Search Results (10,624)

The photocatalytic activity of Bi₂WO₆ Aurivillius phase has been widely exploited for the degradation of a wide range of gaseous and aqueous molecules, as well as microorganisms, under the influence of visible irradiation. Strategies for the development of doped and co-doped bismuth tungstate materials require the thermodynamic data on this phase. The heat capacity of bismuth tungstate, Bi₂WO₆, was investigated using a DSC microcalorimeter on polycrystalline powder samples in the temperature range from 313 to 1103 K (40–830 °C) in two separate runs. The samples were synthesized by solid-state reaction from pure binary oxides at 1033 K (760 °C) in a platinum crucible with cover. The high temperature C_p(T) data were fitted by the Maier–Kelley equation and, from this relation, the standard molar heat capacity of γ-Bi₂WO₆ polymorph was estimated to be at 298.15 K 176.8 ± 3.9 J·K⁻¹·mol⁻¹. A reversible second-order transition of Bi₂WO₆ phase was observed in the experimental temperature range, with a peak close to 940 K (667 °C). Additionally, the extrapolation of C_p(T) to 0 K was proposed using a method based on the multiple Einstein model. Thermodynamic properties (heat capacity C_p(T), entropy S°(T), enthalpy H°(T), Gibbs energy G°(T)) of crystalline γ-Bi₂WO₆ were calculated in the temperature range of 298.15–1123 K (25–850 °C). Full article

A modular, multi-functional (encompassing data acquisition, management, preprocessing, and transmission) sensing (MMFS) system based upon the Internet of Things (IoT) paradigm is discussed in this paper with the goal of continuous real-time, multi-sensor and multi-location monitoring of aircraft (including drones) structural performances during flight. According to industrial and system requirements, a microcontroller and four sensors (strain, acceleration, vibration, and temperature) were selected and integrated into the system. To enable the determination of potential in-flight failures and estimates of the remaining useful service life of the aircraft, resistance strain gauge networks, piezoelectric sensors for capturing structural vibrations and impact, accelerometers, and thermistors have been integrated into the MMFS system. Real flight tests with Evektor’s Cobra VUT100i and SportStar RTC aircraft have been undertaken to demonstrate the features of recorded data and provide requirements for the MMFS functional design. Real flight test data were analysed, indicating that a sampling rate of 1000 Hz is necessary to balance representation of relevant features within the data and potential loss of quality in fatigue life estimation. The design and evaluation of the performance of a prototype (evaluated via representative stress/strain experiments using an Instron Hydraulic 250 kN machine within laboratories) are detailed in this paper. Full article

High-resolution air temperature (AT) data is essential for understanding urban heat dynamics, particularly in urban areas characterised by complex microclimates. However, AT is rarely available in such detail, emphasising the need for its modelling. This study employs a Random Forest regression framework to predict 20 m resolution AT maps across Milan, Italy, for 2022. We focus on seasonal heatwave periods, identified from a long-term climate reanalysis dataset, and multiple diurnal and nocturnal phases that reflect the daily evolution of AT. We predict AT from a high-quality dataset of 97 authoritative and crowdsourced stations, incorporating predictors derived from geospatial and Earth Observation data, including Sentinel-2 indices and urban morphology metrics. Model performance is highest during the late afternoon and nighttime, with an average $R^2$ between 0.33 and 0.37, and an RMSE between 0.7 and 1.4 °C. This indicates modest, yet reasonable agreement with observations, given the challenges of high-resolution AT mapping. Daytime predictions prove more challenging, as noted in previous studies using similar methods. Furthermore, we explore the potential of hyperspectral (HS) data to estimate surface material abundances through spectral unmixing and assess their influence on AT. Results highlight the added value of HS-derived material abundance maps for insights into urban thermal properties and their relationship with AT patterns. The produced maps are useful for identifying intra-urban AT variability during extreme heat conditions and can support numerical model validation and city-scale heat mitigation planning. Full article

This study presents a molecular dynamics (MD) investigation of water evaporation in copper nanochannels, with a focus on accurately modeling copper–water interactions through forcefield calibration. The TIP4P/2005 water model was coupled with the Modified Embedded Atom Method (MEAM) for copper, and the oxygen–copper Lennard–Jones (LJ) parameters were systematically tuned to match experimentally reported water contact angles (WCAs) on Cu (111) surfaces. Contact angles were extracted from simulation trajectories using a robust five-step protocol involving 2D kernel density estimation, adaptive thresholding, circle fitting, and mean squared error (MSE) validation. The optimized forcefield demonstrated strong agreement with experimental WCA values (50.2°–82.3°), enabling predictive control of wetting behavior by varying ε in the range 0.20–0.28 kcal/mol. Using this validated parameterization, we explored nanoscale evaporation in copper channels under varying thermal loads (300–600 K). The results reveal a clear temperature-dependent transition from interfacial-layer evaporation to bulk-phase vaporization, with evaporation onset and rate governed by the interplay between copper–water adhesion and thermal disruption of hydrogen bonding. These findings provide atomistically resolved insights into wetting and evaporation in metallic nanochannels, offering a calibrated framework for simulating phase-change heat transfer in advanced thermal management systems. Full article

Climate change (CC) is a growing threat to water security in agricultural regions, particularly in semi-arid areas. This study evaluates the impact of CC on reference evapotranspiration (ET₀) in Irrigation District 001 Pabellón de Arteaga, Aguascalientes (DR 001), with the aim of strengthening its sustainable management. We used historical data (2002–2023) and future projections (2026–2100) from 22 CMIP6 global climate models, previously corrected for bias under the scenarios SSP2-4.5 and SSP5-8.5. The evaluation of the correction methods showed that PTF-scale performed best in correcting precipitation, solar radiation, relative humidity, and wind speed, although the latter showed a low correlation. The maximum, mean, and minimum temperatures showed a better fit with the RQUANT and QUANT methods. The ACCESS-ESM1-5 model displayed the best performance in six of the nine corrected variables; therefore, it was the most suitable model to estimate ET₀. The uncertainty analysis showed that the FAO-56 method, although characterized by a higher current error, is more robust for future projections. A progressive increase in ET₀ is projected under both CC scenarios, ranging from 13.0 to 15.8% (SSP2-4.5), and between 12.5 and 20.4% (SSP5-8.5). The results highlight the urgent need to implement water adaptation strategies in DR 001 and make informed decisions to achieve resilient water management in the face of CC. Full article

Polyphenols are chemical compounds found in plants, and coffee is an important source of them. The objective of the study was to evaluate the kinetics of polyphenol degradation in a blend of specialty coffee (green, roasted and roasted–ground beans), packaged in eight different packages, under accelerated storage conditions. The samples were stored at 40, 50 and 60 °C for 12, 8 and 4 days, respectively. The degradation kinetics were modelled based on chemical kinetics and determination of the reaction order. Using the Arrhenius model, the rate constants (k) and activation energies (E_a) were estimated, which were then used to calculate and predict the half-life. The degradation followed zero-order kinetics. The rate constant (k) varied between 0.437 and 9.534 days⁻¹ (40–60 °C). The E_a ranged from 49.321 to 118.04 kJ*mol⁻¹. The average shelf life shows a direct correlation with the characteristics and barrier properties of the packaging, with the longest storage times for daily storage at 25 °C being for vacuum-packed green beans (27.16 months), vacuum-packed roasted beans (3.14 months) and roasted ground coffee in trilaminate foil with a valve (40.21 months). Polyphenol retention decreased significantly with increasing temperature. For green bean, roasted bean and roasted ground coffee, the packaging that showed the best protection for the coffee was vacuum packaging and trilaminate with valve respectively, being crucial for preserving these bioactive compounds. Full article

Industrial processes governed by food safety regulations, such as high-temperature short-time (HTST) pasteurization, rely on continuous sensor monitoring to ensure compliance with standards like Hazard Analysis and Critical Control Points (HACCP). However, extracting actionable process insights from raw sensor data remains a non-trivial task, largely due to the continuous, multivariate, and often high-frequency characteristics of the signals, which can obscure clear activity boundaries and introduce significant variability in temporal patterns. This paper proposes a process mining framework to extract activity-based representations from multivariate sensor data in a pasteurization scenario. By modelling temperature, pH, conductivity, viscosity, turbidity, flow, and pressure signals, the approach segments continuous data into discrete operational phases and generates event logs aligned with domain semantics. Unsupervised learning techniques, including Hidden Markov Models (HMMs), are used to infer latent process stages, while domain knowledge guides their interpretation in accordance with critical control points (CCPs). The extracted models support conformance checking against HACCP-based procedures and enable predictive process-monitoring tasks such as next-activity prediction and remaining time estimation. Experimental results on synthetic (literature-grounded data) demonstrated the method’s ability to enhance safety, compliance, and operational efficiency. This study illustrates how integrating process mining with regulatory principles can bridge the gap between continuous sensor streams and structured process analysis in food manufacturing. Full article

Obtaining evapotranspiration (ET) estimates at high spatiotemporal resolution is a fundamental prerequisite for clarifying the patterns and controlling factors of agricultural water consumption in drylands. However, most existing ET products are provided at daily or coarser spatial–temporal scales, which limits the ability to capture short-term variations in crop water use. This study developed a novel hourly 10-m ET estimation method that combines remote sensing with machine learning techniques. The approach was evaluated using agricultural sites in two arid regions: the Heihe River Basin in China and the Bekaa Valley in Lebanon. By integrating hourly eddy covariance measurements, Sentinel-2 reflectance data, and ERA5-Land reanalysis meteorological variables, we constructed an XGBoost-based modeling framework for hourly ET estimation, and incorporated the SHapley Additive exPlanations (SHAP) method for model interpretability analysis. Results demonstrated that the model achieved strong performance across all sites (R² = 0.86–0.91, RMSE = 0.04–0.05 mm·h⁻¹). Additional metrics, including the Nash–Sutcliffe efficiency coefficient (NSE) and percent bias (PBIAS), further confirmed the model’s robustness. Interpreting the model with SHAP highlighted net radiation (Rn), 2-m temperature (t2m), and near-infrared reflectance of vegetation (NIRv) as the dominant factors controlling hourly ET variations. Significant interaction effects, such as Rn × NIRv and Rn × t2m, were also identified, revealing the modulation mechanism of energy, vegetation status and temperature coupling on hourly ET. The study offers a practical workflow and an interpretable framework for generating high-resolution ET maps, thereby supporting regional water accounting and land–atmosphere interaction research. Full article

For sustainable greenhouse design, natural ventilation is a vital component; it depends on the local climate. Therefore, optimizing the greenhouse orientation and vent opening configuration is a critical issue that needs to be addressed for a specific location (e.g., the central region of Saudia Arabia). Experiments were conducted in winter, in a curved-roof, single-span, N-S oriented greenhouse that includes roof and side-wall vents. Five different vent opening arrangements were examined. The outside and inside greenhouse environmental parameters were measured, and the ventilation rate (kg·s⁻¹) and the number of air exchanges per hour (N_a) were estimated for each opening case using a modified energy balance equation. The results showed that the common wind directions are N-S and NW-SE. For effective ventilation, greenhouses should be oriented in the E-W or NE-SW directions. Opening the side-wall vents exhibited the highest wind-driven ventilation rate that is essential to control temperature and humidity at the crop level, while only opening the roof vents is not recommended. In the central region of Saudi Arabia, natural ventilation is sufficient for operating greenhouses (${\overline{N}}_a$ > 30). Opening the roof and side-wall vents (combined wind and buoyancy effects) is the most efficient as long as the greenhouse axis is aligned perpendicular to the wind direction. Such information is essential for sustainable greenhouse management in an arid environment. Full article

The primary objective of this research is to simplify and make the industrial manufacturing process of coated maraging steels more economical by combining the advantages of additive manufacturing with simultaneous bulk (aging) and surface (nitriding) treatment in an effective manner. With this aim, preliminary experiments were performed that demonstrated the hardness (and related microstructure) of an as-built MS1 maraging steel, produced by selective laser melting (SLM), is comparable to that of the bulk maraging steel products treated by conventional solution annealing. The direct aging of the solution-annealed and as-built 3D printed maraging steel resulted in similar hardness, indicating that the kinetics of the precipitation hardening process are identical for the steel in both conditions. This assumption was strengthened by a thermodynamic analysis of the kinetics and determination of the activation energy for precipitation hardening using Differential Scanning Calorimetry (DSC) measurements. Industrial target experiments were performed on duplex-coated SLM-printed MS1 steel specimens, which were simultaneously aged and salt-bath nitrided, followed by PVD coating with three different ceramic layers: DLC, CrN, and TiN. For reference, similar duplex-coated samples were used, featuring a bulk Böhler W720 maraging steel substrate that was solution annealed, precipitation hardened, and salt-bath nitrided in separate steps, following conventional procedures. The technological parameters (temperature and time) of the simultaneous nitriding and aging process were optimized by modeling the phase transformations of the entire heat treatment procedure using DSC measurements. A comparison was made based on the in-depth hardness profile estimated by the so-called expanding cavity model (ECM), demonstrating that the hardness of the surface layer of the coated composite material systems is determined solely by the type of the coatings and does not influenced by the type of the applied substrate materials (bulk or 3D printed) or its heat treatment (whether it is a conventional, multi-step treatment or a simultaneous nitriding + aging process). Based on the research work, a proposal is suggested for modernizing and improving the cost-effectiveness of producing aged, duplex-treated, wear-resistant ceramic-coated maraging steel. Full article

Understanding the thermal environment of outdoor public spaces is critical for climate-responsive architectural design, evidence-based urban science, and data-driven smart city planning. Thermal comfort shapes both individual decision-making and collective behavioural patterns, offering valuable insights for designing spaces that support year-round vitality. This study investigates the relationship between thermal conditions and crowd behaviour in severe cold regions by combining behavioural mapping with on-site environmental measurements. Results show that in high-temperature conditions, spatial distribution is primarily influenced by sunlight and shade, whereas at low temperatures, sunlight has minimal effect on space use. Attendance, duration of stay, and activity intensity follow quadratic relationships with the Universal Thermal Climate Index (UTCI), with optimal values at 29 °C, 26 °C, and 27 °C, respectively. Walking speed is inversely correlated with UTCI, with the fastest speeds observed under cold discomfort, reflecting rapid departure from space. Sitting behaviour peaks at 21 °C UTCI and declines to nearly zero when UTCI is below 10 °C. A comparative analysis between Harbin and other regions reveals significant deviations from temperate zone patterns and greater similarity to subtropical behavioural responses. A key contribution of this study is the introduction of the spatial usage rate model and the foot vote method, two novel, observation-based tools that allow for the objective estimation of thermal comfort without relying solely on subjective surveys. These methods offer architects, planners, and smart city practitioners a powerful evidence-based framework to evaluate and optimise outdoor thermal performance, ultimately enhancing usability, adaptability, and public engagement in cold-climate cities. Full article

The impacts of climate change are globally evident and cause significant damage to ecosystems and human activities. These impacts intensify social and economic inequality in Southern Africa (SA), where agriculture is vital for livelihoods and economic development. This study aimed to assess long-term trends in climate elements and parameters relevant to drought regimes in SA to identify drought hotspots and relate them to socioeconomic indicators. The methods include the Theil–Sen slope estimator and the Mann–Kendall statistical significance test. The study analysed ERA5 data for the 1971–2020 to compute the Standardised Precipitation Index (SPI) and Standardised Precipitation Evapotranspiration Index (SPEI) drought indices and descriptors. Results of the trend analysis reveal (i) the existence in almost the entire SA of statistically significant trends of increasing temperature and potential evapotranspiration and decreasing precipitation; (ii) increasing drought risk hotspots in the SPI and SPEI across all timescales, in the north central rainforest region, south and southeast of SA, while decreasing in the northwest coast, central west region, and in the northeast more recently; and (iii) hotspots in the drought descriptors within the same regions, but of a smaller size. Our findings pinpoint drought hotspots in regions with moderate-to-high population density and agricultural systems that involve species vital for food security and of considerable socioeconomic and commercial importance, emphasising the significance of our results for managers and decision-makers. Full article

The Global Cement and Concrete Association (GCCA) estimated that by 2050, 36% industry-wide sustainable value will be created, which includes sequestering CO₂ into the cement and concrete industry to produce commercially feasible high-value products. Direct utilization of CO₂ in the cement and concrete industry, which utilizes natural and sustainable materials, is gaining momentum. Naturally occurring mixtures of hydro magnesite and huntite are important industrial minerals which, upon endothermic decomposition over a specific temperature range, will release water and CO₂. This unique chemistry has led to such mixtures being successfully utilized as fire retardants, replacing aluminum hydroxide or Alumina Tri-Hydrate (ATH). Despite the developed marketplace for magnesium-based fire-retardant products, there is little mention of CO₂ mineral carbonation methods, which attempt to recover and convert magnesium from natural seawater or industrial waste into oxides or carbonates as part of the carbon sequestration initiative. The hypothesis to be proven in this work states that if the process of seawater mineral carbonation is prematurely quenched, Mg²⁺ ionic species in seawater adsorbed on the calcite lattice formation will be trapped and therefore recovered in various oxidized forms, such as magnesium oxides, magnesium hydro magnesite, and magnesium carbonate precipitates. A novel method to recover magnesium Mg²⁺ ions from seawater was successfully explored and documented; as such, from an initial concentration of 1250 ppm Mg²⁺ in raw seawater, the average concentration of spent Mg²⁺ ions after the reaction was as low as 20 ppm. A very efficient near-total recovery of Mg²⁺ from the seawater into the solid precipitates was recorded. Subsequently, the process for continuous seawater mineral carbonation for the production of magnesium/brucite/huntite products was successfully proven and optimized to operate with a 30 s reaction time, a dynamic feedstock concentration, [CaO] at 1gpl in seawater and a room temperature reaction temperature (30 °C), where the average yield of the fire-retardant magnesium-based compounds was 26% of the synthesized precipitates. Approximately 5000 g of the hydro magnesite materials was molded into a fire-retardant brick or concrete wall, which was subjected to an accredited fire performance and durability testing procedure BS476-22:1987. There were encouraging results from the fire resistance testing, where the fire-retardant material passed BS476-22:1987, with performance criteria such as physical integrity failure, the maximum allowable face temperature, and a minimum duration before failure, which was up to 104 min, evaluated. Full article

In response to the increasingly severe energy crisis and global warming, ORC systems have attracted considerable attention owing to their ability to harness waste heat for power generation. Reducing the amount of organic working fluid in the heat exchanger can improve the economic performance of the ORC system. To achieve this aim, a new simulation model for plate evaporators and condensers of small/micro-scale ORC systems was developed, which can estimate the amount of organic working fluid and the outlet parameters. An ORC test rig was constructed to validate the model. Several experiments cases with different inlet temperatures were conducted. After validation, the impact of adjusting the operational and geometry parameters of the heat exchangers on the amount of organic working fluid was investigated. The results showed that appropriately increasing the temperature of the heat sources and cold sources or narrowing the heat exchanger width reduced the amount of working fluid in both the condenser and evaporator by over 30%. When adjusting the operational flow rate, the comprehensive impact on both the evaporator and condenser must be considered. The maximum mass was reduced by approximately 15.4%. The study results offer insights into designing plate evaporators and condensers for small/micro-scale ORC systems. Full article

In this study, three different reactor concepts for the oxidative coupling of methane (OCM) reaction are examined at the miniplant scale. Their performance and response to variations in key process parameters, such as temperature and gas hourly space velocity (GHSV), are evaluated over a wide range. In addition to the conventional Packed Bed Reactor (PBR), Packed Bed Membrane Reactor (PBMR), and Chemical Looping Reactor (CLR) approaches were tested. The PBMR was realized with a porous ceramic $\alpha$-Alumina membrane as air/O₂ distributor. The CLR was operated in a poly-cyclic operation. Similarities of the different reactor concepts as well as layout-immanent differences with regard to changes in reaction conditions could be identified and advantages and disadvantages of the processes highlighted. The results show that C₂ selectivity can be improved by both PBMR and CLR in comparison to conventional PBR, possibly reducing cost-intensive downstream units. While a PBMR can slightly improve selectivity (23%) while keeping the same conversion compared to a PBR, the use of a CLR allows for achieving exceptionally high selectivities of up to 90%. In order to address the low conversion, CLR tests were carried out with an additional O₂ carrier material, which led to a significant improvement in terms of C₂ yield. In addition to an evaluation and comparison of the different reactor concepts, the findings at the miniplant scale provide estimates of their potential use and scalability. Full article