Search Results (579)

Developing molecular electrocatalysts with controllable and predictable properties remains a central challenge in hydrogen evolution reaction (HER) catalysis. Herein, four Sb(III) corrole complexes (1–4) bearing zero to three p-cyano-substituted meso-phenyl groups (-CN Ph) were synthesized to investigate the effect of electron-withdrawing substituents on their catalytic HER performance, in which complexes 2–4 are newly reported. All prepared complexes were well characterized via UV–vis, NMR, HRMS, and XPS. SEM–EDS and UV–vis analyses indicated their uniform dispersion and excellent stability under organic and neutral aqueous solvent electrolysis conditions. When using TsOH as the proton source in DMF, complex 4 exhibited the highest activity with a TOF of 42.19 s⁻¹ at an overpotential of 895 mV. In mixed aqueous–organic media, the Faradaic efficiency of complex 4 reached 85.5%. The HER activity increases with the increasing number of cyano groups, and this observation has been rationalized via DFT calculations, which indicates a ligand-centered reduction and supports a possible ECEC pathway for the HER. These results highlight that cyano functionalization can modulate the electronic properties of Sb(III) corroles, thereby enhancing HER performance. This is helpful for designing efficient Sb(III) corrole-based HER catalysts. Full article

As the global energy transition accelerates toward low-emission and sustainable industrial energy systems, green hydrogen produced from renewable sources has emerged as a promising alternative to natural gas in energy-intensive sectors. This study presents the design, implementation, and experimental validation of a rooftop photovoltaic–proton exchange membrane (PV–PEM) hydrogen energy system developed as a proof-of-concept for textile industry applications. The proposed system integrates monocrystalline photovoltaic panels with east–west solar tracking, a 4 kW inverter, and a PEM electrolyzer with a hydrogen production capacity of 3.6 L/h, enabling on-site solar-to-hydrogen conversion. Produced hydrogen is stored in a high-pressure metal tank and utilized for downstream energy applications, demonstrating a complete renewable energy pathway. System performance is monitored in real time and evaluated using an experimental methodology supported by GUM-based and Monte Carlo uncertainty analysis. A carbon reduction assessment is conducted under representative industrial operating scenarios, including uncertainty quantification. The results indicate that the prototype system achieves an energy output corresponding to an average monthly emission reduction of approximately 222 kg CO₂e. The modular and scalable architecture allows flexible expansion to support gradual natural gas substitution in textile processes such as drying, heating, and steam generation. Overall, the study demonstrates the technical feasibility and environmental potential of integrating rooftop PV–PEM hydrogen systems into textile manufacturing, providing a transferable framework for industrial decarbonization. Full article

Proton exchange membrane fuel cells (PEMFCs) are attractive energy sources for clean and efficient power generation; however, their nonlinear characteristics and sensitivity to operating condition variations make maximum power point tracking (MPPT) a challenging control problem. Conventional MPPT techniques often exhibit slow convergence, steady-state oscillations, and degraded performance under dynamic fuel flow variations. This paper proposes a machine learning–driven MPPT control strategy for a PEMFC system integrated with a DC–DC boost converter. The MPPT problem is formulated as a supervised classification task, where machine learning classifiers generate duty-cycle commands to regulate the converter and ensure operation at the maximum power point. A detailed PEMFC–converter model is developed in MATLAB/Simulink-2025b, and a dataset of 3000 labeled samples is generated under varying fuel flow conditions. Several classification algorithms, including decision trees, support vector machines (SVM), k-nearest neighbors (kNN), and ensemble learning methods, are systematically evaluated within an identical simulation framework. Simulation results show that the proposed machine learning-based MPPT controller significantly improves dynamic and steady-state performance. Ensemble Boosted Trees achieve the best overall response with a settling time of approximately 32 ms, peak power overshoot below 4.5%, and steady-state power ripple limited to 1.5%. Quadratic SVM and weighted kNN classifiers also demonstrate stable tracking behavior with power ripple below 2.1%, while overly complex models such as Cubic SVM suffer from large oscillations and reduced accuracy. These results confirm that classification-based machine learning offers an effective, fast, and robust MPPT solution for PEMFC systems under dynamic operating conditions. Full article

For those who did not follow the invention and development of enantioselective catalysis, this review introduces pertinent historical aspects of the field and presents the scientific concepts of asymmetric bio- and organocatalysis. They are powerful technologies applied in organic laboratories and industry. They realize chiral amplification by converting inexpensive achiral substrates and reagents into enantiomerically enriched products using readily recoverable solvents, if any are used. Racemic substrates can also be deracemized catalytically. More sustainable fabrications are now available that require neither toxic metallic species nor costly reaction conditions in terms of energy, atmosphere control, product purification, and safety. Nature has been the source of the first asymmetric catalysts (microorganisms, enzymes, alkaloids, amino acids, peptides, terpenoids, sugars, and their derivatives). They act as temporary chiral auxiliaries and lower the activation free energy of the reaction by altering the reaction mechanism. Reductions, oxidations, carbon-carbon and carbon-heteroatom bond-forming reactions are part of the process panoply. Asymmetric catalyzed multicomponent and domino reactions are becoming common. Typical modes of activation are proton transfers, hydrogen bonded complex formation, charged or uncharged acid/base pairing (e.g., σ-hole catalysts), formation of equilibria between achiral aldehydes and ketones with their chiral iminium salt or/and enamine intermediates, umpolung of aldehydes and ketones by reaction with N-heterocyclic carbenes (NHCs), phase transfer catalysis (PTC), etc. Often, the best enantioselectivities are observed with polyfunctional catalysts derived from natural compounds, but not always. They may combine to form chiral structures containing nitrogen, phosphorus, sulfur, selenium, and iodine functional moieties. Today, man-made enantiomerically enriched catalysts, if not enantiomerically pure, are available in both enantiomeric forms. Being robust, they are recovered and reused readily. Full article

Background: Proton pump inhibitors (PPIs) are commonly used to manage acid-related gastrointestinal conditions. Nevertheless, growing attention has been paid to their long-term safety, especially their possible link to dementia and Alzheimer’s disease (AD). Prior research has yielded inconsistent findings, underscoring the need for a comprehensive and current evaluation. Methods: A systematic search was conducted across PubMed, Embase (Ovid), and the Cochrane Library to identify relevant publications up to May 28, 2025, without language restrictions. Two investigators independently extracted study information and evaluated methodological quality as well as potential sources of bias. Eligible studies were observational in design and investigated the association between proton pump inhibitor (PPI) exposure and the risk of developing dementia compared with non-use. For the quantitative synthesis, pooled risk ratios (RRs) and corresponding confidence intervals were generated using a random-effects approach. Study Results: Eighteen studies, encompassing more than 6.3 million participants, met the inclusion criteria. The pooled estimate showed no statistically significant association between PPI use and overall dementia risk (RR = 1.14, 95% CI 0.98–1.33; I² = 99%). However, significant heterogeneity and variable risk of bias—particularly due to confounding, exposure misclassification, and immortal time bias—limit certainty in these findings. Subgroup analyses revealed significantly elevated risks among individuals aged ≥65 years (RR = 1.21, 95% CI 1.01–1.46) and in studies from Asia (RR = 1.31, 95% CI 1.12–1.52) and Europe (RR = 1.32, 95% CI 1.10–1.59), suggesting possible population- or context-specific vulnerability. Conclusions: Our findings reveal a lack of consistent evidence supporting a link between PPI use and dementia risk, primarily due to significant heterogeneity among existing studies. While no robust overall association was demonstrated, significant subgroup signals in older adults and specific regions suggest that clinical uncertainty remains. Rather than indicating a direct causal risk, these results underscore the importance of prescribing stewardship. Clinicians should focus on appropriate prescribing, ensuring long-term PPI therapy is reserved for patients with a clear therapeutic justification and utilized for the shortest effective duration. Full article

Background/Objectives: First row transition metal ions have recently regained attention in coordination chemistry as alternatives to gadolinium-based paramagnetic contrast agents, motivated by emerging safety concerns associated with certain Gd³⁺-based contrast agents. In this study, we report the development of a novel homoleptic diketonate Fe³⁺ complex functionalized with biocompatible indole moieties. We investigate its potential as a paramagnetic relaxation agent by evaluating its ability to modulate the T₁ and T₂ relaxation times of water proton. Methods: Iron(III) tris-1,3-(1-methylindol-3-yl)propanedionate [Fe(BIP)₃] was synthesized via a thermal method from bis(1-methylindol-3-yl)-1,3-propanedione (HBIP) using Fe(ClO₄)₃∙6 H₂O as the metal source. The complex was characterized by UV-Vis, IR and NMR spectroscopy, differential scanning calorimetry–thermogravimetric analysis, and single-crystal X-ray diffraction. Fe(BIP)₃ aggregation behavior in aqueous environment, including size and morphology of aggregates, was investigated using dynamic light scattering and scanning electron microscopy. Incorporation of the aggregates into phospholipid vesicles was evaluated by fluorescence resonance energy transfer and fluorescence correlation spectroscopy. The paramagnetic properties of monomeric Fe(BIP)₃ were probed in solution by nuclear magnetic resonance recurring to the Evans bulk magnetization method. Results: The designed synthetic procedure successfully afforded Fe(BIP)₃, which was fully characterized by UV-Vis and IR spectroscopy, as well as single-crystal X-ray diffraction. Aqueous solutions of Fe(BIP)₃ spontaneously formed rice-grain-shaped nanoscale aggregates of hydrodynamic radius ≈ 30 nm. Incorporation of these aggregates into phospholipid vesicles enhanced their stability. The longitudinal r₁ and transverse r₂ relaxivities of Fe(BIP)₃ aggregates were assessed to be 1.92 and 52.3 mM⁻¹s⁻¹, respectively, revealing their potential as paramagnetic relaxation agents. Conclusions: Fe(BIP)₃ aggregates, stabilized through incorporation into phospholipid vesicles, demonstrate promising potential as novel paramagnetic relaxation agents in aqueous environments. Full article

The aim of this paper is to present a more complete analysis of the theoretical concepts and experimental aspects of the physics of photoproduction interactions involving nuclei. We thus determine the relative contributions of excited nucleon, $p\pi$, and $p\pi \pi$ resonances and $\rho$, $\eta$, $\omega$ and K production, as well as the subsequent decay channels leading to neutrino and $\gamma$-ray production. This treatment is based, in large part, on the most recent and extensive empirical data on particle photoproduction interactions off protons and He nuclei. It is shown that, in astrophysical sources with steep proton energy spectra, the $\Delta$(1232) resonance channel clearly dominates. However, a blend of $N^{*}$ resonances at ∼1400 GeV can contribute as much as 20% to the neutrino flux. It is further found that $\gamma$–He interactions produce approximately 10% of astrophysical pions, as compared with $\gamma p$ interactions. Full article

In recent years, green hydrogen production via water electrolysis driven by renewable energy sources has garnered increasingly significant attention. Among the various water electrolysis technologies, proton-exchange membrane water electrolysis (PEMWE) distinguishes itself owing to the unique advantages, including the compact architecture, high efficiency, rapid dynamic response, and high purity of the generated hydrogen. The membrane electrode assembly (MEA) serves as the core component of a PEM electrolyzer. And only a high-performance and stable MEA can provide a reliable platform for investigating the mass transport behavior within the porous transport layer (PTL). In this study, the MEA fabrication method was optimized by varying the ionomer-to-carbon (I/C) ratio, coating strategy, and anode Ir mass loading. As a result, the cell voltage was reduced from 1.679 V to 1.645 V at 1.0 A cm⁻², with a small degradation of 1.3% over 70 h of operation. Based on the optimized MEA, the effects of the structure and porosity of PTL on the mass transport behavior were further analyzed. After the PTL parameter optimization, the cell voltage was further reduced to 1.630 V at 1.0 A cm⁻², while a high-speed camera captured bubble dynamics in real time, showing the fast detachment of small oxygen bubbles. The integrated electrochemical and visualization results provide a useful guideline to designing both MEA and PTL for efficient PEMWE. Full article

Emerging research indicates that neuronal activity is maintained by an architectural system of protons in a multi-scale fashion. Proton architecture is formed when organelles (such as mitochondria, endoplasmic reticulum, lysosomes, synaptic vesicles, etc.) are coupled together to produce dynamic energy domains. Techniques have been developed to visualize protons in neurons; recent advances include near-atomic structural imaging of organelle interfaces using cryo-tomography and nanoscale resolution imaging of organelle interfaces and proton tracking using ultra-fast spectroscopy. Results of these studies indicate that protons in neurons do not diffuse randomly throughout the neuron but instead exist in organized geometric configurations. The cristae of mitochondrial cells create oscillating proton micro-domains that are influenced by the curvature of the cristae, hydrogen bonding between molecules, and localized changes in dielectric properties that result in time-patterned proton signals that can be used to determine the metabolic load of the cell and the redox state of its mitochondria. These proton patterns also communicate to the rest of the cell via hydrated aligned proton-conductive pathways at the mitochon-dria-endoplasmic reticulum junctions, through acidic lipid regions, and through nano-tethered contact sites between mitochondria and other organelles, which are typically spaced approximately 10–25 nm apart. Other proton architectures exist in lysosomes, endosomes, and synaptic vesicles. In each of these organelles, the V-ATPase generates steep concentration gradients across their membranes, controlling the rate of cargo removal from the lumen of the organelle, recycling receptors from the surface of the membrane, and loading neurotransmitters into the vesicles. Recent super-resolution pH mapping has indicated that populations of synaptic vesicles contain significant heterogeneity in the amount of protons they contain, thereby influencing the amount of neurotransmitter released per vesicle, the probability of vesicle release, and the degree of post-synaptic receptor protonation. Additionally, proton gradients in each organelle interact with the cytoskeleton: the protonation status of actin and microtubules influences filament stiffness, protein–protein interactions, and organelle movement, resulting in the formation of localized spatial structures that may possess some type of computational significance. At multiple scales, it appears that neurons integrate the proton micro-domains with mechanical tension fields, dielectric nanodomains, and phase-state transitions to form distributed computing elements whose behavior is determined by the integration of energy flow, organelle geometry, and the organization of soft materials. Alterations to the proton landscape in neurons (e.g., due to alterations in cristae structure, drift in luminal pH, disruption in the hydration-structure of the cell, or imbalance in the protonation of cytoskeletal components) could disrupt the intracellular signaling network well before the onset of measurable electrical or biochemical pathologies. This article will summarize evidence indicating that proton–organelle interaction provides a previously unknown source of energetic substrate for neural computation. Using an integrated approach combining nanoscale proton energy, organelle interface geometry, cytoskeletal mechanics, and AI-based multiscale models, this article outlines current principles and unresolved questions related to the subject area as well as possible new approaches to early detection and precise intervention of pathological conditions related to altered intracellular energy flow. Full article

The RADFET VT06 developed by Varadis (Cork, Ireland), which is aimed at high-dose applications, mainly for spacecraft missions, has been characterized by low- and high-energy proton beams at two different facilities, the Accelerator National Centre (Sevilla, Spain) and the Paul Scherrer Institute (PSI) located in Villigen (Switzerland), using a reader unit system developed by the University of Granada (Spain). The devices have been characterized with proton energies of 1, 2, 3, 150, and 230 MeV, with accumulated doses from 130 to 512 Gy, where the RADFET was unbiased during the irradiation while the source voltage was measured before and after irradiation to monitor the radiation dose. Excellent linearity has been obtained with a minimum correlation factor R² of 0.996, with a sensitivity that can vary from (0.691 ± 0.007) mV/Gy for 1 MeV to (1.143 ± 0.023) mV/Gy for 230 MeV without any build-up layer. An excellent stability was found in the studied cases, with dispersion being lower than 4% after a dose accumulation higher than 500 and 200 Gy for protons of 1 and 3 MeV, respectively. The detectors demonstrated linear responses, very low sensitivity dispersion per set of samples, and excellent stability after irradiation. This shows that, with an appropriate readout system, the RADFET can become an excellent system for high-dose proton beams. Full article

Integrating electrochemical fuel cells and internal combustion engines can enhance the total efficiency and sustainability of power systems. This study presents a promising solution by integrating a Proton Exchange Membrane Fuel Cell (PEMFC) with a mini gas turbine, forming a hybrid system called the “Oya System.” This approach aims to mitigate the efficiency losses of gas turbines during high ambient temperatures. The hybrid model was designed using Aspen Plus for modelling and the EES simulation program for solving mathematical equations. The primary objective of this research is to enhance the efficiency of gas turbine systems, particularly under elevated ambient temperatures. The results demonstrate a notable increase in efficiency, rising from 37.97% to 43.06% at 10 °C (winter) and from 31.98% to 40.33% at 40 °C (summer). This improvement, ranging from 5.09% in winter to 8.35% in summer, represents a significant achievement aligned with the goals of the Oya System. Furthermore, integrating PEMFC contributes to environmental sustainability by utilising hydrogen, a clean energy source, and reducing greenhouse gas emissions. The system also enhances efficiency through waste heat recovery, further optimising performance and reducing energy losses. This research highlights the critical role of interface engineering in the hybrid system, particularly the interaction between the PEMFC and the gas turbine. Integrating these two systems involves complex interfaces that facilitate the transfer of electrochemistry, energy, and materials, optimising the overall performance. This aligns with the conference session’s focus on green technologies and resource efficiency. The Oya System exemplifies how innovative hybrid systems can enhance performance while promoting environmentally friendly processes. Full article

Laser-driven ion acceleration in dense, hydrogen-rich media can be significantly enhanced by embedding metallic nanoantennas that support localized surface plasmon (LSP) resonances. Using large-scale particle-in-cell (PIC) simulations with the EPOCH code, we investigate how nanoantenna geometry and laser pulse parameters influence proton acceleration in gold-doped polymer targets. The study covers dipole, crossed, and advanced 3D-cross antenna configurations under laser intensities of 10¹⁷–10¹⁹ W/cm² and pulse durations from 2.5 to 500 fs, corresponding to experimental conditions at the ELI laser facility. Results show that the dipole antennas exhibit resonance-limited proton energies of ~0.12 MeV, with optimal acceleration at the intensities 4 × 10¹⁷–1 × 10¹⁸ W/cm² and pulse durations around 100–150 fs. This energy is higher by roughly three orders of magnitude than the proton energy for the same field and same polymer without dopes: ~1–2 × 10⁻⁴ MeV. Crossed antennas achieve higher energies (~0.2 MeV) due to dual-mode plasmonic coupling that sustains local fields longer. Advanced 3D and Yagi-like geometries further enhance field localization, yielding proton energies up to 0.4 MeV and larger high-energy proton populations. For dipole antennas, experimental data from ELI exists and our results agree with it. We find that moderate pulses preserve plasmonic resonance for longer and improve energy transfer efficiency, while overly intense pulses disrupt the resonance early. These findings reveal that plasmonic field enhancement and its lifetime govern energy transfer efficiency in laser–matter interaction. Crossed and 3D geometries with optimized spacing enable multimode resonance and sequential proton acceleration, overcoming the saturation limitations of simple dipoles. The results establish clear design principles for tailoring nanoantenna geometry and pulse characteristics to optimize compact, high-energy proton sources for inertial confinement fusion and high-energy-density applications. Full article

With the rapid advancement of hydrogen-based direct current microgrid (H₂-DCMG) technology, multi-port converters (MPCs) have emerged as the pivotal interface for integrating renewable power generation, energy storage, and diverse DC loads. This paper systematically reviews the current research status and development trends of isolated and non-isolated MPC topologies within hydrogen-based DC microgrids. Firstly, it analyses the interface requirements for typical distributed energy sources (DER) such as photovoltaics (PV), wind turbines (WT), fuel cells (FC), battery energy storage (BESS), proton exchange membrane electrolyzers (PEMEL), and supercapacitors (SC). Secondly, it classifies and evaluates existing MPC topologies, clarifying the structural characteristics, technical advantages, and challenges faced by each type. Results indicate that non-isolated topologies offer advantages such as structural simplicity, high efficiency, and high power density, making them more suitable for residential and small-scale microgrid applications. Isolated topologies, conversely, provide electrical isolation and modular scalability, rendering them appropriate for high-voltage electrolytic hydrogen production and industrial scenarios with stringent safety requirements. Finally, the paper identifies current research gaps and proposes that future efforts should focus on exploring topology optimization, system integration design, and reliability enhancement. Full article

This work explores water hydrolysis using magnesium as a decentralized dihydrogen source for off-grid households. A dedicated reactor design enabled on-demand dihydrogen generation, coupled with a Proton Exchange Membrane Fuel Cell (PEMFC) for electricity and heat production. Different energy management strategies were compared, highlighting the limitations of single-purpose approaches and the benefits of converting surplus electricity to heat. The integration of photovoltaic generation further reduced magnesium demand by 30%, thus reducing storage requirements to close to 1565 kg of magnesium powder per year, i.e., a volume of 0.9 m³ to cover the heat and electricity needs of a four-person household. Results demonstrate that combining water hydrolysis with magnesium and renewables provides a feasible and sustainable solution for autonomous energy supply in isolated sites. Full article

Hybrid membranes are promising alternatives for various applications, combining a continuous polymer phase with a dispersed filler phase to achieve synergistic functional benefits. The ideal fillers should possess well-defined structures and unique properties for multi-functionality, as well as being sourced from renewable, biodegradable materials for sustainability purposes. This study explored the potential of using cellulose-based renewable materials as fillers for hybrid polymer electrolyte membranes (PEMs) in fuel cells. Cellulose whiskers (CWs), known for their high crystallinity and elastic modulus, were effectively synthesized via optimized sequential alkali treatment and acid hydrolysis. Subsequent functionalization with citric acid was performed to enhance their reinforcing properties and overall performance. Initial characterization using ATR-FTIR and XRD confirmed the CWs’ structural composition, high crystallinity, and the presence of reactive groups (sulfate and hydroxyl). The functionalization process introduced new carbonyl groups (C=O), which was verified by ATR-FTIR, while maintaining high hydrophilicity. Morphological analysis revealed that the crosslinked CWs created a denser and more compact microstructure within the membrane, leading to a significant enhancement in mechanical strength. The modifications to the cellulose whiskers not only improved structural integrity but also boosted the membrane’s ion exchange capacity (IEC) and proton conductivity compared to membranes with unmodified CWs. Initial experiments demonstrated CWs’ compatibility as a filler in a polysulfone (PSU) matrix, forming hybrid membranes suitable for fuel cell applications. Full article