Open Access

This study investigates sulfur spillover, the spontaneous and rapid spread of sulfur over carbon surfaces at ambient temperature. The process is studied by small-angle X-ray scattering (SAXS), X-ray radiography, and microcalorimetry from which a number of physicochemical properties are derived. The results confirm that sulfur immediately interacts with porous carbon upon mixing, with most signal changes occurring within a few hours. For the first time, thermodynamic data of the process are determined. Using microcalorimetry, the lower bound of the reaction enthalpy is determined to be Δsp H = − 28.2 kJ molS8 − 1 . With an estimated reaction entropy of Δsp S = 273.78 J molS8 − 1 K− 1 , the Gibbs Free Energy of the spillover process is estimated as Δsp G = − 100.23 kJ molS8 − 1 , which reduces the theoretical cell voltage of Li-S batteries by about 64 mV. Furthermore, depending on the configuration, DFT calculations have revealed repulsive and attractive interactions; the latter are caused by defects that eventually result in ring opening and the formation of S ─C bonds. This suggests that spillover includes various processes that occur simultaneously. Considering metal-sulfur batteries, sulfur spillover may be critical for preparing and cycling sulfur-carbon composite cathodes, which is demonstrated for a Li–S solid-state battery.

Green hydrogen is poised to be a critical vector in the global energy transition and plays a crucial role in reducing carbon emissions and creating a global clean energy market. However, the economic viability of large-scale green hydrogen production hinges on the optimal design and location. Namibia has an excellent wind and solar energy potential, enabling a feasible, cost-effective green hydrogen production from intermittent renewable energy. This study developed a techno-economic optimization model for cost-effective green hydrogen facilities in Namibia using a single-objective genetic algorithm to determine the optimal wind, solar, and battery storage capacities needed to meet an annual production target of 355,000 tons at Luderitz, Namibia. The model runs on an hourly time-series simulation and uses a discounted cash flow method to minimize the levelized cost of hydrogen for a full year. The results of the optimized system gave a levelized cost of hydrogen of 2.50 USD/kg compared to 7.5 USD/kg obtained from a study on local hydrogen production analysis. This demonstrated the superior performance of the proposed algorithm. A sensitivity analysis was performed on the green hydrogen system, using different numbers of electrolyzers. A range of 150 to 200 units each rated 17.5 MW. Using the proposed algorithm, it was discovered optimal number of Electrolyzers that results in optimal cost of hydrogen is between 196 and 200 units. The findings demonstrated that the levelized cost of hydrogen is not just an average value, as had been demonstrated by various documented publications.

Explosion-related traumatic brain injuries are increasingly recognized as a health risk in a military context. Repetitive low-level blast (LLB) exposure is also of concern, which commonly occurs during training exercises and operational missions using weapon systems or explosives. Although single low-level pressure loads often cause few or no immediate symptoms, repeated exposures are believed to contribute to long-term neurological damage and may increase the risk of developing neurodegenerative diseases later in life. Research in LLB exposure, a complex field, is currently a challenge due to limitations of conventional test setups for generating reproducible shock waves. Specifically, reflections within the test setups and subsequent fluid dynamic effects often result in load cases bearing insufficient resemblance to real detonations. This study presents an acetylene-oxygen-driven shock wave generator which produces shock waves with pressure-time characteristics comparable to real military related LLB-events like such as weapon system muzzles or breaching charges. Measurements at 1.0 m from the relief outlet yielded mean peak overpressures of 85 kPa and 450 m/s shock propagation velocity in the air. To investigate the interaction of the shock wave with a soft tissue, a simplified soft tissue model composed of 17 wt% organic gelatin at 15 °C was used. This generic model provided the internal material sound propagation velocity of human soft tissue of 1542.4 m/s. Embedded piezoelectric pressure sensors determined pressure-time profiles that retained good accordance with idealized characteristics of the external shock wave. The results showed expected overpressure and shock propagation velocity increase to 130 kPa and 1690 m/s upon coupling into the organic gelatin, which has a substantially higher impedance. The results demonstrate that the shock wave generator, combined with the organic gelatin based soft tissue model, provides a controlled, scalable, and high reproducible experimental setup for simulating and analyzing LLB exposures. This experimental approach enables systematic investigation of shock wave propagation in soft tissue and provides a basis for studying injury-related mechanical material responses and evaluating protective technologies. Future applications include controlled exposure of biological models, investigations into the influence of personal protective equipment, and development of mitigation strategies against LLB-induced injuries.

Polymer membranes are critical functional components in proton-exchange membrane water electrolyzers (PEMWEs), where they simultaneously enable ionic transport, separate reactive gases, and Sustain mechanical loads. Despite their central role, membrane failure remains a key limitation for System reliability and safety, driven by the complex interaction of electrochemical reactions, two-phase flow, transport processes, and material degradation due to mechanical, chemical, and thermal loads. In particular, gas-liquid flow regimes in catalyst layers, porous transport layers, and flow channels strongly influence local pressure, temperature, and concentrations at the membrane interface. These impact the membrane’s hydration conditions, inducing heterogeneous swelling, stress concentrations, and Membrane thinning, which accelerates the aging process. This contribution presents a multiphysics modeling framework for the simulation-based investigation of membrane degradation and failure mechanisms in PEMWEs, synthesizing ideas from previous works into a novel integrated modeling approach. Two-phase flow in the adjacent porous and free-flow regions is described using porous-media formulations and phase-field computational fluid dynamics, resolving gas generation, saturation, and pressure fields under different operating conditions. The resulting interface quantities are coupled to a porous-mixture-based finite strain membrane model that accounts for hydration-dependent transport and swelling-induced deformation. Damage or failure indicators are introduced to capture the onset of critical membrane degradation driven by cyclic loading, dehydration, or pressure fluctuations. This modeling concept enables systematic analysis of how operating conditions and flow regimes, including annular or mist-like patterns, contribute to membrane stress and failure risk. The Framework provides a foundation for predictive lifetime assessment and supports the design of more durable and safer electrolyzer systems.

Introduction: Mitral regurgitation (MR) is a common valvular disease associated with complications such as pulmonary hypertension, atrial fibrillation, and heart failure. However, its full impact on the cardiovascular system, especially on right heart function, is not yet fully understood. Understanding this relationship is important because the right ventricle (RV) is critical for maintaining cardiovascular function. Dysfunction of the RV, which may be contributed by conditions like MR, is strongly associated with poor clinical outcomes. Despite its importance, comprehensively studying MR's effect on the RV has been challenging due to the complex, interdependent nature of cardiovascular dynamics, limited patient data, and the difficulty in synthesizing disparate information to clarify the left heart-right heart connection. Methods: The primary goal of this study is to investigate the effects of MR on cardiovascular hemodynamics and RV function by integrating 3D models of the left heart with a closed-loop 0D models of the entire cardiovascular system. We further conduct detailed analyses using patient-specific models to explore how various system modifications impact the RV, providing insights into the nuanced effects of MR on the right heart. Results and Discussion: This analysis provides several clinically relevant insights. First, progressive MR markedly increases RV afterload and predisposes the RV to dysfunction, even when intrinsic RV contractility is preserved or enhanced. Second, MR-specific severity indices and left-heart metrics alone fail to capture the true burden on the right heart; RV impairment can progress despite stable or only modestly changing MR descriptors. Finally, these findings highlight the need to incorporate direct assessment of RV structure and function into the evaluation of MR, as RV vulnerability plays a critical role in determining patient risk and guiding management decisions.