Search Results (11,544)

Phosphoric acid-doped polybenzimidazole membranes are a leading fluorine-free electrolyte platform for high-temperature proton exchange membrane fuel cells, enabling proton transport under anhydrous conditions. However, recent evidence shows that conductivity, mechanical stability, and acid retention are intrinsically coupled, preventing independent optimization of these properties. This review establishes a unified framework in which membrane performance is governed by a multidimensional design space defined by acid doping level, activation energy (E_a), hydrogen-bond network topology, and mechanical confinement. Conductivity is shown to scale with both carrier density and hopping energetics, while mechanical stability decays with increasing ADL due to acid-induced plasticization, described through a semi-empirical relationship. Analysis across molecular architectures, including molecular weight control, crosslinking, backbone modification, topological design, and free-volume engineering, demonstrates that performance emerges from a balance between transport efficiency and structural stability. Device-level benchmarking further reveals that similar conductivity values can correspond to orders-of-magnitude differences in voltage decay rate, confirming that durability is governed primarily by mechanical confinement and acid mobility rather than σ alone. A multivariate stability corridor is identified, within which phosphoric acid-doped polybenzimidazole membranes achieve σ ≈ 0.14–0.20 S·cm⁻¹ while maintaining low degradation rates under realistic high temperature proton exchange membrane conditions. Based on this framework, quantitative design rules are derived linking acid doping level, activation, topology, and mechanical properties. This work shifts membrane design from conductivity-driven optimization toward predictive structure–property–durability engineering, providing a basis for the development of next-generation HT-PEM fuel cells with sustained long-term performance. Full article

Mechanistic interpretability seeks to reverse-engineer the computational circuits within large language models, but current methods rely on exhaustive or heuristic search over exponentially many feature interactions. This paper introduces Active Circuit Discovery (ACD), a framework that combines attribution-graph analysis with active inference to select interventions efficiently. ACD uses Anthropic’s circuit-tracer library as its attributiongraph backend, applying Edge Attribution Patching with transcoders to identify the active transcoder features for each prompt. A partially observable Markov decision process (POMDP) agent, implemented with pymdp, maintains a multi-factor generative model of feature importance, layer role, and causal influence. At each step, the agent selects both a target feature and an intervention type (ablation, activation patching, or feature steering) by minimising Expected Free Energy over the joint feature–action space, and it learns its observation model online through Dirichlet parameter updates. ACD is an interventionselection layer over existing attribution-graph tools; it is not a whole-circuit discovery method, and no claim of state-of-the-art circuit discovery is made. The framework is evaluated on Gemma-2-2B (26 layers) and Llama-3.2-1B (16 layers) across four settings: Indirect Object Identification (IOI), multi-step reasoning, feature steering, and a multidomain benchmark spanning geography, mathematics, science, logic, and history. With a budget of 20 interventions per prompt, an ablation-only agent scored by bounded oracle efficiency against the ablation oracle reaches 82.0% efficiency on Gemma IOI and 73.0% on Gemma multi-step. It exceeds random selection by 43.5% (relative) on Gemma IOI (paired permutation p = 0.031) and is competitive with greedy ranking, a heuristic UCB bandit, and a plain UCB baseline. A direct Edge-Attribution-Patching ranking is itself a strong baseline that the agent does not consistently surpass, and on Llama multi-step the agent reaches 9.3% efficiency (37.8% with finer layer-role bins). All comparisons report bootstrap 95% confidence intervals. The full multi-action agent is characterised separately by a Relative Cumulative KL, a steering-driven amplification factor reported apart from the bounded efficiency. Feature steering changes the top-1 prediction in a dose-dependent manner, but a matched random-feature control shows that circuit-selected features are only marginally, and not significantly, more steerable than random active features at large multipliers, indicating that part of the effect is generic activation scaling. Multi-domain analysis shows task-dependent circuit structure, with IOI circuits concentrated in late layers and reasoning and scientific knowledge recruiting early and middle layers. Code, notebooks (free T4), AMD64/aarch64 Docker images, and raw results are publicly available. Full article

The nucleation and growth mechanisms of copper electrodeposition from Cu(I)-containing-reline, a deep eutectic solvent, were investigated through a combination of electrochemical techniques and surface characterization. Cyclic voltammetry revealed the characteristic nucleation loop associated with an overpotential-driven electrocrystallization process, from which the equilibrium potential of the Cu(I)/Cu(0) redox couple was determined to be −0.35 V vs. a Ag quasi-reference electrode. Experimental potentiostatic current density transients were analyzed using nucleation models capable of accounting for both adsorption and three-dimensional (3D) diffusion-controlled growth, thereby allowing deconvolution of the individual contributions to the overall current response. The kinetic parameters, including the nucleation frequency and the number density of active sites, exhibited an exponential dependence on the applied overpotential, thus indicating enhanced nucleation kinetics at greater driving forces, while determining a Cu(I) diffusion coefficient of (3.39 + 0.09) × 10⁻⁷ cm² s⁻¹. Thermodynamic analysis showed that the Gibbs free energy of the formation of the critical nucleus decreases with increasing overpotential and follows the expected dependence on the inverse square of the overpotential, in agreement with classical nucleation theory. The estimated critical nucleus size was found to be smaller than one atom, suggesting that nucleation occurs at highly active surface sites. Furthermore, an exchange current density of (3 ± 1) μA cm⁻² was estimated for the Cu(I) electrochemical reduction. Scanning electron microscopy revealed a high density of copper nanoparticles (~20 nm) distributed across the electrode surface, along with larger aggregates (~100 nm) formed by coalescence and growth, consistent with a progressive nucleation mechanism. X-ray photoelectron spectroscopy confirmed that the deposits consist exclusively of metallic copper, with no evidence of oxidized species. These results demonstrate that copper electrodeposition in reline is governed by a complex interplay between the thermodynamic driving force, the interfacial kinetics, and mass transport, comprehensively providing fundamental insight into the electrocrystallization processes in deep eutectic solvents. Full article

Lytic polysaccharide monooxygenases (LPMOs) are promising enzymes for lignocellulose degradation; however, wild-type LPMOs often exhibit limited catalytic activity and stability. In this study, computer-aided virtual saturation mutagenesis was applied to AnLPMO15g from Aspergillus niger, and eight potentially beneficial mutants (S197H, S197F, E185V, E185L, E185M, E185I, Q108M, and A249P) were identified based on predicted changes in unfolding free energy (∆∆G). Six mutants demonstrated enhanced activity in a 2,6-dimethoxyphenol (2,6-DMP) oxidation assay, which serves as a proxy for peroxidase-like activity. The E185V mutant exhibited a 45% increase over the wild type. The triple mutant E185V/Q108M/A249P further increased the catalytic efficiency by 56%. Notably, when combined with cellulase, E185V/Q108M/A249P enabled a 202.5% increase in reducing sugars from wheat straw, achieving a synergy degree of 1.83, highlighting its potential to improve agricultural residue conversion. Molecular dynamics simulation suggested that the E185V/Q108M/A249P triple mutant induced flexible conformational changes in six residues, which may improve substrate binding affinity. This study presents an effective strategy for engineering AA9 family LPMOs to enhance catalytic performance, facilitating efficient and cost-effective degradation of lignocellulosic biomass with implications for sustainable agricultural waste management and circular bioeconomy. Full article

The Pacific oyster (Crassostrea gigas) is well known for its pronounced umami taste. Here the interaction between the T1R1/T1R3 taste receptor and three oyster-based peptides, namely, FLNQDEEAR (FR-9), EEFLK (EK-5), and FNKEE (FE-5), was investigated via molecular docking and molecular dynamics (MD) simulations, as well as molecular mechanics Poisson–Boltzmann surface area (MM–PBSA) and residue–residue contact score (RRCS) analyses. A full-length human T1R1/T1R3 heterodimer was constructed with AlphaFold3. MD simulations indicated that the binding of FR-9 led to a large structural fluctuation, a large radius of gyration, and a large solvent accessible surface; on the contrary, FE-5 yielded the most stable receptor–ligand complex. The MM-PBSA analysis showed that the binding free energies of the three peptides were in the order of FR-9 > EK-5 > FE-5. The RRCS analysis indicated that RRCS values per residue were in the order of FR-9 < EK-5 < FE-5, in line with the reported umami score, and that the highest taste score of FE-5 originated from the hydrophobic interactions between Glu301 (receptor) and Phe1 (ligand) as well as the salt bridges between arginine (Arg277 and Arg307, receptor) and glutamic acid (Glu4 and Glu5, ligand) residues. These findings show that structural stability and residue contact density were more informative than binding affinity for distinguishing the taste intensity of umami peptides. Full article

The adhesive bonding of aluminum with other materials is widely used in the aerospace, marine, automotive and railroad industries that require lightweight materials. Adhesive bonding has the advantages of reduced corrosion, stress concentration, and cost effectiveness. To improve bonding strength and performance, we examined the use of ascorbic acid (vitamin C), which is a water-soluble compound and a natural reducing agent. Owing to its reducing power and acidity, ascorbic acid allows the Al etching process to proceed efficiently to increase the surface roughness and prevent Al oxidation. In addition, this study used an eco-friendly technique of simply immersing aluminum substrates in an ascorbic acid solution with sodium chloride. The surface free energy was evaluated using the sessile drop method and calculated using the Owens–Wendt–Rabel and Kaelble method. Confocal microscope was used to investigate the roughness of the surface, and the functional groups of Al surface were analyzed by X-ray photoelectron spectroscopy. The bonding strength was measured using the single-lap joint shear test. Compared to aluminum without treatment, the bonding strength of a treated AA 6061 was enhanced by 58.6%. Full article

L-carnitine plays a central role in mitochondrial fatty acid transport and cellular energy regulation; effects on the biochemical phenotype of brain cancer cells remain insufficiently characterized. Here, we applied confocal Raman spectroscopy and imaging to investigate the biochemical alterations induced by L-carnitine supplementation—administered as its tartrate salt—in human astrocytoma cells. Raman spectral analysis revealed distinct changes in lipid-, protein-, nucleic acid-, and cytochrome-associated vibrational features following 24 h of treatment, suggesting alterations in mitochondrial activity and cellular energy-related processes. Principal component analysis identified PC1 (93.87%) as representing the intrinsic biochemical composition of the cells, whereas PC2 (1.19%) and PC3 (0.59%) captured subtle yet consistent variations in lipid organization, protein conformation, and redox-sensitive vibrational features associated with L-carnitine exposure. Pearson correlation analysis of Raman cluster spectra indicated biochemical differences across cellular compartments, with the most pronounced changes observed in lipid droplets, supporting modifications in lipid-associated cellular processes. These findings demonstrate that Raman imaging provides a sensitive, label-free platform for resolving L-carnitine-induced biochemical heterogeneity at the single-cell level. Overall, this study highlights vibrational spectroscopy as a powerful tool for characterizing cellular responses to metabolic modulators and provides insight into the biochemical impact of exogenous L-carnitine in brain cancer cells. Full article

The microstructure of as-cast Al-xSi (x = 4, 7, 10) alloys solidified under various cooling rates was characterized using scanning electron microscopy (SEM). To overcome the multicollinearity among eutectic silicon parameters, Principal Component Regression (PCR) analysis was employed to quantitatively evaluate the effects of silicon morphology, scale, and content on the electrical conductivity of the alloys. The results demonstrate that rapid solidification significantly refines the plate-like eutectic silicon and reduces its volume fraction, leading to improved electrical conductivity. The PCR model shows that a hierarchical mechanism: volume fraction (PC1) acts as the principal determinant, increasing baseline resistance primarily by truncating the electron mean free path (MFP); meanwhile, within identical alloy systems, morphological parameters (PC2) play a dominant regulatory role. A semi-quantitative electron drift path model was established, confirming that the morphological deviation of eutectic silicon from a spherical shape (i.e., increased aspect ratio) causes a non-linear increase in the amplitude of electron detours. This geometric elongation significantly degrades electrical conductivity, providing theoretical guidance for the microstructural design of high-conductivity Al-Si alloys, which can be practically applied to the manufacturing and optimization of lightweight, heat-dissipating enclosures for new energy vehicle (NEV) motors and power distribution systems. Full article

The increasing demand of digital technologies and their integration with wearable health devices provides an efficient trigger for next-generation wearable healthcare devices for long-term physiological monitoring. The advancement of energy harvesting mechanism, nanomaterial-based sensor fabrication and their integration with digital technologies have emerged as a promising solution for transforming future of digital health. This study provides a comprehensive summary and framework for wearable self-powered electronic devices, enabling continuous, battery-free health monitoring and advancing the development of sustainable, next-generation digital healthcare systems. This review paper presents a broad and detailed overview of current technologies and sensors advancement in developing low-power wearable, self-powered electronic devices suitable for healthcare applications. The importance and reliable use of key energy harvesting approaches including triboelectric, piezoelectric, thermoelectric, and photovoltaic approaches are systematically presented which focused on development of energy efficient wearable devices. This review further examines the low-power circuit design strategies for flexible electronics focusing personalized healthcare monitoring. Current challenges and limitations related to advanced manufacturing of wearable health devices focusing on large-scale deployment are also analyzed. Finally, the key future research directions are outlined for advancing a next-generation intelligent digital health system. Full article

A high quality factor, denoted as the Q-factor, is crucial for micromachined disk resonator gyroscopes, commonly referred to as DRGs, to suppress thermomechanical noise and improve bias stability. However, the coupled energy dissipation mechanisms under low-pressure conditions impose significant limitations on further Q-factor enhancement. This paper establishes a rigorous multiphysics damping analysis framework for DRGs and quantitatively investigates the contributions of air damping, thermoelastic damping, and anchor loss. A free-molecular squeeze-film damping model is derived based on kinetic gas theory and molecular energy transfer mechanisms, avoiding the continuous fluid assumption of the classical Reynolds equation, which fails in low-pressure regimes. Due to the highly symmetric ring structure and central anchor design, finite element method simulations reveal an extremely high anchor-loss-limited quality factor, Q_anchor, of approximately 1.85 × 10¹², indicating negligible anchor-induced dissipation. Under an operating pressure of 0.1 Pa, air damping is validated as the absolute dominant energy dissipation mechanism with a gas quality factor, Q_air, of approximately 1.105 × 10⁵, which is significantly lower than the thermoelastic damping quality factor, Q_TED, evaluated at 8.98 × 10⁵. To break the classical trade-off between squeeze-film damping suppression and capacitive drive efficiency, a decoupled gap optimization strategy is proposed. By maintaining the drive electrode gap, gap_e, at 7.2 µm while increasing only the parasitic ring-to-suspended-mass gap, gap_m, to 12 µm, the squeeze-film-damping-limited Q-factor is improved by approximately 25% to 1.381 × 10⁵ without degrading electromechanical coupling efficiency. In addition, the optimal anchor radius is determined to be approximately 160 µm. The proposed framework provides practical design guidance for high-Q DRGs and other MEMS resonant inertial sensors. Full article

Underwater object detection using forward-looking sonar presents fundamental challenges absent from terrestrial imagery: low-contrast single-channel inputs, multi-scale acoustic shadows, and object classes spanning a wide range of acoustic scattering characteristics. Three coordinated modifications to the YOLOv8 framework are proposed to address structural limitations of standard bottleneck chains for this domain. A fractional-order feature propagation mechanism based on Grunwald–Letnikov discretization enables each bottleneck to access a decaying-weighted history of all prior intra-chain feature states via a single learnable scalar per block. A boundary-aware gating module with joint spatial-channel attention selectively suppresses fractional correction at geometric boundary locations. A parameter-free energy-based attention module applied in the detection neck exploits the local statistical distinctiveness of genuine acoustic features during multi-scale fusion. Evaluated on the Underwater Acoustic Target Detection dataset, the proposed system achieves mAP50 of 0.8635 and mAP50-95 of 0.3964, improvements of 0.0188 and 0.0136 respectively over the YOLOv8n baseline at less than 2.0% parameter overhead, surpassing larger generic YOLOv8 variants on mAP50. Full article

Objectives: This study aimed to identify core genes associated with mitochondria-related transcriptomic signatures and evaluate their potential as computational biomarkers, immune characteristics, regulatory mechanisms, and potential therapeutic relevance. Methods: Obesity-related transcriptome datasets were obtained from the GEO database. Differentially expressed genes (DEGs) were intersected with mitochondria-related genes (MRGs) to identify obesity-related MRGs. Functional enrichment, protein–protein interaction (PPI) analysis, CytoHubba, LASSO and random forest algorithms were used to screen core genes. External validation, ROC analysis, immune infiltration analysis, regulatory network construction, candidate drug prediction, and molecular docking were further performed. Results: A total of 527 DEGs and 15 differentially expressed MRGs were identified. Enrichment analysis suggested that these mitochondria-related genes were mainly associated with disrupted mitochondrial energy metabolism, lipid metabolic remodeling, and altered substrate utilization. ECHDC2, FASN, NAT8L, and AASS were identified as core MRGs; these genes are respectively associated with mitochondrial metabolic regulation, de novo fatty acid synthesis, N-acetylaspartate-related mitochondrial metabolism, and lysine degradation. These genes were significantly downregulated in obesity and showed good diagnostic performance. Immune infiltration analysis revealed alterations in the immune microenvironment, and the core genes were negatively correlated with multiple immune cell types. Molecular docking showed that Genistein had the lowest predicted binding free energy with NAT8L (−8.89 kcal/mol), suggesting relatively favorable binding among the tested ligand–target pairs. Conclusions: ECHDC2, FASN, NAT8L, and AASS may serve as candidate computational biomarkers, among which FASN represents a known lipid metabolism-related gene, supporting the biological plausibility of the workflow. Full article

Background/Objectives: Tuberculosis (TB), caused by Mycobacterium tuberculosis complex, remains a major global health challenge. Recently, D-enantiomer of human lactoferricin 1–11 (D-form hLF 1–11), a short peptide derived from the N-terminal region of lactoferrin, has demonstrated potent antimycobacterial activity. However, its direct mechanism of action has not yet been elucidated. Methods & Results: In the present study, M. smegmatis was employed as a model organism to investigate the mechanism underlying D-form hLF 1–11 activity. Initially, the minimum inhibitory concentration (MIC) was determined and the results revealed growth inhibition at 400 µg/mL. Live/dead fluorescence staining demonstrated mycobactericidal activity, as indicated by increased propidium iodide (PI) uptake relative to the untreated control. Scanning electron microscopy and high-resolution fluorescence microscopy revealed membrane disruption and substantial morphological deformation, along with a time-dependent accumulation of the peptide at the membrane and inside the cells. Furthermore, label-free quantitative proteomic analysis of peptide-treated cells revealed extensive metabolic alterations in carbon metabolism, acetyl-CoA-dependent lipid biosynthesis, oxidative stress defense, translational machinery, and energy production systems. Conclusions: Collectively, these findings provide mechanistic insights into the antimycobacterial activity of D-form hLF 1–11 against M. smegmatis. Full article

Internal combustion engines are a well-established, efficient and dispatchable solution for distributed power generation and they are widely used in various sectors including grid balancing, data centers and combined heat and power systems. Current research efforts focus on further increasing efficiency, enabling decarbonization through renewable fuels and improving responsiveness to electricity demand in the presence of variable renewable energy sources. In this context, the free-piston linear generator (FPLG) stands out as a highly promising technology, as it directly converts piston motion into electricity, offering high efficiency, reduced mechanical complexity and seamless grid integration. Initially explored for its high-efficiency potential with homogeneous charge compression ignition combustion at extreme compression ratios, opposed-piston FPLGs are now commercially available for distributed power generation, delivering global efficiencies exceeding 45%, near-zero emissions and multi-fuel capability. Building on the detailed studies conducted by Svrcek and co-authors, this work investigates the power-generation potential of low-temperature homogeneous combustion using CFD simulations with detailed chemical kinetics. First, rapid compression machine (RCM) experiments with methane were reproduced in simulations to validate the proposed methodology and to consolidate experimental findings on the maximum achievable efficiency. Subsequently, an extensive RCM simulation campaign supported the identification of optimal operating conditions in terms of air–fuel ratio using methane as fuel. The RCM results enabled the definition of a preliminary methane-fueled opposed-piston FPLG configuration. Full-cycle simulations including gas exchange, mixing and combustion demonstrated an indicated efficiency of 58% at an equivalence ratio $\varphi =0.5$ and a compression ratio of 50. The key novelties of this study are the development of a novel RCM-2 configuration that more closely reproduces the dynamic behavior of an opposed-piston FPLG including air-spring effects and the introduction of a divided intake port strategy to simultaneously reduce fuel slip and mitigate knocking behaviour through charge stratification. The simulation results for the proposed configuration confirm the potential of opposed-piston FPLGs for high-efficiency power generation and highlight key parameters affecting performance and emissions formation. Full article

Quinoline derivatives constitute a privileged class of nitrogen-containing heterocycles with extensive applications in medicinal chemistry, agrochemicals, materials science, and functional organic materials. Owing to their broad biological and industrial relevance, the development of efficient, selective, and sustainable synthetic methodologies for quinoline construction remains an active area of research. This review provides a comprehensive overview of recent advances in quinoline synthesis, with particular emphasis on catalytic strategies aligned with the principles of green and sustainable chemistry. Classical transformations, including the Friedländer, Skraup, and Povarov reactions, are revisited in the context of modern catalytic developments that improve reaction efficiency, substrate scope, selectivity, and environmental compatibility. Special attention is devoted to homogeneous and heterogeneous catalytic systems based on both platinum-group and earth-abundant transition metals, highlighting the growing importance of borrowing-hydrogen and acceptorless dehydrogenative coupling methodologies. Recent progress in nanocatalysis, photocatalysis, multicomponent reactions, ionic-liquid-mediated transformations, and metal-free protocols is also critically discussed. Furthermore, solvent-free processes, microwave-assisted synthesis, and recyclable catalytic systems are examined as practical approaches toward minimizing waste generation and energy consumption. Mechanistic aspects, catalytic design principles, substrate limitations, and sustainability metrics are evaluated throughout the review to provide a critical perspective on current methodologies. Collectively, the advances summarized herein demonstrate the rapid evolution of quinoline synthesis toward more atom-economical, environmentally benign, and operationally efficient processes, while also identifying future opportunities for the development of next-generation catalytic platforms for quinoline-based heterocycle construction. Full article