Search Results (9,152)

The paper investigates the possibility of small hydrogen (SH) formation in the early Universe during an interval of about 10–80 s after the Big Bang. Assuming that SH exists as proposed by the author earlier, the current study examines the cosmological conditions under which the SH can be formed and survive. The photon, baryon, and electron–positron pair densities are estimated, together with the corresponding thermal energies and temperatures, and the formation cross section required to obtain a specified SH abundance and the maximum destruction cross section consistent with SH survival are derived. Although the microscopic formation and destruction cross sections are not presently known, phenomenological constraints the cross sections must satisfy are derived for a given SH abundance. The study suggests that, if SH exists and has negligible nuclear interactions, it would not significantly participate in the standard Big Bang nucleosynthesis reaction network. The possibility that SH can undergo early cosmological decoupling, subject to the presently unknown momentum-transfer cross sections, is also discussed. If SH is formed in sufficient abundance and decouples sufficiently early, it can provide an interesting mechanism for early structure formation and may potentially contribute to the formation of black-hole seeds. This study does not establish the existence of SH, but rather examines whether the conditions in the early Universe present immediate cosmological obstacles to SH formation and survival. Full article

This study aims to characterize the seasonal variability and optical properties of aerosols and to investigate their potential sources, transport pathways, and radiative impacts over a rural site in Southeast India. Ground–based MICROTOPS–II Sunphotometer observations during April 2021–December 2023 were integrated with trajectory–based source analysis and OPAC–SBDART radiative–transfer simulations to examine the links between aerosol characteristics, meteorological conditions, source regions, and radiative effects. The annual mean aerosol optical depth at 500 nm (AOD₅₀₀) was found to be 0.56 ± 0.22, peaking during pre–monsoon (0.66 ± 0.19) and winter (0.64 ± 0.23), and lowering during the rainy monsoon (0.49 ± 0.21). Enhanced aerosol loading during the dry seasons was associated with local emissions and long–range continental transport, whereas monsoon conditions favored marine influence, atmospheric ventilation and wet scavenging, as supported by trajectory analyses using potential source contribution function (PSCF) and concentration weighted trajectory (CWT) models. Higher Ångström exponent (AE) values during winter and pre–monsoon (1.30 ± 0.24) indicated dominance of fine–mode continental aerosols, while the lower monsoon values (0.83 ± 0.37) reflected increased contribution of coarse particles. Negative values of spectral curvature further confirmed fine–mode dominance during dry seasons. The estimated precipitable water vapor increased markedly from winter (2.00 ± 0.37 cm) to monsoon (4.35 ± 0.35 cm), likely influencing aerosol optical properties through hygroscopic growth. Meteorological parameters significantly modulated aerosol loading and size distribution across seasons. AOD–AE relationships revealed predominance of fine anthropogenic aerosols in all seasons except monsoon, while aerosol classification indicated substantial fine–mode contributions under turbid atmospheric conditions. OPAC–SBDART simulations estimated significant aerosol–induced surface cooling (−41 to −42 W m⁻²) and atmospheric warming (38–41 W m⁻²) under high aerosol loading conditions, leading to atmospheric heating rates of 1.1–1.2 K day⁻¹. However, lower aerosol loading in monsoon reduced heating rates to 0.3–0.4 K day⁻¹. Current findings highlight the critical role of monsoon flow and meteorological dynamics in regulating aerosol characteristics and regional radiative forcing over Southeast India. Full article

A distribution feeder is built meshed and operated radially, so at any instant it occupies one of a combinatorial family of topologically radial configurations. We show that this family, weighted in the natural maximum-entropy way, is a determinantal point process whose kernel is the transfer-current matrix of the network, and we read that kernel in the operator’s language: the probability that a line section is energised equals its own self transfer-current factor, Foster’s sum rule is the trace identity, and the covariance of two switching states is minus the square of their normalised transfer current. Independent faults leave the feeder exactly within this family for any number of faults, whereas no restoration mechanism ignorant of the section resistances can return it there; among those that can, one is canonical, being the unique mechanism that reverses the fault, and its weight is the section’s transfer-current factor in the post-fault network with everything still energised shorted. We show, and report, that these weights are a structural diagnostic and not a repair priority. The maintained feeder is solved in closed form, and an exact transport equation prices what a reinforcement programme costs the feeder’s ability to reconfigure. The central spanning-tree and sector identities are verified against exhaustive enumeration; the dynamical and sensitivity statements are checked by exact master-equation computations and finite differences. Full article

Air quality modeling of sulfur dioxide (SO₂) concentrations remains challenging due to the high variability of both natural and anthropogenic emission sources, as well as the complexities associated with its multiphase chemistry. The data assimilation (DA) of satellite observations is a promising technique for constraining model uncertainties by combining the strengths of high-resolution and dense satellite retrievals with physical consistent model outputs. However, existing SO₂ DA applications have primarily focused on volcanic events while this study addresses them together with other emissions. The implementation of an SO₂ DA framework within the MINNI regional chemical transport model using an Ensemble Adjusted Kalman Filter (EAKF) via the DART framework is presented. The performances of the DA assimilation framework were tested using Sentinel-5P/TROPOMI SO₂-COBRA total column retrievals over continental Europe for August 2023. The filter constrained the ensemble variance to capture plumes from power plants and volcanic activity. The ensemble considered 20 members and perturbations of emissions and boundary conditions. On a monthly basis, the mean correction for the total column averaged over the domain was 2 × 10⁻⁵ mol m⁻², with localized maximum adjustments reaching 3.3 × 10⁻⁴ mol m⁻². At the surface level, domain-averaged corrections of concentrations reached up to 2.6 µg m⁻³. Despite current limitations related to ensemble size, static vertical localization, and the typical temporal fading of initial condition corrections, validation against in situ data confirmed the system’s ability to transfer column information to near-surface levels. These results demonstrate the feasibility and added value of integrating mixed-source SO₂ satellite retrievals into regional air quality simulations, contributing to more accurate, observation-driven atmospheric monitoring. Full article

Advances in artificial intelligence, high-performance computing, and generative AI technologies have driven a rapid increase in the memory bandwidth and data throughput required of semiconductor systems, establishing High Bandwidth Memory (HBM)—which vertically stacks multiple DRAM dies—as a key enabling memory technology. However, increasing the stack count and shrinking the interconnect pitch in HBM not only intensify vertical heat accumulation and hotspot formation but also give rise to complex reliability issues, including thermo-mechanical stress arising from coefficient-of-thermal-expansion (CTE) mismatch, package warpage, interfacial delamination, Cu protrusion, void formation, and joint degradation. This review analyzes the heat-generation and heat-transfer mechanisms of HBM packages and examines package-level thermal management strategies based on thermal interface materials, underfill, non-conductive film, epoxy molding compound, heat spreaders, and high-thermal-conductivity composites. It further summarizes the current crowding, electromigration, Cu–dielectric interfacial defects, and thermo-mechanical failure mechanisms that arise at fine-pitch interconnects and hybrid-bonding interfaces, together with the material and process design strategies developed to mitigate them. In addition, structure-based thermal management technologies—thermal TSVs, embedded cooling, and hybrid bonding—are compared. This review emphasizes that the thermal bottlenecks and reliability degradation of HBM are interconnected through interfacial thermal resistance, interfacial adhesion, residual stress, and interfacial defects, and proposes that next-generation, highly stacked HBM requires a multi-scale thermal-reliability co-design that integrally controls the heat-, stress-, and current-transfer pathways across the entire package and interconnect domain, rather than relying on the improvement of individual material properties alone. Full article

The dual active bridge (DAB) converter is one of the most common types of isolated bidirectional power converters in modern spacecraft EPS owing to its galvanic isolation, bidirectionality, soft switching, and good controllability. However, the goal of power transfer maximization often clashes with real-world spacecraft EPS constraints, namely thermal compliance, reliability, and the accuracy of simplified models used for analysis. This paper proposes a physics-informed methodology to derive the practical operating range under single phase shift (SPS) control based on a rigorous piecewise time-domain representation. From this model, the steady-state initial condition, general closed-form RMS current expression, ZVS boundary condition, and ZVS-aware loss model linked to the junction-temperature estimate are derived. The validity domain of the fundamental harmonic approximation (FHA) is evaluated against the exact model across the full (φ, k) space, and a two-dimensional operating map superposing power contours, the ZVS limit, and the thermal limit is presented. For the baseline case study at k = 1.0, the thermal constraint limits the nominal feasible upper phase shift to approximately 35°, while the broader 15–45° range remains useful for design assessment and operation toward 45° requires lower effective resistance and/or improved thermal management. The normalized SPS power-transfer curve retains the same shape under variations in L and f_s, but RMS current, losses, and thermal feasibility must be reassessed for each converter design. The resulting closed-form framework provides a steady-state feasibility-evaluation tool for spacecraft EPS design and offers a computational basis for future supervisory constraint evaluation under varying voltage, load, and thermal conditions. Full article

The development of sustainable and efficient methods for carbon–carbon (C–C) bond formation remains the main objective in modern organic synthesis. In recent years, photocatalysis has developed as a suitable alternative to conventional transition-metal-catalyzed approaches, offering mild reaction conditions, high functional-group tolerance, excellent atom economy, and the ability to utilize visible light as a clean and renewable energy source. Through unique radical-mediated pathways, photocatalytic strategies allow the selective activation of traditionally unreactive substrates, including haloarenes, alkanes, alcohols, carboxylic acids, and amines, thereby providing efficient routes to complex molecular architectures. Beyond organic synthesis, photocatalysis has also demonstrated significant potential in broader areas of applied chemistry. This review summarizes the major advances in photocatalytic C–C bond coupling reported from 2023 to early 2026, with special focus on C(sp³)–C(sp³), C(sp³)–C(sp²), and C(sp²)–C(sp²) bond-forming reactions. Representative catalytic systems, substrate scope, reaction mechanisms, and synthetic applications are critically discussed, including dual photoredox/transition-metal catalysis, metal-free photocatalysis, hydrogen atom transfer (HAT), proton-coupled electron transfer (PCET), radical–radical coupling, decarboxylative and deaminative functionalization, and enantioselective transformations. Finally, current challenges, emerging trends, and future opportunities for developing more sustainable, scalable, and selective photocatalytic C–C bond-forming methodologies are highlighted, providing a comprehensive resource for researchers working in synthetic and medicinal chemistry. Full article

Ultraweak photon emission (UPE) provides a noninvasive optical signature of oxidative chemistry, but the relationship between infection-associated reactive oxygen species (ROS) and photon emission remains mechanistically uncertain. Here, we develop a multiscale framework linking pathogen dynamics, immune activation, signaling ROS, emission-relevant oxidative chemistry, chemiexcitation-capable intermediates, electronically excited molecular states, and wavelength-resolved UPE. Chemiexcitation is represented as incoherent Lindblad pumping, allowing stochastic oxidative reactions to populate molecular excited states without assuming coherent ROS-driven optical excitation. The model was evaluated using literature-constrained oxidative inputs for healthy, severe COVID-19, and sepsis conditions, together with Latin Hypercube uncertainty propagation, Sobol sensitivity analysis, fixed-ROS counterfactual testing, spectral robustness analysis, and a pathway-level PMA/DPI intervention consistency test. Two admissible oxidative-to-photon mappings produced sharply different quantitative predictions from the same clinical ROS inputs. Under a high-gain structure, 9.01-fold and 13.86-fold oxidative increases produced 42.21-fold and 89.02-fold increases in peak UPE, whereas a saturating structure compressed the same inputs to 1.445-fold and 1.450-fold. Local elasticity remained near 1.7 under the high-gain mapping but declined to 0.011 and 0.005 at the COVID-19 and sepsis inputs under the saturating mapping. At fixed ROS, downstream parameter uncertainty produced more than a 200-fold spread in predicted UPE under the high-gain structure. Sobol analysis identified the saturation scale, emission-relevant oxidative lifetime, and signaling-to-emission conversion as the dominant contributors to output variance. In a pathway-level consistency test, a subset of high-gain realizations reproduced the reported DPI/PMA residual-UPE interval under physically admissible residual oxidative drive, whereas none of the sampled saturating realizations did. The model also predicted a progressive redistribution of spectral intensity toward longer wavelengths with increasing oxidative burden, although absolute spectral centroids remained dependent on the assumed spectral representation and emitter weighting. These results show that current ROS measurements constrain the direction of the UPE response more strongly than its quantitative magnitude and do not identify a unique universal ROS-to-UPE transfer function. Full article

This paper investigates stable and compact diagnostic feature signatures for faults related to demagnetization in brushless direct-current (BLDC) and permanent-magnet synchronous motor (PMSM) drives. Discovery analysis on the public DUDU-BLDC v1 benchmark—where DUDU is the project name derived from the PolishDiagnostyka Uszkodzeń i Degradacji Urządzeń—compares current, speed, and combined representations under explicit top-k budgets using ReliefF, minimum-redundancy maximum-relevance (mRMR), least absolute shrinkage and selection operator (LASSO), and Bayesian automatic relevance determination (ARD) logistic ranking. The revision is accompanied by DUDU-BLDC 1.5, a new and previously unpublished March 2026 dataset comprising 50 recordings from five physical motors under altered acquisition conditions. On this second campaign, leakage-free nested five-fold recording-grouped validation with three deterministic repeats reached balanced accuracies of 0.760 and 0.758 for the two confirmatory within-motor tasks. Motor-held-out balanced accuracies fell to 0.500 and 0.554, with four of five physical-motor estimates at chance and one estimate at 0.663, exposing substantial between-motor heterogeneity. A paired experiment that quantized the original raw current signals to the approximately 0.08 A resolution of DUDU-BLDC 1.5 produced a mean absolute balanced-accuracy change of 0.0046, although the maximum change was 0.0725 and individual ranking-stability changes were larger. The results support compact signatures for repeated monitoring within an established or calibrated motor population and show aggregate robustness to reduced current resolution. They do not establish universal transfer to unseen motor instances; broader deployment requires motor-specific calibration or more diverse multi-motor training data. Full article

Electrochemical CO₂ reduction reaction (ECO₂RR) is a promising technology for converting rapidly rising atmospheric CO₂—driven by fossil fuel consumption and industrial processes—into a circular carbon economy. In particular, ECO₂RR is expected to enable renewable-based long-duration energy storage (LDES) systems through the highly efficient conversion of CO₂ into high-value multi-carbon (C2⁺) compounds. However, scaling ECO₂RR to the industrial level remains challenging because, under high-current operation, the CO₂ consumption rate exceeds its supply rate, causing a sharp decline in local CO₂ concentration. The resulting increase in local pH promotes both carbonate formation and electrode flooding within the gas diffusion electrode (GDE), creating a wetting-induced mass transfer bottleneck. To address this challenge, this review categorizes and analyzes recent strategies for CO₂ microenvironment engineering that overcome mass transfer limitations at high-current densities, focusing on two complementary approaches: (1) enhancing gas-phase CO₂ supply while suppressing flooding through nano/microscale hydrophobic polymers and structural gradient designs, and (2) enhancing active CO supply in the liquid phase through electrolyte composition optimization. We further show that these strategies are not mutually independent but create complementary structural and chemical synergies, and we propose future directions for simultaneously improving high-current operability and C2⁺ product selectivity. Full article

Soil degradation is commonly quantified using state or trend indicators, but these measures do not show whether a shortfall has accumulated through time, created a deferred obligation, or transferred costs and risks across actors, places, sectors or generations. This Concept Paper addresses that gap by developing Soil Security Debt as a preliminary accounting architecture anchored in five Soil Security dimensions: capacity, condition, capital, connectivity and codification. A purposive synthesis of soil assessment, environmental debt, Land Degradation Neutrality, ecosystem accounting and environmental liability identifies transferable principles. The architecture separates native-unit indicator gaps, normalised dimension accounts, gross incurrence, verified repayment and outstanding balances. Biophysical, ecological, soil-carbon, water, economic, social and governance debt are overlapping interpretive lenses; intergenerational transfer describes the incidence of outstanding liabilities. A hypothetical calculation demonstrates internal calculability, while retrospective mappings of erosion and soil-carbon studies illustrate how empirical evidence could populate parts of the ledger. The framework is not an empirically validated universal index: operational use requires context-specific indicators, defensible references, uncertainty propagation, sensitivity analysis and longitudinal validation. Soil Security Debt offers a testable way to distinguish a current adverse state from an accumulated or transferred liability and make prevention, restoration and residual loss explicit in assessment and policy. Full article

Against the background of resource constraints and the difficulty of independent green technology innovation, green technology transfer (GTT) provides an important pathway for listed port companies to reduce energy-related emissions from their operational activities and advance low-carbon transformation. Based on panel data from 19 listed Chinese port companies from 2011 to 2024, this paper examines the effect and mechanisms of GTT on energy-related operational port carbon emissions (EOPCE) from both theoretical and empirical perspectives. The results show that (1) GTT significantly reduces EOPCE, and this finding remains robust after a series of robustness and endogeneity tests. (2) Mediation analysis indicates that GTT reduces EOPCE by promoting a cleaner energy consumption structure and technological progress. (3) Moderation analysis shows that environmental regulation, regional innovation support, and port financial health significantly strengthen the negative effect of GTT on EOPCE, while no statistically significant moderating effect of port technology absorptive capacity is identified under the current sample and proxy measure. (4) Heterogeneity analysis reveals that the effect of GTT on EOPCE varies across port regions and digitalization levels. Full article

While Artificial Intelligence (AI) has transformed materials discovery, the primary bottleneck to technological impact remains the transition from lab-scale synthesis to robust, industrial-scale manufacturing. Most promising materials perish in this depth, which is referred as the “valley of death”. The current review consolidates and critically evaluates the emerging ecosystem of AI-driven strategies and frameworks designed specifically to bridge this “lab-to-fab” gap. The review shifts our attention from property prediction to the engineering-driven problems of manufacturability. Furthermore, the review discusses the main obstacles to scaling the production of materials, such as reproducibility, process optimization in the context of uncertainty, and techno-economic viability, as well as the AI approaches being developed to overcome them. This includes Natural Language Processing (NLP) for method extraction, graph neural networks for reaction modeling, reinforcement learning for process control, Bayesian optimization for definition of process windows, and integrated AI–Techno-Economic Analysis (TEA) frameworks. Equally importantly, the review examines the principal failure modes that constrain practical deployment, including out-of-distribution generalization, incomplete and non-transferable literature-derived data, simulator-to-plant mismatch, uncertainty miscalibration, and the continued need for expert oversight. The article concludes with a forward-looking roadmap for the future of AI in chemical and materials engineering. The proposed conclusion is defined by a paradigm shift from simply finding new materials to creating viable, economical, and scalable pathways to produce them, thereby enabling a new era of synthesis-aware materials innovation. Full article

Mediterranean vernacular masonry houses embody centuries of accumulated environmental knowledge, yet many are currently threatened by abandonment, together with functional obsolescence. This study proposes a framework for the conservation-oriented upgrading of 19th-century Mediterranean stone houses that reconciles heritage preservation with contemporary environmental requirements. Using the vernacular settlement of Korogonianika, Peloponnese, Southern Greece, as a case study, the research combines documentation and analysis of the existing heritage regulatory framework, construction material discussions, building condition assessments, and outdoor microclimate evaluations through ENVI-met simulations. The study concludes with the development of conservation-compatible energy retrofit strategies. The microclimatic analysis examines representative winter and summer conditions to identify the influence of settlement morphology, orientation, building density, and traditional stone construction on thermal comfort. Results demonstrate that the fabric of the village plays an important role in thermal comfort. In particular, high thermal mass and passive bioclimatic characteristics of the settlement moderate seasonal thermal stress. These findings inform restoration interventions that preserve the environmental intelligence embedded in the vernacular architecture while improving building resilience. The proposed framework underscores that effective upgrading should be guided by both heritage values and local microclimatic conditions, offering a transferable methodology for the conservation and sustainable rehabilitation of Mediterranean vernacular masonry houses. Full article

Bearings are crucial components in motor bearing transmission systems because they reduce friction and support loads. Therefore, bearing fault diagnosis is particularly important. This paper proposes a fault diagnosis method for motor bearing transmission systems based on acoustic signals and acoustic feature fusion. The complete acoustic signal is segmented, and seven time-series imaging methods, including Gramian Angular Difference Field (GADF) and Gramian Angular Summation Field (GASF), are used to convert one-dimensional signals into two-dimensional feature maps. The generated images are then input into a RegNet-based transfer learning network. According to the single-feature training results, the feature map datasets ranking in the top two, three, and four are selected for feature fusion to construct new datasets. The results obtained under the present experimental setup indicate that acoustic feature fusion can improve the diagnostic performance compared with using a single feature map dataset. After comprehensive comparison, the dataset generated by summing two feature maps, namely STFT and Mel spectrogram, is selected as the final input dataset in this study. The current work focuses on a fixed operating condition, and further validation under different speeds, loads, sensor positions, background noise levels, bearing models, and defect severities will be conducted in future work. Full article