Search Results (638)

The transition from conventional silica nanoparticle (SiNP) production based on purified alkoxysilanes and high-temperature flame hydrolysis of silicon tetrachloride to renewable and waste-derived silicon resources requires more than precursor substitution. It requires a mechanistic understanding of how feedstock mineralogy, silicon speciation, impurity chemistry, and processing history propagate through dissolution, nucleation, condensation, gelation, aging, drying, and pore evolution to determine material performance, environmental burden, and manufacturing feasibility. Although previous reviews have established the technical feasibility of producing silica from secondary resources, their predominant organization by feedstock, synthesis route, or application provides limited ability to explain why nominally similar processes generate materials with markedly different structural and functional properties. This review addresses these through a resource-pull, feedstock-to-function framework that links resource chemistry and process design to critical material attributes, application-specific specifications, sustainability, and scale-up requirements. Agricultural residues, industrial by-products, geothermal resources, waste glass, and fluorosilicate streams are critically compared according to silicon form and phase, reactivity, impurity profile, compositional variability, purification demand, and attainable product quality. Particular attention is given to waste-derived alkaline silicate systems, in which molecular, oligomeric, and colloidal silica coexist and therefore require characterization beyond bulk SiO₂ concentration. Established and emerging processing strategies, including controlled combustion and alkaline extraction, alkali fusion, ambient-pressure drying, microwave and mechanochemical activation, biogenic and biomimetic templating, and continuous processing, are evaluated according to their mechanistic effects, technological maturity, structural control, and demands for energy, reagents, water, solvents, effluent treatment, and capital. Across these routes, gelation and aging emerge as critical transfer stages through which feedstock composition is translated into network connectivity, pore architecture, shrinkage behavior, and ultimately functional performance. Evidence from secondary-source aerogels further shows that properly controlled waste-derived systems can attain BET surface areas of approximately 350–500 m² g⁻¹, within the textural range of many alkoxide-derived materials, indicating that feedstock variability, impurity management, and process control are more important constraints than an inherently lower performance ceiling. On this basis, this review proposes a minimum evidence framework comprising feedstock traceability, intermediate-speciation and colloidal characterization, silicon mass balance, gelation and aging metrics, application-specific qualification criteria, performance-normalized life cycle and techno-economic assessment, process analytical control, and staged pilot validation. Collectively, these principles provide a mechanistically grounded basis for moving sustainable silica synthesis beyond isolated proof-of-concept demonstrations toward reproducible, scalable, application-matched, and commercially credible manufacturing platforms. Full article

Mine leachate and saline industrial wastewater streams are often treated as liabilities to be remediated or disposed of. These flows often contain substantial water and dissolved mineral resources that can be reclaimed. In this work, a waste-heat-assisted falling-film evaporation reactor was developed and assessed for application as a pre-concentration step before water and mineral recovery processes. Two case studies were considered: synthetic saline wastewater containing 80 g/L Na₂SO₄ and 70 g/L NaCl for salt recovery, and iron-rich mine water containing approximately 4000 mg/L Fe²⁺, 95 mg/L Fe³⁺, and 13,000 mg/L acidity as CaCO₃ for downstream pigment and magnetite recovery. Saline water or mine leachate flows down a bank of vertical conduit pipes as a thin film while air flows through the pipe cores. Heat is transferred to the system from industrial waste gas externally. Psychrometric relationships, heat transfer, energy balances, and techno-economic analysis were used to assess the impact of air temperature, conduit diameter, column height, pipe material, and waste-gas temperature on overall reactor performance. Experiments were carried out to confirm expected psychrometric operation and establish appropriate operating temperatures while confirming the impact of conduit geometry on heat-transfer characteristics. A benchmark case of design evaporation rate equal to 100 L/h was chosen for comparison of all tests. Dry air operation was shown to be technically possible but severely limited by the moisture capacity of air; at 26 °C and 101.3 kPa, approximately 205,000 m³/h of air was required. When using industrial waste heat, the operation changed from psychrometric/mass-transfer-limited to heat-transfer-controlled. Using waste gas entering at 144 °C and exiting at 80 °C reduced airflow requirements to approximately 880 m³/h, allowing a much more compact reactor design with approximately 635 (12 mm diameter) conduit pipes. Relative to the 40 °C air benchmark, electrical power was reduced from approximately 24.7 kW to 2.9 kW, and screening-level reactor cost by ~84%. Findings demonstrated that appropriate waste heat enables the application of evaporation if there is sufficient local heat flux. Smaller conduit diameters, sufficient column height, and greater waste-gas inlet temperatures were all beneficial. Choice of material required trade-offs between heat-transfer coefficient, corrosion, and material cost. Full article

Culvert construction at stream crossing sites can lead to zones of high-velocity water flow which can disrupt the dispersal and connectivity of species of greatest conservation need (SGCN) in Texas. To help inform effective culvert design, the swimming performance of the following seven fish species has been measured, the first three of which are SGCN themselves, and the last four serve as hosts for glochidia of SGCN mussels (mussel genera indicated in parentheses): Colorado Roundnose Minnow, Texas Shiner, Headwater Catfish, Largemouth Bass (host for Lampsilis spp.), Green Sunfish (host for Lampsilis spp.), Channel Catfish (host for Cyclonaias spp.) and Blacktail Shiner (host for Fusconaia spp.). The primary objective was to measure the critical swimming speeds (U_crit) under a range of relevant temperatures (15, 22.5, and 30 °C) to be used in site-specific calculations of culvert water velocities (Vf). A secondary objective was to collect additional physiological endpoints of relevance to overall swimming performance, including maximum burst swimming speed (U_max), metabolic rate measurements (i.e., standard (SMR), maximum (MMR) and aerobic scope (AS)) and calculations of cost of transport (COT) and optimal swimming speed (U_opt). As expected, U_crit tended to increase with increasing temperature for several species with metabolic rate measurements following congruent trends, whereas U_max exhibited thermal independence for all species. Full article

As the global energy sector and maritime industry transition toward carbon neutrality, Carnot batteries have emerged as a critical technology for flexible, long-duration energy management. Carnot batteries, which operate on a Power-to-Heat-to-Power principle, present a highly promising alternative to conventional electrochemical batteries. The present study provides a review of Carnot battery architectures, systematically evaluating their thermodynamic cycles, working fluids, Thermal Energy Storage media and key turbomachinery components. A comparative assessment of the current literature illustrates that system selection requires balancing round-trip efficiency, Energy Storage Density and Technology Readiness Level. According to the findings of the present study, high-temperature Brayton cycles offer robust baseline efficiencies of 60–80% whereas subcritical Rankine cycles benefit from commercial maturity and can achieve efficiencies exceeding 200% when integrated with cryogenic heat sinks like LNG. It should be clarified that efficiency values exceeding 100% represent “Apparent Round-Trip-Efficiencies (RTE)” resulting from the thermodynamic contribution of external exergy streams, such as LNG cryogenic cold, rather than standalone cycle efficiencies, which are strictly below 100%. In addition, volumetric energy density varies drastically based on the physical phase of the storage medium, scaling from under 1 kWh/m³ for unpressurized water to over 385 kWh/m³ for advanced thermochemical systems. Although most configurations currently remain in the prototyping phase, the technology holds transformative potential for the maritime sector. Carnot batteries can deliver a self-contained, zero-emission electrical power supply to cover the vessel’s electrical load requirements during harbor stays and transit within Emission Control Areas (ECAs) by dynamically capturing and storing shipboard waste heat during open sea transit. Full article

Understanding how urbanization modifies stream thermal regimes is essential for assessing freshwater ecosystem responses to climate variability and land-use and land-cover (LULC) change. This study investigated air temperature (AT)–water temperature (WT) relationships at annual, monthly, and diurnal timescales in two adjacent, relatively flat watersheds with contrasting urbanization levels in North Central Texas: the urbanized Doe Branch and less urbanized Little Elm Creek during 2012–2021. A single harmonic analysis was applied to characterize annual and diurnal thermal patterns, including mean temperature, amplitude, and phase, while statistical analyses were used to evaluate seasonal and daily thermal variability and peak timing. At the annual scale, AT and WT metrics were strongly correlated at both sites (r = 0.85–0.94, p < 0.01) indicating that atmospheric conditions were the dominant control of annual stream temperature variability. Annual mean WT increased with AT, suggesting strong air–water thermal coupling and the potential for warmer stream temperatures under future climate warming. However, Doe Branch exhibited higher annual mean WTs, delayed seasonal peak WTs, and reduced annual temperature ranges compared with Little Elm Creek, reflecting the influence of urban watershed characteristics on seasonal thermal responses. At the diurnal scale, daily mean WT remained strongly coupled with daily mean AT, whereas daily temperature range and peak timing showed weaker relationships with AT. The greater variability in peak WT timing at Doe Branch suggests that short-term stream thermal dynamics were influenced by additional watershed characteristics beyond atmospheric forcing alone. Full article

Forest fires are a major environmental concern in Northern Thailand, contributing to ecosystem degradation, biodiversity loss, and seasonal air pollution. This study identified the environmental factors influencing forest fire occurrence and developed a forest fire susceptibility map using an integrated Geographic Information System (GIS) and Logistic Regression (LR) framework in Chom Thong District, Chiang Mai Province, Thailand. Fire occurrence data were derived from Visible Infrared Imaging Radiometer Suite (VIIRS) active fire hotspots detected by the Suomi National Polar-orbiting Partnership satellite (Suomi-NPP satellite) during 2023–2025. A total of 1674 hotspots were identified (616 in 2023, 889 in 2024, and 169 in 2025). Ten environmental variables, including elevation, slope, aspect, Topographic Wetness Index (TWI), stream density, rainfall, Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Land Surface Temperature (LST), and land-use, were analyzed. The LR model was trained using 2293 training samples (70%) and validated using 983 samples (30%). The results revealed that slope, rainfall, stream density, and LST were significant predictors of forest fire occurrence, with deciduous and evergreen forests exhibiting the highest susceptibility among land-use classes. The resulting forest fire susceptibility map classified 235.12 km² (21.16%) and 204.16 km² (18.38%) of the district as very high and high susceptibility, respectively, primarily in mountainous forest areas. The model achieved an overall accuracy of 77.5% and an Area Under the Curve (AUC) value of 0.852, indicating good predictive performance. Furthermore, the proposed Geographic Information System-Logistic Regression (GIS-LR) framework provides an interpretable and transferable approach for forest fire susceptibility assessment and generates spatial information that can support forest fire prevention, resource allocation, and environmental management in Northern Thailand and other fire-prone regions. Full article

Real-world fault data for hydrogen-cooled turbogenerators are scarce and largely proprietary, which hinders data-driven health assessment aligned with severity standards. This paper proposes a standards-aligned, multi-source ordinal fusion framework and demonstrates it, as a proof of concept, on a reproducible four-domain surrogate collection. The collection combines public industrial datasets—SKAB (cooling loop), UCI-WWT (water chemistry), CARE Wind Farm A (electrical and thermal conditions)—and a physics-informed hydrogen-side stream derived from Henry’s law and a continuously stirred tank reactor (CSTR) mass balance, joined by paired sampling. The collection is a methodological benchmark, not a validated diagnostic for any specific machine. A dual-head classifier supervised by a hybrid CORN + EMD ordinal loss, a multi-stream fusion backbone, and a calibrated ensemble with per-model temperature scaling are aligned with the four-level GB/T 43188-2023 scheme (Normal/Attention/Abnormal/Serious). All methods are evaluated under a unified protocol (mean ± standard deviation over three seeds; the deterministic calibrated ensemble is reported as a single value). On 600 fused test samples, the ensemble reaches F1-macro 0.5349, Accuracy 0.6717, Cohen’s κ = 0.4713, and quadratic-weighted kappa (QWK) 0.5948, improving F1-macro by +22.4 pp over the strongest full-scale single-source baseline (InceptionTime on CARE, trained under the identical protocol), with larger rank-aware gains (+30.4 pp on κ, +36.2 pp on QWK). It further improves by +8.9 pp over the strongest cross-entropy fusion baseline retrained under the identical protocol. The results support the methodological claim that fusing four heterogeneous monitoring domains under rank-aware ordinal supervision yields coherent, standards-aligned severity grades, offering a reproducible benchmark and methodology whose transfer to real hydrogen-cooled turbogenerators remains to be validated on co-recorded plant data. Full article

Water pollution can compromise the ecological integrity of freshwater habitats, thereby exposing freshwater communities to sources of pollution such as wastewater and agricultural and industrial discharges. Diatoms are key organisms because of their role as primary producers; thus, they have been regularly used as bioindicators to assess water quality. The diatom assemblages were collected from the surface of small stones in four rivers (El Carmen, Jipiro, San Simón, and Curitroje) across three zones defined according to a land-use gradient (high, medium, and low). A total of 54 diatom species were recorded. The El Carmen stream showed the highest total richness (29 species), followed by Curitroje (21), Jipiro (19), and San Simón (11). The results revealed significant changes in diatom richness, abundance, diversity indices, trophic index (IT) and community structure associated with both stream and zone. Following a similar pattern, temperature, conductivity, TDS (total dissolved solids), and pH also strongly influenced community composition. Achnanthidium subatomus, Sellaphora lanceolata, Odontidium mesodon were indicators of the high zone and show a general preference for zones characterized by conserved riparian vegetation, fast, clear and oxygenated water. On the other hand, Gomphonema reichardtii, Rhopalodia musculus, Gomphonema clavatulum, Gomphonema subclavatum, Gomphonema variostriatum, Eunotia incisa were indicators of a low zone with heavy organic pollution, water pollution, and environmental changes in temperature, conductivity, TDS and pH. Full article

Photovoltaic–thermal (PVT) collectors co-generate electricity and heat—natural front ends for thermochemical energy storage (TCES)—provided the heat transfer fluid stays above the reactor’s desorption temperature. Using an eight-node model of a 0.6834 m² collector at 8.64° N whose thermal core is partially validated against measured data from the same tropical–coastal site (rooftop PV module temperature, RMSE 3.8 °C; prototype absorber-to-water heat transfer, RMSE 1.3 °C), flow-regulated to the ≈95 °C SrCl₂/NH₃ desorption threshold, we quantify the energy and exergy delivered for charging under tropical–monsoon intermittency. The 95 °C setpoint operation, the ≈5.3 h charging window, and all reported exergy yields are simulated: the built prototype delivered hot water peaking at 79 °C and did not reach the 95 °C setpoint. On a measured clear-sky day (clearness index K_t = 0.52), the collector yields 1.38 kWh of energy but only 0.43 kWh of exergy (first-law efficiency ≈ 38%; gross exergy efficiency ≈ 13%); across a 30-seed synthetic-intermittency ensemble, the exergy yield is 0.678 kWh at ≈14% gross exergy efficiency (≈52% combined first-law efficiency). In both cases, the thermal stream dominates the energy output while the electrical stream dominates the exergy output—on the sunlit day, the exergy is about 80% electrical—because 95 °C heat carries a Carnot factor (exergetic quality factor, 1 − T_a/T₇, at the instantaneous ambient dead state) of only ≈0.18 and an integrated Bejan/Kotas thermal-exergy quality of only ≈0.09. The controller holds the outlet within 1.4 K of the setpoint for ≈5.3 h, whereas no fixed flow in the 0.5–5.0 L min⁻¹ range ever reaches it: feedback control is a structural enabler, not an optimisation. On overcast days, the threshold is never reached and charging heat collapses to zero, leaving a PV-only generator. Exergy delivery is nonetheless nearly controller-independent: the accumulated exergy delivery deficit after a 50% irradiance drop is 937 kJ, a controller-independent value changing only 1.3% across a systematic 4 × 4 gain sweep (K_p 0.33–2.7×, K_d 0.25–5× of nominal), and predictive control improves it by ≤1%. For PVT–TCES at this scale, the decisive lever is deployability, not control sophistication. Full article

Directing a stream of air across the tooth when light curing resin-based composites (RBCs) may affect their degree of conversion (DC), maximum rate of polymerization (RP_max), and in vitro intrapulpal temperature. Methods: Filtek One Bulk Fill and VisCalor bulk were preheated according to the manufacturer’s instructions and used to fill a Class I cavity in a molar at 32 °C. A stream of air at either 15 or 30 psi was directed across the tooth from an air-water syringe positioned 1 cm from the buccal surface. The RBCs were light-cured for 20 s using the Bluephase N, and the DC and RP_max were determined from real-time FT-IR data. A T-type thermocouple positioned inside the pulp chamber recorded the temperature. DC and RP_max data were analyzed using one-way ANOVA, whereas temperature was analyzed using two-way ANOVA, followed by Tukey post hoc tests. Results: Directing a stream of air at the tooth produced no significant differences in the DC and RP_max. The temperature change (ΔT) decreased compared to when no air was delivered. No significant difference in ΔT was found between the two air pressures. Conclusions: Directing a stream of air across the tooth when the preheated RBC was inserted did not affect the polymerization kinetics. The air stream reduced the temperature rise inside the pulp chamber as the RBC was light-cured. Clinical Significance: Directing a stream of air across the tooth at either 15 psi or 30 psi during light curing is an easy method to reduce the temperature increase inside the pulp chamber without affecting the polymerization kinetics of the evaluated preheated RBCs in this in vitro model. Full article

Copper smelter slag represents a significant secondary resource of critical metals, while flotation tailings serve as an abundant sulfur-bearing waste stream. This study investigated a waste-on-waste sulfation roasting approach for the selective recovery of Cu, Ni, and Co from fayalite copper smelter slag using flotation tailings as an in situ sulfur source and sodium metabisulfite (SMBS, Na₂S₂O₅) as a sulfation promoter. The effects of roasting temperature, roasting time, slag-to-tailings ratio, SMBS dosage, and water-leaching conditions were systematically evaluated. Under the optimum conditions of a slag-to-tailings ratio of 1:1, roasting at 600 °C for 4 h with 30 wt% SMBS addition, followed by water leaching at 25 °C for 2 h, extraction efficiencies of 85.5% Cu, 81.6% Ni, and 87.1% Co were achieved, while Fe dissolution remained below 5%, demonstrating high selectivity. Phase and microstructural analyses by XRD, FTIR, SEM, and TG–DTA revealed that pyrite oxidation generated sulfur oxides required for metal sulfation, whereas SMBS promoted sulfur release and sulfate stabilization, enhancing sulfation efficiency. Thermodynamic analysis further confirmed the feasibility of sulfide oxidation and sulfate formation within the investigated temperature range. The results demonstrate that the synergistic use of tailings and SMBS enables efficient low-temperature sulfation roasting of fayalite slag and provides a promising route for the selective recovery of valuable metals from metallurgical waste materials. Full article

Satellite -derived environmental features can predict county-level life expectancy (LE) across the contiguous United States with a mean absolute error of 1.08 years over two decades, without using any census or sociodemographic inputs. We assembled 61,680 county-year observations across 3084 counties from 2000–2019, integrating features from 11 satellite and gridded data streams. The data streams include the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and vegetation indices, Sentinel-1 synthetic aperture radar, Sentinel-2 and Landsat optical imagery, the United States Department of Agriculture (USDA) Cropland Data Layer, the European Commission Joint Research Centre (JRC) Global Surface Water layer, the Copernicus Digital Elevation Model, the European Space Agency Climate Change Initiative (ESA CCI) soil moisture record, and the Food and Agriculture Organization (FAO) gridded livestock densities. After a supervised pruning step that removed low-importance variables, a Random Forest regressor was trained and evaluated using 5-fold cross-validation grouped by county. The grouping places all 20 years of each county exclusively in either the training set or the test set, which prevents spatial information leakage between folds. Coefficient of determination, mean absolute error, and root mean squared error are reported as $R^2=0.631\pm 0.013$, MAE $=1.08\pm 0.02$ years, and RMSE $=1.48\pm 0.04$ years. Moran’s I, a measure of residual spatial autocorrelation, is $0.0988$ ($p=0.001$), which supports geographic generalisation. Multimodal fusion reduces unexplained variance by approximately one-third relative to the strongest single-modality baseline (MODIS land surface temperature alone, $R^2=0.442$). TreeSHAP attribution analysis reveals a feature hierarchy in which nighttime land surface temperature features carry roughly $6.16\times$ the cumulative attribution weight of all daytime channels combined. The model response shows a protective inflection near a minimum overnight temperature of about 7.5 °C. Because all input streams are globally available, the framework is architecturally extensible to regions where civil registration and vital statistics systems are incomplete; however, the trained model and its thresholds require recalibration against local mortality data before application outside the contiguous United States. With that caveat, the approach supports satellite-based monitoring of United Nations Sustainable Development Goal (UN SDG) Target 3.9. Full article

This study investigated density-driven mixing and stratified flow dynamics in Paldang Reservoir, a river-type reservoir formed at the confluence of the South Han River, North Han River, and Gyeongan Stream in South Korea. High-resolution field observations were conducted under varying hydrologic and hydraulic conditions using an Acoustic Doppler Current Profiler (ADCP) and multi-parameter water quality sensors (EXO2). Spatial distributions of flow velocity, water temperature, and electrical conductivity (EC) were analyzed to evaluate tributary interaction and mixing behavior within the reservoir. Distinct spatial mixing structures associated with tributary inflow heterogeneity and hydraulic operation conditions were identified. During flood-season conditions, highly turbid and high-conductivity inflow from the South Han River propagated beneath the North Han River inflow, generating density-driven lower-layer intrusion near the confluence region. Under intermittent discharge conditions at the Cheongpyeong Dam, unstable upper- and lower-layer separation structures and localized reverse-flow behavior developed. In contrast, continuous discharge conditions promoted stable tributary propagation and persistent stratified mixing structures. Case-based Richardson number (Ri) estimates further indicated localized shear-driven mixing at low-Ri inflow sections and relatively stable stratification at high-Ri sections, providing quantitative support for the observed spatial heterogeneity in density-driven mixing. Overall, spatial mixing in Paldang Reservoir was governed by tributary density contrasts and further shaped by hydraulic operation conditions. These findings improve understanding of density-driven mixing processes in river-type reservoirs under varying hydraulic conditions. Full article

Dissolved oxygen (DO) is a critical water quality parameter in aquaculture systems. Low DO events can stress, limit the growth of, or even cause mortality of aquatic life in aquaculture systems and require rapid management decisions. This study presents a process-based approach for short-term DO forecasting that is intended to support rapid deployment and transferability across various aquaculture systems. Future DO is computed using a mass-balance equation driven by daily stream metabolism and reaeration coefficients estimated from the previous 24 h of weather and water observations. These coefficients are combined with the next day’s observed water temperature, atmospheric pressure, photosynthetically active radiation, and salinity to predict DO 24 h ahead under idealized measured-input conditions with a ten-minute resolution. Model performance was evaluated across multiple aquaculture ponds with varying aeration techniques by assessing prediction accuracy of daily DO minimums using a safety-based metric and full-day DO trajectories using root mean square error. The model successfully predicted 91.77% of DO drops below 6 mg/L within 1 mg/L in a consistently aerated artificial pond and achieved high success in a natural watershed system. Performance was reduced in systems with highly variable aeration. Prediction accuracy was the highest in surface locations away from aerators. These results indicate that a minimal-history process-based framework can identify low DO risk under idealized measured-input conditions, particularly in surface locations away from aerators and in systems with constant or natural aeration. Full article

Global satellite missions with the capability to measure ocean surface currents are continually being proposed. This new observation type is expected to significantly improve ocean model analysis and forecast skill. The potential impact of assimilating sea surface currents from the proposed wide-swath Ocean Dynamics and Surface Exchange with the Atmosphere (ODYSEA) mission is investigated in this study. An Observing System Simulation Experiment (OSSE) is set up with a 1 km Navy Coastal Ocean Model (NCOM) analysis-forecasting system in the Gulf of America domain over a 4-month time period. When compared to an experiment with only the standard data streams of temperature, salinity, and sea surface height anomaly observations from in situ and satellite platforms assimilated, the inclusion of ODYSEA-like sea surface current observations leads to a 13% and 17% reduction in the domain and time averaged root mean squared error (RMSE) for surface u and v components, respectively, as well as an improvement in the current velocity throughout the upper water column. The assimilation of the sea surface current observations also leads to an improvement in the model sea surface height, although there is a negligible to slight degradation in the temperature and salinity at depth, which is likely due to the explicit geostrophic assumption made within the velocity assimilation methodology. Full article