Search Results (14,637)

Ground-based microwave radiometers (MWRs) continuously retrieve atmospheric temperature and vapor density profiles, but systematic biases relative to radiosonde observations limit their quantitative application in nowcasting and data assimilation. In this study, we matched temperature and vapor density profiles from six ground-based MWRs with L-band radiosonde observations at Wuhan to evaluate data quality for 2025 and analyze the sources of station-to-station bias differences. We established linear regression, random forest (RF), and artificial neural network (ANN) models to correct biases by height group and sky condition, respectively, and compared the corrected data with the original data. The results show that, compared with radiosonde data, the MWR temperature was generally cold-biased under clear (−0.895 °C), cloudy (−0.729 °C), and rainy (−0.188 °C) skies, whereas the vapor density was moist-biased under all three conditions (+0.417, +0.209, and +0.47 g/m³). The per-station biases differed markedly and could not be explained by spatial separation alone, indicating station-specific environmental and representativeness differences rather than instrument differences. All three correction methods significantly reduced the deviations; taking the RMSE together with the residual bias as the joint criterion, the ANN was selected as the best method, reducing the test set temperature RMSE from 2.802 °C to 2.284 °C (−18.5%) and the vapor density RMSE from 2.764 g/m³ to 1.746 g/m³ (−36.8%), followed by random forest (−17% and −35.9%) and linear regression (−6.8% and −6.8%). After removing the small constant residual bias, the ANN is both the most accurate and effectively unbiased. The corrected profiles brought the thermodynamic instability parameters to a usable level for severe-convection nowcasting and provided an early-warning signal in the pre-onset period of gale and short-duration heavy rain, which also provide a reference for the quantitative application of microwave radiometer data. Full article

Agricultural phosphorus losses create a need for simple and sustainable reactive media suitable for decentralized interception. This study compared unmodified pyrite, iron filings, and limestone for phosphorus removal from low-concentration synthetic phosphate solutions using dosage, apparent thermodynamic, nonlinear isotherm, kinetic, pH, SEM, and binary-mixture analyses. Based on the tested dosage range, 60 g/L was selected for pyrite and 40 g/L for iron filings and limestone. Pyrite showed an exothermic apparent response (ΔH° = −8.12 kJ/mol), whereas limestone and iron filings were endothermic (ΔH° = 11.75 and 19.99 kJ/mol). Nonlinear Freundlich fitting provided a slightly better description than Langmuir fitting, with R² values of 0.9867, 0.9821, and 0.9648 for pyrite, limestone, and iron filings, respectively. Linearized pseudo-second-order fitting characterized the short-term phosphorus-removal kinetics of pyrite and limestone, while iron filings exhibited non-monotonic behavior. The 1:1 iron filings–limestone mixture maintained phosphorus removal above 99% across 10–100 g/L, with the highest removal at 40 g/L. The pH and SEM observations supported material-specific reaction environments and surface transformations. These batch-scale results identify unmodified Fe- and Ca-based media as candidates for further evaluation in sustainable agricultural phosphorus management under real runoff and continuous-flow conditions. Full article

Understanding the molecular organization of surfactants at the sc-CO₂/water interface is essential for the rational design of CO₂-philic interfacial formulations with reduced fluorine content. In this work, three low-fluorinated anionic surfactants (LF1–LF3) with different hydrophobic-tail architectures were investigated together with a fluorine-free branched co-surfactant (ZBJ) using density functional theory (DFT) calculations and molecular dynamics (MD) simulations. DFT calculations revealed a clear amphiphilic segregation of solvent affinity: the fluorinated tails preferentially interacted with CO₂, whereas the sulfonate headgroups exhibited stronger affinity for water. MD simulations showed that the surfactants, initially positioned at the sc-CO₂/water interface, underwent interfacial reorganization and orientational ordering, with their fluorinated tails extending into the sc-CO₂ phase and their hydrophilic headgroups oriented toward the aqueous phase. Tail branching strongly affected interfacial packing and structural stability; the three-tailed, claw-like LF3 formed the thickest and most thermodynamically stable monolayer, with an interfacial formation energy of −330.30 kJ/mol. In the LF3/ZBJ mixed system, ZBJ occupied packing voids between LF3 molecules, further stabilizing the mixed monolayer and yielding an interfacial formation energy of −342.07 kJ/mol. These results clarify how tail architecture, CO₂-philic/hydrophilic partitioning, counterion coordination, and steric complementarity govern the interfacial organization and stabilization of low-fluorine surfactants, providing molecular-level guidance for the rational design of low-fluorine surfactant formulations for sc-CO₂/water systems. Full article

A magnetic chitosan composite was applied to study the adsorption of nanoplastics (NPs), prepared from single-use plastic bottles and packaging materials by mechanical fragmentation (MF) and nanoprecipitation (NPR), on magnetic biopolymer. The resulting polystyrene (PS) and polyethylene terephthalate (PET) samples were characterised by SEM, TEM, DLS, zeta potential and ATR-FTIR. The magnetic chitosan composite (MCSC) was prepared by synthesising Fe₃O₄ nanoparticles and modifying chitosan through crosslinking. Batch experiments were conducted to study the adsorption of PSNPR, PETNPR, and PETMF nanoplastics on the magnetic chitosan composite. Changes during the adsorption process were monitored using UV–Vis spectroscopy. The maximum efficiencies of PSNPR and PETMF are 97% and 94%, respectively, at pH 5, whereas the maximum efficiency of PETNPR is 94% at pH 6. The Langmuir maximum adsorption capacity (q_m) values for PSNPR, PETNPR, and PETMF are 26.7, 13.8, and 19.4 mg g⁻¹, respectively. The Freundlich and Langmuir isotherms, thermodynamic studies, as well as pseudo-first-order and pseudo-second-order models, were applied to study the adsorption behaviour of nanoparticles on the magnetic chitosan composite. The XPS and FT-IR data for pristine and adsorbed nanoplastics as well as modelling results indicated complex adsorption mechanisms. Full article

The coexistence of dyes and phosphate in industrial effluents creates a treatment challenge because both contaminants can occur as negatively charged species while interacting differently with adsorbent surfaces. To explore a potential solution, this study evaluated magnesium oxysulfite/sulfate (MgOS) for methyl orange (MO) and phosphate adsorption under single- and binary-solute conditions. MgOS was characterized by complementary physicochemical and surface analyses, and adsorption equilibrium, kinetics, thermodynamics, pH effects, and competitive behavior were examined. MgOS exhibited a mesoporous, chemically heterogeneous structure and maintained effective adsorption over a broad pH range with an apparent pH-regulating effect. Adsorption capacities reached 50.6 mg g⁻¹ for MO and 16.3 mg g⁻¹ for phosphate in single-solute systems. MO reached equilibrium within 7–45 min and was generally described by pseudo-first-order kinetics. Phosphate required 150–360 min and showed concentration-dependent kinetic behavior, with PSO and Elovich models providing the best fits depending on the fitting approach and initial concentration. MO adsorption was spontaneous and exothermic, while phosphate adsorption was spontaneous and endothermic. Surface characterization supported electrostatic interactions, hydrogen bonding, and Mg-site coordination for MO, whereas phosphate removal involved ligand exchange, inner-sphere coordination, and Mg-O-P/Mg-phosphate-like species. Phosphate reduced MO adsorption by 11.9–30.7% in binary systems, while phosphate adsorption remained comparatively stable. MgOS therefore showed potential for simultaneous MO and phosphate removal under competitive conditions. Full article

The accurate prediction of the power of high-pressure roller mills is considered essential for evaluating equipment operating conditions and optimizing energy consumption. Existing power prediction methods, however, are considered to have notable limitations: mechanistic models exhibit limited adaptability under dynamic conditions, and purely data-driven models lack physical logic constraints, often resulting in physically inconsistent predictions during extreme conditions such as shutdowns. To address these problems, proposed in this paper is a power prediction method that combines Long Short-Term Memory (LSTM) networks with Physics-Informed Neural Networks (PINN) under a sliding-window rolling prediction framework, termed LSTM-PINN. This method takes HPGR as the research object and integrates the LSTM-PINN framework with the physical mechanism of high-pressure roller mills for power prediction. Specifically, based on the physical operating mechanism of HPGR, four constraint relationships-monotonicity, linear prior, thermodynamic, and energy conservation-are introduced and embedded into the loss function of LSTM-PINN. While LSTM-PINN has been applied in other domains, its combination with the HPGR physical mechanism for power prediction has not been previously reported. The LSTM network extracts dynamic temporal features of power evolution, while the four mechanism-driven physical constraints guide the model toward physically consistent predictions. Experiments using actual operational data from a mining company demonstrate that: (1) the pure LSTM model outputs non-zero power during shutdown, whereas LSTM-PINN brings predictions to zero; (2) compared with pure LSTM, LSTM-PINN reduces RMSE by 23.13%, 13.02%, and 11.86%, and reduces MAE by 21.67%, 13.70%, and 10.85% under the single-feature, multi-feature, and all-feature input combinations, respectively. Among all configurations, the multi-feature combination achieves the lowest absolute errors with the smallest variance, representing the optimal trade-off between accuracy and stability. Overall, the proposed method substantially improves prediction accuracy, interpretability, and reliability, providing a trustworthy basis for energy optimization and intelligent control of HPGRs. Full article

This study investigates the volumetric behavior and transport properties of two non-aqueous binary systems designed for carbon capture: monoethanolamine + dimethyl sulfoxide and + N,N–dimethylformamide. Experimental density and viscosity data were measured across the entire composition range at various temperatures. Density values were correlated using the Belda, Herraez, Emmerling et al. and Gonzalez–Olmos–Iglesias equations. Viscosity data were fitted using the Grunberg–Nissan, Heric–Brewer, four-body McAllister and Jouyban–Acree models. The calculated excess molar volumes and viscosity deviations were mathematically correlated using the Redlich–Kister polynomial equation. The values of the excess molar volume are positive for monoethanolamine + dimethyl sulfoxide and negative for monoethanolamine + N,N–dimethylformamide, while negative values were obtained for the viscosity deviation for both systems. Utilizing Eyring’s theory, the thermodynamic functions of activation were calculated. The CO₂ absorption capacity was determined experimentally for both non-aqueous systems. The Fourier transform infrared spectroscopy spectra were determined before and after absorption and discussed. Full article

Quantum uncertainty and wavefunction collapse remain among the most conceptually unresolved aspects of microscopic physics. Here, we investigate whether uncertainty and collapse-like electron localization may admit a complementary thermodynamic interpretation through recursive entropy-field dynamics. The electron is modeled as a dynamically evolving entropy field geometry composed of structural, electromagnetic, and thermal entropy components maintained through continuous recursive interaction with the surrounding vacuum entropy field. Within this framework, uncertainty emerges from incomplete temporal accessibility to rapidly evolving recursive electron configurations occurring beneath experimentally accessible timescales. Repeated recursive phase sampling naturally produces probabilistic measurement statistics and approximately Gaussian localization statistics. Electron–photon interaction is further modeled through phase-matched recursive entropy coupling, where repeated entropy transfer progressively reorganizes the electron entropy geometry toward localization. Numerical simulations reproduce finite-width Dirac-delta-like localization behavior, localization saturation after a finite number of recursive cycles, and intrinsically nonzero collapse timescales, with a lower bound of approximately 3.2 × 10⁻²⁰ s for an electron at rest under ideal recursive coupling. These results suggest that wavefunction collapse may emerge as a finite recursive thermodynamic localization process rather than an instantaneous state projection. The framework further provides a qualitative thermodynamic interpretation that relates normalized recursive accessibility to Born probability, discusses recursive entropy evolution as a possible physical basis for intrinsic quantum timescales, and outlines how Bell-type correlations may emerge within an extended recursive entropy framework. Together, these results establish a phenomenological foundation for exploring recursive entropy dynamics underlying quantum uncertainty and localization while identifying model-dependent predictions that may provide targets for future experimental investigation. Full article

Wastewater treatment remains a pressing global challenge due to the continuous discharge of recalcitrant pollutants from anthropogenic activities. Among these, synthetic dyes are particularly problematic due to their persistence and toxicity, requiring advanced and sustainable removal strategies. In this study, a novel bio-based hydrogel was synthesized via a green process, avoiding the use of harmful chemicals. The hydrogel, composed of alginate and mucilage extracted from Opuntia ficus-indica, was applied as an adsorbent for the removal of Neutral Red dye from a synthetic aqueous solution. Characterization revealed a rough surface morphology, mesoporosity, and a specific surface area of 0.14 m²/g. The material exhibited a point of zero charge at pH 9.0, and its surface was rich in functional groups, including hydroxyl, deprotonated carboxyl, and ether groups, which contributed to dye adsorption through non-electrostatic mechanisms. Optimal removal was achieved at acidic pH, with a maximum adsorption capacity of 26.6 mg/g at pH 5.0. The adsorption kinetics followed a pseudo-second-order model, reaching equilibrium within 200 min, with a maximum uptake of 24.8 mg/g after 720 min. Thermodynamic analysis indicated a spontaneous, exothermic, and reversible adsorption process, with maximum capacities of 1420, 1432, and 1308 mg/g at 25, 35, and 45 °C, respectively. Competitive adsorption studies showed a decrease in capacity in the presence of electrolytes (KCl, NaCl, and MgCl₂). The hydrogel demonstrated excellent reusability, retaining over 90% efficiency after five consecutive cycles, and showed no toxicity in lettuce seed germination tests. These results highlight the potential of alginate-Opuntia ficus-indica hydrogel as a sustainable, non-toxic, and efficient adsorbent for dye removal in water treatment applications. Full article

Direct air capture (DAC) technology is transitioning from the prototype stage into commercialization, yet its large-scale deployment still faces challenges related to high energy consumption and associated environmental and ecological impacts. In this study, we first develop a unified thermodynamic model for the two mainstream DAC routes, solid adsorption (S-DAC) and liquid absorption (L-DAC). Based on this consistent framework, we then conduct life cycle assessment (LCA) and emergy analysis to jointly construct a systematic sustainability evaluation framework integrating energy, emergy, and LCA methods. The Sustainability Composite Index (SCI) was proposed by integrating key indicators to provide a holistic measure for sustainability assessment across different DAC systems. Results indicate that overall, S-DAC demonstrates superior sustainability with a composite index (SCI) of 0.823, compared to 0.759 for L-DAC, although trade-offs exist across different indicators. Under the baseline scenario S-DAC performs well in emergy transformity (Tr), and second law efficiency, whereas L-DAC excels in energy consumption, net carbon removal efficiency, and total environmental impact. The choice of electricity and heat sources exerts considerable influence on the sustainability performance of both DAC systems. Among the 24 energy source scenarios, the photovoltaic power (PV) S-DAC integrated with biomass heat achieves the highest sustainability with an SCI of 0.907. Conversely, the coal-fired L-DAC system and natural gas-powered integrated solutions exhibit the poorest sustainability, with an SCI of 0.711. Notably, even when clean energy is employed, different systems still involve trade-offs across metrics. These findings underscore that comprehensive sustainability assessment is essential before scaling up DAC technologies. Full article

The Gibbs equation describes the relationship between the enthalpy (∆H), entropy (∆S), and Gibbs energy (∆G) changes in physicochemical processes: ∆G = ∆H − T∆S. It remains a cornerstone of chemical thermodynamics, yet it has features that need to be understood. The linear correlations between ∆S and ∆H (or ∆G and ∆H) are often found across various series of processes. These correlations do not follow from the laws of thermodynamics, thus meaning that there may be additional restrictions on the variation in the thermodynamic potentials. In this study, we attempted to establish the quantitative principles governing the ∆G vs. ∆H relationship across various processes involving non-covalent interactions at 298.15 K, from solvation and vaporization to molecular complexation and supramolecular recognition. The baseline for the analysis was the linear ∆G vs. ∆H correlation for solvation in non-associated solute–solvent systems, first noted by Barclay and Butler. The classification of the solute–solvent systems enabled quantification of the deviations associated with conformational flexibility, complexation and solvophobic effects upon solvation. These regularities necessarily meant that the ∆G vs. ∆H for solution- and gas-phase molecular complexation processes should be described by similar linear relationships, having the same slope as the Barclay–Butler baseline. Furthermore, this framework was applied to α-cyclodextrin host–guest systems. The validity of the established relationships was checked against more than 4500 experimental thermodynamic values. They enable the calculation of the enthalpy change from a single equilibrium constant measurement at 298.15 K, with the deviation comparable to an experimental uncertainty. The predictive power does not depend on the process (solvation, vaporization, and complexation), the phase it takes place in (gas, liquid), or the dominating interaction type (collective/pairwise, van der Waals forces/hydrogen bonding/charge transfer), highlighting the uniform character of the discussed relationships. Full article

Ionic liquids (ILs) are often described as designer solvents. However, a single cation–anion pair rarely optimizes phase stability, transport properties, and task-specific functions simultaneously. Mixing introduces composition as a continuous design variable, which can suppress crystallization, reorganize coordination and hydrogen-bond networks, redistribute ions on interfaces, and balance viscosity, conductivity, selectivity, and reactivity. This critical review analyses binary and higher-order IL mixtures, including common-ion, reciprocal, double-salt, eutectic, and glass-forming systems, with a focus on studies published from 2018 to 2026, and selected foundational reports. Applications include CO₂ capture and gas separation, liquid separations, biomass processing, electrochemical energy technologies, thermal management, catalysis, electrospray propulsion, and biological systems. The review connects composition-dependent performance to phase behavior, thermal stability, density and excess volume, transport properties, interfacial organization, polarity, hydrogen bonding, and acid–base descriptors. Special attention is given to counterexamples and to distinguishing eutecticity, thermodynamic non-ideality, and functional synergy. The evidence indicates that the most useful formulation does not necessarily maximize a single property or coincide with the eutectic composition. Its benefit frequently lies in expanding the operating window or balancing multiple requirements. Rational formulation therefore requires composition-resolved measurements, explicit reference states, and multiobjective optimization from molecular structure to process or device performance. Full article

Bubble-point behavior of shale oil under nanoconfinement is critical for understanding phase evolution during CO₂-enhanced shale-oil recovery. In this study, visual micro/nanofluidic PVT experiments were conducted to systematically investigate bubble-point pressure deviations of pentane–CO₂, hexadecane–CO₂, pentane/decane/hexadecane–CO₂, and shale oil–CO₂ systems. Measurements were performed at gas–oil ratios of 130 and 260 and temperatures of 65–125 °C using a 10 nm single-scale pore model and a coupled 10 μm–10 nm pore-network model. Experimental results were compared with theoretical predictions from a confinement-modified Peng–Robinson equation of state incorporating capillary pressure, surface adsorption, and critical-property shifts. Furthermore, a metastable nucleation limit was introduced to describe the experimentally observed phase-transition pressure below the equilibrium bubble-point boundary. Pronounced downward deviations toward the metastable region were observed in isolated 10 nm pores. For the pentane–CO₂ system at 65 °C and GOR = 130, the experimentally observed phase-transition pressure was approximately 3.5 MPa, compared with an equilibrium prediction of 4.3 MPa, corresponding to a relative deviation of 18.35%. The deviation decreased as temperature approached the critical region and was reduced at higher GOR. For example, at GOR = 260, the deviation of the hexadecane–CO₂ system decreased from 40.63% at 65 °C to 10.01% at 125 °C. Fluid composition also strongly affected confinement sensitivity, with heavier hydrocarbon systems exhibiting stronger shifts toward metastable behavior. In contrast, bubble-point pressures in the coupled 10 μm–10 nm network remained close to the equilibrium predictions of the micrometer-scale pores and deviated significantly from the metastable limit. For the shale oil–CO₂ system at 65 °C and GOR = 130, the relative deviation decreased from 29.77% in the isolated 10 nm pore model to only 2.43% in the coupled 10 μm–10 nm network. These results demonstrate that nanoconfined bubble-point behavior is governed by the coupled effects of thermodynamic conditions, fluid composition, metastability, and pore-scale connectivity. Full article

The CFD study investigated three different groove geometries: circular, rectangular, and trapezoidal grooves, and these results were compared to a smooth tube. The results obtained from this CFD study were compared with experimental work completed for Reynolds numbers of 10,000, 22,000, 34,000, and 38,000. A CFD analysis for Reynolds numbers between 10,000 and 50,000 were performed to further investigate the effects of heat transfer on these geometries. This CFD work validated the experimental results and analyzed three additional Reynolds numbers of 42,000, 46,000, and 50,000 to further evaluate the turbulence effect on heat transfer. For increasing Reynolds numbers in the turbulence region, the Nusselt number significantly increased. The Nusselt number for the grooved geometries was significantly greater than that of the smooth tube. The augmented grooves resulted in the greatest enhancement of heat transfer for the circular, rectangular, and trapezoidal grooves at a Reynolds number of 34,000 and were 63%, 31%, and 58%, respectively. These results are consistent with the experimentally obtained results for the circular, rectangular, and trapezoidal grooves of 63%, 47%, and 58%, when compared to the smooth tube. It was observed that overall thermal enhancement was greatest for the augmented grooves in the Reynolds number range between 10,000 and 20,000. The friction factor for each grooved tube increased with higher Reynolds numbers, while the smooth tube showed a reduction in friction factor for the range 10,000 < Re < 38,000. All three grooves had greater axial pressure drop than the compared smooth tube. The rectangular groove exhibited the greatest axial pressure drop, while the circular and trapezoidal grooves were similar in their results. The mean heat enhancement factors for the circular, rectangular, and trapezoidal grooves were determined to be 1.40, 1.12, and 1.25, respectively. Therefore, all three grooved geometries proved to be thermodynamically advantageous when compared to the smooth tube. Full article

The processing of lead cakes containing osmium and rhenium is complicated by the significant variability in their elemental and phase compositions. The aim of this study was to determine the effects of lead cake composition on acid consumption and the recovery of Os and Re during oxidative leaching in a continuous-flow reactor. The leaching of 15 industrial cakes derived from copper production—containing 440–4260 g/t Re and 23–63 g/t Os—was investigated in a sulfuric acid medium, using sodium hypochlorite as the oxidizing agent. The experimental results showed that increasing contents of PbCO₃, PbO, and metallic Pb in the cake reduce Os and Re recovery at a fixed reagent dosage. It is established that variations in H₂SO₄ consumption are primarily driven by the cake’s phase composition; in particular, the acid is consumed through reactions with acid-neutralizing matrix components (PbCO₃ and PbO), thereby altering the effective pulp acidity and oxidative leaching conditions. Thermodynamic modeling indicated that pH changes primarily affect the chemical state of matrix components, whereas Os and Re remain predominantly in the forms OsO₄(aq) and ReO₄⁻, respectively. Under near-optimal conditions, recoveries of up to 95–96% for Os and 99–100% for Re were achieved. The kinetic study results demonstrated a faster extraction rate for Re compared with Os. In summary, the results show that the phase composition of the cake is a key parameter influencing acid and oxidant consumption; furthermore, adjusting the reagent regime based on the composition of industrial lead cakes enhances the stability and efficiency of Os and Re recovery. Full article