Dynamic Analysis (IDA). The influence of distinct frequency components is analyzed by decomposing NF records into low-frequency pulses and high-frequency residual components. Also, the role of pulse to the 1st modal period of the piers (Tp/T1) is investigated by evaluating the piers’ response under the action of NF records, which were clustered into four groups. Results were assessed by evaluating the intensity measure and capacity of the studied piers at the desired performance objectives according to the FHWA manual. Moreover, the mean annual frequencies of exceeding performance limit states and the confidence levels of meeting performance objectives are studied. The results of the study indicate that the dominance of the component of NF ground motions depends on factors such as the intensity of gravity loads, ground motion characteristics, and the Tp/T1 ratio. The components of NF records within certain clusters of the Tp/T1 ratio are necessary for accurate response assessment, while FF records can be used for conservative design purposes, depending on the level of ground motion intensity and the intensity of applied gravity load. The SMASC-reinforced piers with specific λ factors (i.e. λ = 0.5 or λ = 1.0) and low intensity of gravity loads lead to a higher (1.6 times higher) mean annual frequency of exceeding a limit state, compared to pure steel rebars. Also, the confidence levels for meeting performance objectives vary depending on the ground motions, but, as gravity load intensity increases, confidence levels decrease, particularly for piers with a λ factor of 0.5.

Benchmarking the Performance of the Actuator-Disk Method for Low-Pressure Axial Flow Fan Simulation

Abstract The actuator-disk method is a cost-effective simulation tool that implicitly represents the rotor of a turbomachine using a blade-element approach combined with two-dimensional (2D) airfoil coefficient input data. Actuator-disk models further rely upon empirical coefficient corrections to modify the 2D input data to better mimic physical blade aerodynamic characteristics. However, the fabrication of high-fidelity, general-purpose corrections remains a formidable challenge, so the limits of actuator-disk model accuracy have never been rigorously tested and remain uncertain. This is especially the case for low-pressure axial flow fan models, given the relative lack of empirical corrections conceived specifically for fan rotor simulation. In this study, benchmark performance limits of the actuator-disk method for axial flow fan analysis are explored. The limits of the modeling approach are interrogated by simulating actuator-disk fan models embedded with accurate physical blade data derived from explicit three-dimensional (3D) fan model computations. It is subsequently shown that even with a near-precise coefficient description, the method remains unreliable. However, using an unconventional actuator-disk model formulation that is based directly on 3D blade force inputs, it is demonstrated that the accuracy of conventional models can be noticeably enhanced if the input coefficient data is artificially manipulated. This nonphysical tuning of the input coefficient data is required to compensate for the simplified flow fields produced by the reduced-order modeling approach. The needed coefficient adjustments, referred to as modeling corrections, are subsequently defined and explained alongside the presentation of new realistic performance targets for future actuator-disk fan model variants.

First experimental evidence of a beam-beam long-range compensation using wires in the Large Hadron Collider

In high intensity and high energy colliders, such as the CERN Large Hadron Collider (LHC) and its future high-luminosity upgrade, interactions between the two beams around the different interaction points impose machine performance limitations. In fact, their effect reduces the beam lifetime, and therefore, the collider’s luminosity reach. Those interactions are called beam-beam long-range (BBLR) interactions, and a possible mitigation of their effect using dc wires was proposed for the first time in the early 2000’s. This solution is currently being studied as an option for enhancing the HL-LHC performance. In 2017 and 2018, four demonstrators of wire compensators have been installed in the LHC. A 2-yearlong experimental campaign followed in order to validate the possibility to mitigate the BBLR interactions in the LHC. During this campaign, a proof-of-concept was completed and motivated an additional set of experiments, successfully demonstrating the mitigation of BBLR interactions effects in beam conditions compatible with the operational configuration. This paper reports in detail the preparation of the experimental campaign, including the corresponding tracking simulations and the obtained results, and draws some perspectives for the future. Published by the American Physical Society 2024

Efficient Deep Model Ensemble Framework for Drug-Target Interaction Prediction.

Accurate prediction of Drug-Target Interactions (DTI) is crucial for drug development. Current state-of-the-art deep learning methods have significantly advanced the field; however, these methods exhibit limitations in predictive performance and the propensity for false negatives. Therefore, we propose EADTN, a simple and efficient ensemble model. We have designed an innovative feature adaptation technique to automatically extract local weights of drugs and targets, and we utilize clustering-enhanced parameter fine-tuning to overcome the issue of false negatives, thereby enhancing its reliability in drug discovery. Based on EADTN, we also propose a Shapley value-based method for identifying key drug substructures, effectively enhancing the model's interpretability. Additionally, we utilized EADTN to reveal potential interactions between NQO1 targets and the drugs SIRT-IN-1 and LY2183240, which were subsequently validated through wet-lab experiments. Experimental evidence demonstrates that EADTN consistently outperforms existing best-performing models across various data sets, promising significant benefits in fields such as drug repositioning.

Solvent Engineering of Thermo-Responsive Hydrogels Facilitates Strong and Large Contractile Actuations.

Thermo-responsive hydrogels can generate the actuation force through volumetric transitions in response to temperature changes. However, their weak mechanical properties and fragile actuation performance limit robust applications. Existing approaches to enhance these properties have typically depended on additional components, leading to an unavoidable interference to the actuation performance. In this work, robust thermo-responsive hydrogels are fabricated through solvent engineering. A particular solvent, N-methylformamide, interacts affinitively with the carbonyl group of N-isopropylacrylamide monomer, solubilizes the monomer with extremely high concentration, stabilizes chain propagation during polymerization, and greatly increases chain lengths and entanglements of the resulting polymer. The synthesized hydrogels are highly elastic, strong, and tough, displaying remarkable thermo-responsive contractile actuation. The simple synthetic process can broaden its applicability in designing robust functional hydrogel applications.

Multi-hazard life-cycle consequence analysis of deteriorating engineering systems

Probabilistic life-cycle consequence (LCCon) analysis (e.g., assessment of repair costs, downtime, or casualties over an asset’s service life) can enable optimal life-cycle management of critical assets under uncertainties. This can lead to effective risk-informed decision-making for future disaster management (i.e., risk mitigation and/or resilience-enhancing strategies/policies) implementation. Nevertheless, despite recent advances in understanding, modeling, and quantifying multiple-hazard (or multi-hazard) interactions, most available LCCon analytical formulations fail to accurately compute the exacerbated consequences which may stem from incomplete or absent repair actions between different interacting hazard events. This paper introduces a discrete-time, discrete-state Markovian framework for efficient multi-hazard LCCon analysis of deteriorating engineering systems (e.g., buildings, infrastructure components) that appropriately accounts for complex interactions between natural hazard events and their effects on a system’s performance. The Markovian assumption is used to model the probability of a system being in any performance level (i.e., limit state) after multiple hazard events inducing either instantaneous and/or gradual deterioration and after potential repair actions through implementing stochastic (transition) matrices. LCCon estimates are then obtained by combining limit state probabilties with suitable system-level consequence models in a computationally efficient manner. The proposed framework is illustrated for two case studies subject to earthquake and flood events as well as environment-induced corrosion during their service life. The first is a reinforced concrete building and the second is a simple transportation road network with a reinforced concrete bridge.

Asymmetric vehicle performance assessment using GG diagrams

In closed-circuit racing such as NASCAR, vehicles often travel on highly-banked oval tracks that are dominated by left-hand corners. The aim of this paper is to study the generation and interpretation of the associated asymmetric GG diagrams and performance metrics. These include GG diagrams on inclined and/or cambered planar road surfaces, and GG diagrams on curved surfaces such as the interior face of an inverted cone. It is shown that a general fixed point on a traditional GG diagram is associated with acceleration or braking along a logarithmic spiral. Under pure acceleration and braking this spiral becomes a straight line, while under constant-speed cornering it becomes a circle. Some of these ideas are developed using a single-track car model. The paper then addresses the calculation and interpretation of GG-diagrams and performance metrics for a Generation 7 (Gen-7) NASCAR on curved road surfaces. The car's stability and performance limits under extreme lateral acceleration conditions are of particular interest. The main results come from a high-fidelity vehicle model and a representative set of parameters.

Cascaded-prism multi-mode beam scanning method for three-dimensional imaging lidar

Light detection and ranging (lidar) has emerged as an indispensable approach to three-dimensional (3D) perception, which probably suffers from performance limitations with traditional beam steering devices. In this paper, we investigate a cascaded-prism beam scanning method to enhance the versatility of 3D imaging lidar systems. The cascaded-prism-based 3D lidar architecture is theoretically developed with an emphasis on a rigorous beam scan model. By exploiting the additional flexibility of cascaded prisms, the lidar can achieve beam scanning through prism rotation in either step-motion or constant-speed mode, which exhibits superior agility and adaptability in multi-mode pattern analysis. Moreover, the cascaded-prism beam scanning lidar is demonstrated with a 3D imaging performance evaluation in terms of field of view, angular resolution and sampling density. It proves that the cascaded-prism beam scanner can offer lidar systems with flexible and configurable 3D imaging capability while balancing between a wide field of view and high angular resolution.

Performance analysis of massive MIMO offshore system with distributed antenna subarrays

In this paper, we propose a transmission scheme of analog precoding for an offshore communication system with distributed antenna subarrays to serve multiple vessels. The proposed analog precoding scheme relies only on line-of-sight (LOS) components of the fading channels, since the accurate estimation of small-scale fading information is challenging due to the varying sea state of maritime wireless channels, such as reflection, scattering, and ducting effect. We derive an approximate expression for the ergodic achievable rate, and emphasize the multiplexing gain analysis of the whole system with a large antenna configuration. In addition, we derive the probability density function (PDF) of signal-to-interference-and-noise ratio (SINR) and further obtain closed-form expressions of symbol error rate (SER). Monte Carlo simulations verify the theoretical analysis, and numerical results demonstrate that the performance of the proposed LOS-based analog precoding scheme for the distributed multiple-input multiple-output (MIMO) offshore system is extremely near to the limitation of system performance, i.e., the ideal situation without any interference.

A-site alkali metal-doped SrTi0.3Fe0.7O3-δ: A highly stable symmetrical electrode material for solid oxide electrochemical cells

To addresses the limitations in electrode performance observed at temperatures ≤700 °C, attributed to the low oxygen surface exchange coefficient primarily caused by high Sr surface segregation, we developed an electrode performance enhancement strategy involving A-site alkali metal doping to SrTi1-xFexO3-δ (STF)-based perovskite. Here, we present the symmetrical electrode material for solid oxide electrochemical cells (SOCs), Sr0.95Mg0.05Ti0.3Fe0.7O3-δ (SMTF), demonstrating a unique combination of excellent symmetrical electrode performance and long-term stability. A-site Mg doping reduces the Sr surface segregation and improves the conductivity but also significantly enhances its electrochemical performance. At 700 °C, the performance of SMTF symmetric cell in both fuel cell and electrolysis modes is 1.5 times higher than that of STF. Moreover, under air atmosphere, SMTF demonstrates stable performance (>1000 h) at 1 A cm−2, with no degradation observed after 400 h testing under humidified hydrogen conditions. Additionally, SMTF exhibits excellent CO2 tolerance in CO2-rich atmospheres.

How strenuous is esports? Perceived physical exertion and physical state during competitive video gaming.

Esports or competitive video gaming is a rapidly growing sector and an integral part of today's (youth) culture. Esports athletes are exposed to a variety of burdens, that can potentially impact an athlete's health and performance. Therefore, it is important that esports athletes are aware of (physical) burden and exertion associated with esports. For this purpose, a study was conducted to evaluate the influence of competitive video gaming on the perceived physical exertion and the perceived physical state (PEPS). Thirty-two healthy male esports athletes participated in two competitive video gaming sessions lasting 90-120 min, interrupted by a 10-minute passive sitting break. Repeated measures of perceived physical exertion (Borg Categorial Ratio-10 scale) and perceived physical state were recorded before, during, and after each video game session. Repeated measures ANOVA and Friedman's test were used for statistical analysis. The results showed a significant difference in all dimensions of the PEPS (p < 0.05) as well as in Borg scale (p < 0.001). Post-hoc tests revealed significant increases in Borg scale between baseline measurements (T0: 1.0 ± 1.0) and after the first competitive video gaming session (T1: 2.4 ± 1.3, p < 0.001), as well as after the second competitive video gaming session (T3: 3.0 ± 1.7, p < 0.001). Furthermore, there was a significant reduction in perceived exertion between the measurement time after the first competitive video gaming session (T1) and the break (T2: 1.3 ± 1.2, p < 0.001). The PEPS dimensions activation, trained, and mobility showed similar significant changes in post-hoc analysis. The results indicate that the perceived physical burden significantly increases during esports participation. As the duration of competitive video gaming extends, the perceived physical state decreases and perceived physical exertion increases. A passive break between two video game sessions can at least partially restore physical exertion and physical state. However, this break neither returns the scores to their baseline levels nor prevents a further decline in scores during the second video game session. Over time and with a lack of observation, this could result in health and performance limitations.

Synthetic-Aperture Radar Radio-Frequency Interference Suppression Based on Regularized Optimization Feature Decomposition Network

Synthetic-aperture radar (SAR) can work in all weather conditions and at all times, and satellite-borne radar has the characteristics of short revisiting period and large imaging width. Therefore, satellite-borne synthetic-aperture radar has been widely deployed, and the SAR images have been widely used in geographic mapping, radar interpretation, ship detection, and other fields. Satellite-borne synthetic-aperture radar is also susceptible to various types of intentional or unintentional interference during the imaging process, and because the interference is a direct wave, its power is much stronger than the wave reflected by targets. As a common interference pattern, radio-frequency interference widely exists in various satellite-borne synthetic-aperture radars, which seriously deteriorates SAR image quality. In order to solve the above problems, this paper proposes a feature decomposition network to suppress interference based on regularization optimization. The contributions of this work are as follows: 1. By analyzing the performance limitations of the existing methods, this work proposes a novel regularization method for radio-frequency interference suppression tasks. From the perspective of data distribution histograms and residual components, the proposed method eliminates the variable components introduced by common regularization, greatly reduces the difficulty of data mapping, and significantly improves its robustness and performance. 2. This work proposes a feature decomposition network, where the feature decomposition module contains two parts; one part only represents the interference signal, and the other part only represents the radar signal. The neurons representing the interference signal are discarded, and the neurons representing the radar signal are used as input for the subsequent network. A cosine similarity constraint is used to separate the interference from the network as much as possible. Finally, this method is validated on the MiniSAR dataset and Sentinel-1A dataset.

Low‐Defect Quantum Dot Lasers Directly Grown on Silicon Exhibiting Low Threshold Current and High Output Power at Elevated Temperatures

The direct growth of III‐V materials on silicon is a key enabler for developing monolithically integrated lasers, offering substantial potential for ultradense photonic integration in vital communications and computing technologies. However, the III‐V/Si lattice and thermal expansion mismatch pose significant hurdles, leading to defects that degrade lasing performance. This study overcomes this challenge, demonstrating InAs/GaAs‐on‐Si lasers that perform on par with top‐tier lasers on native GaAs substrates. This is achieved through a newly developed epitaxial approach comprising a series of rigorously optimized growth strategies. Atomic‐resolution scanning tunneling microscopy and spectroscopy experiments reveal exceptional material quality in the active region and elucidate the impact of each growth strategy on defect dynamics. The optimized III‐V‐on‐silicon ridge‐waveguide lasers demonstrate a continuous‐wave threshold current as low as 6 mA and high‐temperature operation reaching 165 °C. At 80 °C, critical for data center applications, they maintain a 12 mA threshold and 35 mW output power. Furthermore, lasers fabricated on both Si and GaAs substrates using identical processes exhibit virtually identical average threshold current. By eliminating the performance limitations associated with the GaAs/Si mismatch, this study paves the way for robust and high‐density integration of a broad spectrum of critical III‐V photonic technologies into the silicon ecosystem.

Nickel-doped CNTs composite as cathode by sulfur vapor deposition for high-performance all-solid-state lithium‑sulfur batteries

Shuttle effect of polysulfide in the cathode and the safety issues arising from dendrite formation at Li metal anode are the main challenges of traditional liquid lithium‑sulfur batteries. In order to solve the shuttle effect and prevent short circuit, the all-solid-state lithium‑sulfur battery (ASSLSB) is proposed. However, the huge volume expansion of sulfur and the improvement of sulfur conversion efficiency during charge and discharge, which could lead to the limitation of electrochemical performance. Herein, a homogeneous Ni-doped carbon-nanotubes (H-Ni-SVD@CNT) composite cathode of ASSLSB is prepared by sulfur vapor deposition to confine sulfur and promote the conversion of sulfur and Li2S. In this work, SVD-5-S@CNT composite cathode demonstrates high reversible discharge capacity of 1001.1 mAh g−1 after 127 cycles and capacity retention rate of 78.6 % at the rate of 0.1C and 60 °C. Moreover, H-Ni-SVD@CNT composite cathode exhibits superior electrochemical performance, displaying the discharge specific capacity of 1519.3 mAh g−1 at 0.1C and 60 °C. Meanwhile, the discharge specific capacity of H-Ni-SVD@CNT composite cathode is 1060.9 mAh g−1 at room temperature. The synergistic effect of physical confinement and chemical catalysis improves the electrochemical performance of the all-solid-state lithium‑sulfur battery. This work proposes a new strategy for the cathode structure design of the all-solid-state lithium‑sulfur battery.