Search Results (370)

Gypsum (CaSO₄·2H₂O) crystallization underpins numerous industrial processes, yet its response to chemical admixtures remains incompletely understood. This study investigates diffusion-controlled crystal growth in a coaxial test tube system to evaluate how three Sika^® ViscoCrete^® superplasticizers—430P, 111P, and 120P—affect nucleation, growth kinetics, morphology, and thermal behavior. The superplasticizers, selected for their surface-active properties, were hypothesized to influence crystallization via interfacial interactions. Ion diffusion was maintained quasi-steadily for 12 weeks, with crystal evolution tracked weekly by macro-photography; scanning electron microscopy and thermogravimetric/differential scanning were performed at the final stage. All admixtures delayed nucleation in a concentration-dependent manner. Lower dosages (0.5–1.0 wt%) yielded platy-to-prismatic morphologies and higher dehydration enthalpies, indicating more ordered lattice formation. In contrast, higher dosages (1.5–2.0 wt%) produced denser, irregular crystals and shifted dehydration to lower temperatures, suggesting structural defects or increased hydration. Among the additives, 120P showed the strongest inhibitory effect, while 111P at 0.5 wt% resulted in the most uniform crystals. These results demonstrate that ViscoCrete^® superplasticizers can modulate gypsum crystallization and thermal properties. Full article

Synthetic nanopores were recently demonstrated with memristive and nonlinear voltage-current behaviors, akin to ion channels in a cell membrane. Such ionic devices are considered a promising candidate for the development of brain-inspired neuromorphic computing techniques. In this work, we show the composite behavior of nanopore-array large memristors, formed with different membrane materials, pore sizes, electrolytes, and device arrangements. Anodic aluminum oxide (AAO) membranes with 5 nm and 20 nm diameter pores and track-etched polycarbonate (PCTE) membranes with 10 nm diameter pores are tested and shown to demonstrate memristive and nonlinear behaviors with approximately 10⁷–10¹⁰ pores in parallel when electrolyte concentration across the membranes is asymmetric. Ion diffusion through the large number of channels induces time-dependent electrolyte asymmetry that drives the system through different memristive states. The behaviors of series composite memristors with different configurations are also presented. In addition to helping understand fluidic devices and circuits for neuromorphic computing, the results also shed light on the development of field-assisted ion-selection-membrane filtration techniques as well as the investigations of large neurons and giant synapses. Further work is needed to de-embed parasitic components of the measurement setup to obtain intrinsic large memristor properties. Full article

The presence of toxic gas emissions from conventional vehicles is worrisome globally. Over the past few years, there has been a broad adoption of electric vehicles (EVs) to reduce energy usage and mitigate environmental emissions. The EVs are characterized by limited range, cost, and short range. This prompts the need for hybrid electric vehicles (HEVs). This study describes the conversion of a 2022 Volkswagen Crafter (VW) 35 TDI 340 delivery van from a conventional diesel powertrain into a hybrid electric vehicle (HEV) augmented with synchronous electrical machines (motor and generator) and a BMW i3 60 Ah battery pack. A downsized 1.5 L diesel engine and an electric motor–generator unit are integrated via a planetary power split device supported by a high-voltage lithium-ion battery. A MATLAB (R2024b) Simulink model of the hybrid system is developed, and its speed tracking PID controller is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) methods. The simulation results show significant efficiency gains: for example, average fuel consumption falls from 9.952 to 7.014 L/100 km (a 29.5% saving) and CO₂ emissions drop from 260.8 to 186.0 g/km (a 74.8 g reduction), while the vehicle range on a 75 L tank grows by ~40.7% (from 785.7 to 1105.5 km). The optimized series–parallel powertrain design significantly improves urban driving economy and reduces emissions without compromising performance. Full article

Background: Pancreatic adenocarcinoma (PAAD) is an aggressive subtype of pancreatic cancer that is estimated to have a 5-year overall survival rate of only 13%. Most patients present with advanced disease with unpredictable outcomes. The identification of prognostic biomarkers is important to accurately stratify these patients. Methods: We investigated the molecular and survival-related role of ENHO in PAAD by analyzing TGCA mRNA and miRNA data. Survival analysis was conducted using TIMER2.0, “survival”, and “survminer”. Gene set enrichment analysis was conducted using enrichr, while miRNA-mRNA interactions were identified using “multiMiR”. Immune infiltration was assessed using CIBERSORT ABS and ImmuCellAI. Results: We observed that ENHO was strikingly downregulated in PAAD tissues (p = 3.68 × 10⁻⁶⁸), and patients with higher ENHO levels enjoyed significantly better overall survival (HR = 0.597; 95% CI: 0.419–0.852; p < 0.01). Pathway analysis showed that genes co-upregulated with ENHO were enriched for insulin secretion and ion channel activity, whereas those co-downregulated were related to epithelial–mesenchymal transition and extracellular matrix remodeling. Higher ENHO also tracked with increased CD8⁺ T-cell infiltration and correlated positively with PDCD1 and LAG3 but negatively with B7-H3, CD70, and NT5E. Conclusions: Our results point to a protective role for ENHO in pancreatic adenocarcinoma. Full article

The Fricke gel dosimeter, a hydrogel-based chemical dosimeter containing dissolved ferrous sulfate, measures 3D radiation dose distributions by oxidizing Fe²⁺ to Fe³⁺ upon irradiation. This study investigates the variation in Fricke yield, G(Fe³⁺), from a radiation–chemical perspective in both standard and gel-like Fricke systems of varying viscosities, under low- and high-linear energy transfer (LET) conditions. We employed our Monte Carlo track chemistry code IONLYS-IRT, using protons of 300 MeV (LET~0.3 keV/µm) and 1 MeV (LET~25 keV/µm) as radiation sources. To assess the impact of viscosity on G(Fe³⁺), we systematically varied the diffusion coefficients of all radiolytic species in the Fricke gel, including Fe²⁺ and Fe³⁺ ions. Increasing gel viscosity reduces Fe³⁺ diffusion and stabilizes spatial dose distributions but also lowers G(Fe³⁺), compromising measurement accuracy and sensitivity—especially under high-LET irradiation. Our results show that an optimal Fricke gel dosimeter must balance these competing factors. Simulations with lower sulfuric acid concentrations (e.g., 0.05 M vs. 0.4 M) further revealed that G(Fe³⁺) values at ~100 s are nearly identical for both low- and high-LET conditions. This study underscores the utility of Monte Carlo simulations in modeling viscosity effects on Fricke gel radiolysis, guiding dosimeter optimization to maximize sensitivity and accuracy while preserving spatial dose distribution integrity. Full article

Thin amorphous oxide films (a-SiO₂, a-Al₂O₃, a-MgO) were prepared by magnetron sputtering deposition. Their response to high-energy heavy ion beams (23 MeV I, 18 MeV Cu, 2.5 MeV Cu) and gamma-ray (1.25 MeV) irradiation was studied by elastic recoil detection analysis and infrared spectroscopy. It was established that their high radiation hardness is due to a high level of disorder, already present in as-prepared samples, so the high-energy heavy ion irradiation cannot change their structure much. In the case of a-SiO₂, this resulted in a completely different response to high-energy heavy ion irradiation found previously in thermally grown a-SiO₂. In the case of a-MgO, only gamma-ray irradiation was found to induce significant changes. Full article

Microdosimetry plays a critical role in particle therapy by quantifying energy deposition within microscopic domains to assess biological effects. This study evaluates the influence of different microdosimetric functions (MFs) and domain geometries (DGs) on relative biological effectiveness (RBE) predictions in carbon ion radiotherapy. Specifically, we compare the analytical microdosimetric function (AMF), calculated for spherical domains and implemented in PHITS, with the Kiefer–Chatterjee (KC) track structure model, which is conventionally applied to cylindrical geometries. To enable a direct comparison, we also introduce a novel implementation of the KC model for spherical domains. Using both models, specific energy distributions were calculated across a range of domain sizes and geometries. These distributions were input into the modified microdosimetric kinetic model (mMKM) to calculate RBE for the HSG cell line and compared against published in vitro data. The results show that both microdosimetric function and domain geometry significantly affect microdosimetric spectra and the resulting RBE, with deviations exceeding 10% when fixed mMKM parameters are used. Parameter optimization within the mMKM enables alignment across models. Our findings emphasize that microdosimetric function and domain geometry selection must be explicitly accounted for in microdosimetry-based RBE modeling, and that model parameters must be tuned accordingly to ensure consistent and biologically accurate predictions. Full article

The Dual Active Bridge converter (DABC), known for its bidirectional power transfer capability and high efficiency, plays a crucial role in various applications, particularly in electric vehicles (EVs), where it facilitates energy storage, battery charging, and grid integration. The Dual Active Bridge Converter (DABC), when paired with a high-performance CLLC filter, is well-regarded for its ability to transfer power bidirectionally with high efficiency, making it valuable across a range of energy applications. While these features make the DABC highly efficient, they also complicate controller design due to nonlinear behavior, fast switching, and sensitivity to component variations. We have used a Fractional-order PID (FOPID) controller to benefit from the simple structure of classical PID controllers with lower complexity and improved flexibility because of additional filtering gains adopted in this method. However, for a FOPID controller to operate effectively under real-time conditions, its parameters must adapt continuously to changes in the system. To achieve this adaptability, a Multi-Agent Reinforcement Learning (MARL) approach is adopted, where each gain of the controller is tuned individually using the Deep Deterministic Policy Gradient (DDPG) algorithm. This structure enhances the controller’s ability to respond to external disturbances with greater robustness and adaptability. Meanwhile, finding the best initial gains in the RL structure can decrease the overall efficiency and tracking performance of the controller. To overcome this issue, Grey Wolf Optimization (GWO) algorithm is proposed to identify the most suitable initial gains for each agent, providing faster adaptation and consistent performance during the training process. The complete approach is tested using a Hardware-in-the-Loop (HIL) platform, where results confirm accurate voltage control and resilient dynamic behavior under practical conditions. In addition, the controller’s performance was validated under a battery management scenario where the DAB converter interacts with a nonlinear lithium-ion battery. The controller successfully regulated the State of Charge (SOC) through automated charging and discharging transitions, demonstrating its real-time adaptability for BMS-integrated EV systems. Consequently, the proposed MARL-FOPID controller reported better disturbance-rejection performance in different working cases compared to other conventional methods. Full article

(1) Background: Generation IV supercritical water-cooled reactors (SCWRs), including small modular reactor (SCW-SMR) variants, are pivotal in nuclear technology. Operating at 300–500 °C and 25 MPa, these reactors require detailed understanding of radiation chemistry and transient species to optimize water chemistry, reduce corrosion, and enhance safety. Boron, widely used as a neutron absorber, plays a significant role in reactor performance and safety. This study focuses on the yields of radiolytic species in subcritical and supercritical water exposed to ⁴He and ⁷Li recoil ions from the ¹⁰B(n,α)⁷Li fission reaction in SCWR/SCW-SMR environments. (2) Methods: We use Monte Carlo track chemistry simulations to calculate yields (G values) of primary radicals (e⁻_aq, H^•, and ^•OH) and molecular species (H₂ and H₂O₂) from water radiolysis by α-particles and Li³⁺ recoils across 1 picosecond to 0.1 millisecond timescales. (3) Results: Simulations show substantially lower radical yields, notably e⁻_aq and ^•OH, alongside higher molecular product yields compared to low linear energy transfer (LET) radiation, underscoring the high-LET nature of ¹⁰B(n,α)⁷Li recoil nuclei. Key changes include elevated G(^•OH) and G(H₂), and a decrease in G(H^•), primarily driven during the homogeneous chemical stage of radiolysis by the reaction H^• + H₂O → ^•OH + H₂. This reaction significantly contributes to H₂ production, potentially reducing the need for added hydrogen in coolant water to mitigate oxidizing species. In supercritical conditions, low G(H₂O₂) suggests that H₂O₂ is unlikely to be a major contributor to material oxidation. (4) Conclusions: The ¹⁰B(n,α)⁷Li reaction’s yield estimates could significantly impact coolant chemistry strategies in SCWRs and SCW-SMRs. Understanding radiolytic behavior in these conditions aids in refining reactor models and coolant chemistry to minimize corrosion and radiolytic damage. Future experiments are needed to validate these predictions. Full article

Riboswitches regulate gene expression through intricate dynamic conformational transitions, with divalent cation Mg²⁺ and their ligands playing pivotal roles in this process. The dynamic structural mechanism by which the S-adenosyl-L-methionine (SAM) responsive SAM-VI riboswitch (riboSAM) regulates the downstream SAM synthase gene translation remains unclear. In this study, we employed position-selective labeling of RNA (PLOR) to incorporate Cy3-Cy5 into designated positions of riboSAM, applying single-molecule Förster resonance energy transfer (smFRET) method to track its conformational switches in response to Mg²⁺ and SAM. smFRET analysis revealed that in the absence of Mg²⁺ and ligand, riboSAM predominantly adopted a translation-activating apo conformation. Physiological concentrations of Mg²⁺ induced riboSAM to fold into dynamic transit-p and holo-p states, creating a transient and structurally pliable binding pocket for ligand binding. SAM binding locks the dynamic transit-p and holo-p states into their final stable transit and holo conformations through conformational selection, turning off downstream cis-gene expression and completing feedback regulation of cellular SAM concentration. The observed synergistic regulatory effect of Mg²⁺ ions and ligand on riboSAM’s conformational dynamics at single-molecule resolution provides new mechanistic insights into gene regulation by diverse riboswitch classes. Full article

An important aspect of lithium-ion batteries related to lifetime and aging is the change in state within the cells, which results from the expansion of the electrode materials and causes internal stress during operation. In this work, fiber optical sensors by means of Bragg gratings are utilized to determine the internal strain in the anode material. The collected data were employed to approximate aging-related changes in anode strain using a combination of established methods, such as the differential voltage and incremental capacity analysis. Moreover, additional methodologies are proposed and explored, substituting electrical data with optical strain measurements to quantify degradation effects linked to changes in strain. During the cycling of the cell, changes in the strain behavior have been observed and can be partially attributed to changes in the cell’s electrochemical composition. The methods suggested have proven effective in providing additional insights into the current state of the cells and tracking changes over time due to detected degradation effects. Full article

In this work, arc ion plating (AIP) was employed to deposit AlCrMoN coatings on cemented carbide substrates, and the effects of substrate bias voltages (−80 V, −100 V, −120 V, and −140 V) on the microstructures, mechanical properties, and tribological behaviors of the coatings were investigated. The results showed that all AlCrMoN coatings exhibited a single-phase face-centered cubic (FCC) structure with columnar crystal growth and excellent adhesion to the substrate. As the negative bias voltage increased, the grain size of the coatings first decreased and then increased, while the hardness and elastic modulus showed a trend of first increasing and then decreasing, with the maximum hardness reaching 36.2 ± 1.33 GPa. Room-temperature ball-on-disk wear tests revealed that all four coatings demonstrated favorable wear resistance. The coating deposited at −100 V exhibited the lowest average friction coefficient of 0.47 ± 0.02 and wear rate ((3.27 ± 0.10) × 10⁻⁸ mm³/(N∙m)), featuring a smooth wear track with minimal oxide debris. During the steady-state wear stage, the dominant wear mechanisms of the AlCrMoN coatings were identified as oxidative wear combined with abrasive wear. Full article

This study presents a comprehensive analysis of the modifications in electronic structure and magnetism resulting from electronic excitation in pulsed laser-deposited Ba_0.7Sr_0.3Fe_xTi_(1−x)O₃ thin films, specifically for compositions with x = 0, 0.1, and 0.2. To investigate the effects of electronic energy loss (S_e) within the lattice, we performed 120 MeV Ag ion irradiation at varying fluences (1 × 10¹² ions/cm² and 5 × 10¹² ions/cm²) and compared the results with those of the pristine sample. The S_e induces lattice damage by generating ion tracks along its trajectory, which subsequently leads to a reduction in peak intensity observed in X-ray diffraction patterns. Atomic force microscopy micrographs indicate that irradiation resulted in a decrease in average grain height, accompanied by a more homogeneous grain distribution. X-ray photoelectron spectroscopy reveals a significant increase in oxygen vacancy (V_O) concentration as ion fluence increases. Ferromagnetism exhibits progressive deterioration with rising irradiation fluence. Due to the high S_e and multiple ion impact processes, cation interstitial defects are highly likely, which may overshadow the influence of V_O in inducing ferromagnetism, thereby contributing to an overall decline in magnetic properties. Furthermore, the elevated S_e potentially disrupts bound magnetic polarons, leading to a degradation of long-range ferromagnetism. Collectively, this investigation elucidates the electronic excitation-induced modulation of ferromagnetism, employing Fe impurity incorporation and irradiation techniques for precise defect engineering. Full article

This study explores the significant effects of charge–discharge cycling on lithium iron phosphate (LiFePO₄)-based electrochemical cells, with a particular focus on the Sinopoly SP-LFP040AHA cell. As lithium-ion batteries undergo repeated charging and discharging cycles, their internal characteristics evolve, influencing performance, efficiency, and longevity. Understanding these changes is crucial for optimizing battery management strategies and ensuring reliable operation across various applications. To analyze these effects, the study utilizes equivalent electrical circuits (EEC) to model the internal behavior of the battery. The individual components of the EEC—such as its resistive, capacitive, and inductive elements—are examined through 3D waveforms, offering a comprehensive visualization of how each parameter responds to cycling. One of the key contributions of this research is the development and implementation of an EEC identification approach that enables a systematic assessment of battery parameter evolution. This technique provides insights into the general trends and variations in electrical behavior based on the state of charge (SoC) of the cell. By analyzing data across a wide range of SoC values—from 0% (fully discharged) to 100% (fully charged)—and tracking changes over 100 charge–discharge cycles, the study highlights the progressive alterations in battery performance. The findings of this investigation offer valuable implications for battery health monitoring, predictive maintenance, and the refinement of state estimation models. Full article

Recent advancements in wearable electronics have significantly enhanced human–device interaction, enabling applications such as continuous health monitoring, advanced diagnostics, and augmented reality. While progress in material science has improved the flexibility, softness, and elasticity of these devices for better skin conformity, their optical properties, particularly transparency, remain relatively unexplored. Transparent wearable electronics offer distinct advantages: they allow for non-invasive health monitoring by enabling a clear view of biological systems and improve aesthetics by minimizing the visual presence of electronics on the skin, thereby increasing user acceptance. Hydrogels have emerged as a key material for transparent wearable electronics due to their high water content, excellent biocompatibility, and tunable mechanical and optical properties. Their inherent softness and stretchability allow intimate, stable contact with dynamic biological surfaces. Furthermore, their ability to support ion-based conductivity is advantageous for bioelectronic interfaces and physiological sensors. Current research is focused on advancing hydrogel design to improve transparency, mechanical resilience, conductivity, and adhesion. The core components of transparent wearable systems include physiological sensors, energy storage devices, actuators, and real-time displays. These must collectively balance efficiency, functionality, and long-term durability. Practical applications span continuous health tracking and medical imaging to next-generation interactive displays. Despite progress, challenges such as material durability, scalable manufacturing, and prolonged usability remain. Addressing these limitations will be crucial for the future development of transparent, functional, and user-friendly wearable electronics. Full article