Search Results (6,436)

Conventional depletion development and waterflooding are often ineffective in tight oil reservoirs because of their ultra-low permeability, complex fracture–matrix architecture, and limited fluid mobility. Although inter-fracture CO₂ flooding has demonstrated considerable potential for enhanced oil recovery (EOR), the coupled effects of key operational parameters on reservoir pressure evolution, fracture–matrix mass transfer, and oil mobilization remain inadequately understood. In this study, a multi-component compositional simulation model, constrained by detailed geological characterization and calibrated through production history matching of the Yuan 284 block in the Changqing Oilfield, was developed to systematically evaluate the effects of CO₂ injection rate, injection–production time ratio, and shut-in duration on recovery performance and reservoir response. The results show that increasing the CO₂ injection rate from 1000 to 50,000 m³/d improves the recovery factor from 40.49% to 49.90%; however, the incremental recovery gain decreases markedly beyond 30,000 m³/d, which is aggravated by enhanced gas channeling through high-conductivity fracture pathways. Analysis of the injection–production time ratio indicates that an optimal ratio of 0.50 provides the best balance between reservoir energy replenishment and oil displacement efficiency, whereas excessively small ratios result in insufficient pressure support and reduced recovery. In contrast, extending the shut-in duration consistently lowers recovery performance by weakening fracture–matrix mass transfer and promoting pressure dissipation, demonstrating that immediate production following injection is more effective than prolonged soaking under the investigated conditions. The optimized operating scheme yields a recovery factor of 48.87%, substantially exceeding the representative waterflooding recovery level of 35.20%. These findings clarify the mechanisms controlling pressure maintenance, CO₂ utilization efficiency, and volumetric sweep during inter-fracture asynchronous CO₂ flooding, and provide both theoretical insights and practical guidance for the efficient development of ultra-low-permeability fractured tight oil reservoirs. Full article

Industrial contamination can influence the transfer of toxic and essential elements through soil–plant–animal systems and may pose risks to food safety. This study aimed to determine whether contamination patterns in soil are reflected in forage vegetation and meat products and to evaluate trace-element behavior across interconnected components of the soil–plant–animal system. This study assessed the distribution and transfer of 12 elements (As, Be, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, V, and Zn) in soil, forage vegetation, and meat products from five industrially affected areas of Central Kazakhstan. Element concentrations were determined by inductively coupled plasma mass spectrometry. Soil contained the highest concentrations of most elements, confirming its role as the primary reservoir of contamination, whereas forage vegetation reflected local pollution patterns. The highest levels of contamination were generally observed in the industrial centers of Temirtau and Zhezkazgan, with Zhezkazgan exhibiting the most distinct element profile. Soil-to-forage transfer was most pronounced for Cd, Cu, Pb, and Zn, with significant positive relationships between soil and forage concentrations (p < 0.001). Meat products generally contained lower element concentrations than soil and forage; however, Cd, Hg, and As exceeded regulatory limits in 23 of 279 samples (8.2%). By integrating environmental and animal-derived matrices within a single framework, this study provides new insight into trace-element transfer pathways and facilitates the identification of priority contaminants, high-risk areas, and livestock products requiring enhanced environmental and food safety monitoring in industrial regions. Full article

Gas–solid bubbling fluidized beds involving Geldart Group B particles are fundamental to numerous industrial thermochemical processes, where bubble dynamics dictate the efficiency of heat and mass transfer. However, accurately predicting these complex hydrodynamic behaviors remains a challenge due to the non-linear coupling of phase interactions. This study presents a comprehensive validation of 2D and 3D Eulerian–Eulerian Two-Fluid Models (TFM) against an extensive experimental dataset. A ‘core-flow’ consistency principle is adopted, demonstrating that the 3D cylindrical simulation provides a physically equivalent representation of the central bubbling dynamics in the rectangular experimental bed. A key innovation of this work is a novel post-processing framework that bridges raw CFD datasets and quantitative bubbling metrics. Unlike traditional threshold-based segmentation or localized probe measurements, which are often limited by spatial resolution and noise sensitivity, the integrated use of Autodesk 3DS Max for volumetric reconstruction and customized MATLAB (R2024a) algorithms allows for the seamless processing of heterogeneous 2D and 3D data. This methodology significantly enhances the capability to track complex bubble coalescence and breakup events while improving batch-processing efficiency, providing a high-fidelity alternative for analyzing gas–-solid flow patterns in complex geometries. The results show that both experimental data and 2D simulations align with Werther’s correlation, yielding Mean Relative Errors (MRE) of 8.2% and 10.5%, respectively. In contrast, the 3D simulation tracks Darton’s prediction closely with a lower MRE of 7.4%, demonstrating superior concordance in volumetric bubble growth. The core innovation lies in the definition of a clear dimensional choice framework: 2D simulations are computationally sufficient and accurate for predicting macro-scale bubble heights and frequencies under pseudo-2D or narrow-bed constraints. However, 3D simulations are strictly necessary when evaluating unconstrained radial expansion, core-flow dynamics, and precise volumetric bubble diameters (d_v) where full multi-directional degrees of freedom dictate hydrodynamics. Full article

Photosynthetic biogas upgrading (PBU) using microalgae is a promising biological approach for converting raw biogas into biomethane while recovering nutrients and fixing part of the biogenic CO₂ into algal biomass. Unlike conventional physicochemical technologies, which mainly separate CO₂ from CH₄, PBU can combine gas upgrading with wastewater or digestate treatment, nutrient recycling, and biomass production. This review assesses the current state of PBU technology, with particular emphasis on high-rate algal ponds, absorption columns, and closed photobioreactors. It examines the main operating parameters that control gas–liquid mass transfer, carbonate buffering, and photosynthetic activity, including the liquid-to-gas ratio, pH, alkalinity, temperature, light regime, light intensity, and gas retention time. Special attention is given to the combined effects of the L/G ratio, pH, and alkalinity, as these parameters strongly influence CO₂ absorption, CH₄ enrichment, and O₂ contamination of the upgraded gas. The use of wastewater or anaerobic digestate instead of synthetic growth media is identified as an important sustainability advantage, particularly at wastewater treatment plants with existing anaerobic digestion and nutrient-rich side streams. However, digestate use may also create operational challenges related to turbidity, ammonium inhibition, solids, and variable composition. Available studies indicate that PBU may reduce operating costs and greenhouse gas emissions under favorable conditions while creating additional value from algal biomass. Nevertheless, wider deployment is still limited by high land requirements, seasonal variability, O₂ contamination, biomass harvesting, and limited evidence from large-scale systems. Future development should therefore focus on improved oxygen management, more efficient reactor designs, nanoparticle-assisted enhancement of photosynthetic activity, better integration with wastewater treatment, and AI-supported monitoring and control to improve process stability and support scale-up. Full article

The synergistic co-production of ceramic fibers from fly ash and coal gangue offers a promising path for their high-value utilization. However, research in this area remains limited, hindering its broader application. This study employs numerical simulations to assess the influence of high-wheel rotational speed and melt temperature on the mass of inter-wheel melt transfer, as well as their effects on ligament size and slag-ball fraction. The results show that the high wheel, responsible for melt pre-fragmentation and transfer, plays a crucial role in determining the mass of inter-wheel melt transfer and controlling ligament dimensions. In contrast, the low wheel does not directly affect ligament size but aids in transforming pre-fragmented droplets into ligaments and modulates their dispersion. Melt temperature impacts both transfer mass and ligament size by modifying melt properties. The slag-ball fraction increases with the melt temperature and decreases with the high-wheel speed, while the low-wheel speed has a negligible effect. Under the optimal operating conditions of a melt temperature of 1745 °C and equal rotational speeds of 10,000 rpm for both the high and low wheels, a ligament structure with a relatively concentrated size distribution is obtained, with the slag-ball fraction effectively controlled within the range of 8–13%. Full article

The current research investigates the extraction efficiency of an emerging green technology, pressurized liquid extraction (PLE), compared to traditional stirring extraction (STE) in order to recover higher antioxidant capacity from three plant species of the Asteraceae family, namely Solidago virgaurea, Tussilago farfara, and Helichrysum stoechas. The optimal PLE conditions were achieved through a combined response surface methodology (RSM) approach. The resulting optimized PLE parameters (40% ethanol, 160 °C, 25 min, 1700 psi) were experimentally verified and directly contrasted with STE (40% ethanol, 80 °C, 60 min, 500 rpm). Despite having the same solvent polarity, the two methods showed significant variations in mass transfer kinetics and heat intensity. Across all species, PLE significantly boosted the ascorbic acid antioxidant capacity (p < 0.05), thereby showing enhanced recovery of compounds that contribute to the overall antioxidant capacity. STE generated noticeably increased total polyphenolic content and DPPH radical scavenging activity (p < 0.05), indicating that some phenolic subclasses might be susceptible to PLE at higher temperatures. Values for ferric-reducing antioxidant power were largely similar among approaches. Overall, PLE was shown to be highly effective in maximizing the total antioxidant capacity in shorter extraction times, while STE can better preserve specific polyphenolic fractions, as demonstrated through analysis of the optimal extracts by HPLC-DAD. The integration of experimental validation with chemometric modeling supports the reliability and practical applicability of the optimized PLE protocol. Full article

Bisphenol A type epoxy resin has the problem of relatively high brittleness after curing. Although traditional polysiloxane toughening methods can improve toughness, they often come at the expense of strength. In this paper, methylphenyl dimethoxysilane (MPS) was used as a monomer to synthesize end-hydroxyl poly(methylphenyl)siloxane (PMPS), which was then used to modify E51 epoxy resin. The structure and reaction degree were characterized by infrared spectroscopy, proton nuclear magnetic resonance spectroscopy, matrix-assisted laser desorption/ionization time-of-flight/time-of-flight mass spectrometry and viscosity tests. The mechanical test results show that when the PMPS content is 20 wt%, the tensile, flexural, compressive and impact strengths of the modified resin increase by 31.26%, 26.16%, 18.53% and 98.66%, respectively, compared with the unmodified resin, and the tensile and flexural elastic moduli increase by 38.36% and 32.25%, respectively. The fracture toughness increases by 60.29%, indicating that the strength, stiffness and toughness of the material have all been improved. Dynamic mechanical analysis shows that the glass transition temperature and crosslinking density of the system gradually decrease with increasing PMPS content. Thermogravimetric analysis shows that the introduction of PMPS increases the char yield and decreases the maximum thermal decomposition rate, thereby enhancing the thermal stability of the system. Microscopic morphology analysis by optical microscopy, scanning electron microscopy and atomic force microscopy shows that the system has good compatibility, and the internal different modulus phases are distributed in a network-like manner, forming a uniform co-continuous or bicontinuous phase structure. This structure effectively promotes stress transfer and energy dissipation, alleviates local stress concentration, and thus comprehensively improves the mechanical properties of the resin system. Full article

Ozonation is one of the most widely used methods for wastewater treatment. However, it suffers from several drawbacks, including a low reaction rate, long reaction time, and the formation of intermediate byproducts due to incomplete oxidation. Therefore, in this paper, the ozonation process was improved via the MgO nanocatalyst and honeycomb activated carbon (HAC) as a packing material in the bubble column reactor by using the following methods: (O₃/MgO, O₃/HAC, and O₃/MgO/HAC). The results showed that using ozone alone yielded a low chemical oxygen demand (COD) removal efficiency of 63.33% after 90 min, and the phenol concentration was 15 mg/L. However, when the catalyst was added, the efficiency increased to 73.33%, which is attributed to the enhanced generation of more hydroxyl radicals (OH•). The HAC packing material had a positive effect, as the removal efficiency rose to 76.66% due to its effective role in improving the mass transfer inside the reactor. The integrated (O₃/MgO/HAC) method proved to be the most effective at achieving a COD removal efficiency of about 83%; furthermore, the efficiency reached 91% when the initial phenol concentration decreased to 10 mg/L. Two doses of catalysts were used, 0.05 and 0.1 g/L, and it was found that the higher dose (0.1 g/L) had the highest efficiency. The effect of the initial phenol concentration and ozone gas flow rate were studied. The study concludes that the use of the MgO nanocatalyst and the honeycomb-structured activated carbon packing material plays an effective role in improving the ozonation process by increasing the reaction rate, reducing treatment time, and decreasing the demand for additional ozone gas supplies, thus achieving significant economic benefits. Full article

The transition to renewable energy requires scalable and sustainable hydrogen production technologies. Dark fermentation (DF) can generate biohydrogen from diverse biomass feedstock, but its efficiency remains limited. Immobilising anaerobic consortia offers a route to improve performance. This study reports on the immobilisation of whole cells in hybrid biochar–alginate beads (BAB) compared with control alginate beads (CAB) during DF. Biochar from oakwood and water hyacinth, pyrolysed at 450 and 600/650 °C, were incorporated into BAB. BAB increased biohydrogen production rates by 1.4–2.6-fold relative to CAB, driven by enhanced microbial attachment, synergistic interactions, and improved mass transfer. High-temperature biochar generated the strongest effects, raising hydrogen yield by up to 23% and shortening the lag phase by 94%. Biochar properties, including porosity, surface area, inorganic content, electrical conductivity and buffering capacity, likely support these effects. These results establish hybrid biochar-alginate support as a promising platform to accelerate DF and advance biohydrogen as a sustainable biofuel. Full article

Nanobubbles have attracted increasing interest in food systems because they can modify gas dispersion, interfacial transport, washing performance, preservation processes, and the structures of dispersed matrices. However, their behavior cannot be interpreted based on bubble size alone. Proteins, polysaccharides, lipids, salts, colloidal particles, gas composition, and processing conditions can alter interfacial adsorption, gas transfer, bubble persistence, and matrix organization in food systems. This review examines the physicochemical mechanisms proposed to explain nanobubble persistence and functionality, with an emphasis on surface charge, interfacial adsorption, gas supersaturation, confinement, and interactions with food biopolymers. A central distinction is made between passive nanobubble-containing systems and externally activated systems involving hydrodynamic cavitation, ultrasound, plasma, pressure fluctuations, and reactive gases. Under passive conditions, nanobubbles mainly act as gas–liquid interfaces that influence local transport and adsorption. In activated systems, microbial inactivation, reactive oxygen species formation, and apparent mass-transfer enhancement often arise from external energy input, gas chemistry, turbulence, and transient supersaturation rather than from nanobubbles alone. Interfacial stability is used here as an organizing concept to connect nanobubble persistence, food-matrix interactions, generation methods, characterization limitations, and interpretation of reported technological effects. Current methods, such as dynamic light scattering and nanoparticle tracking analysis, provide useful size and concentration estimates but cannot unambiguously distinguish nanobubbles from protein aggregates, fat droplets, micelles, polysaccharide assemblies, and other colloidal structures in complex matrices. Therefore, reliable interpretation requires complementary methods, appropriate controls, and standardized reporting of gas composition, generation method, energy input, matrix properties, and processing conditions. Thus, nanobubble-containing technologies show promise for food processing; however, their value depends on the separation of nanoscale interfacial effects from concurrent hydrodynamic, chemical, and matrix-dependent phenomena. Full article

To understand glycan–protein interactions at biological interfaces, designing surfaces modified with structurally controlled glycans is highly important. In particular, naturally occurring glycosaminoglycans (GAGs) possess periodic sugar arrangements that play important roles in protein recognition, highlighting the need for the development of periodic glycopolymer model systems that can serve as GAG mimics for quantitative interaction analysis. In this study, sequence-controlled periodic glycopolymers were synthesized by reversible addition–fragmentation chain-transfer (RAFT) polymerization and immobilized onto gold surfaces to construct glycan-modified interfaces. The synthesized material was a terminally functionalized periodic glycopolymer with the most basic structure, consisting of alternating maltose-containing vinyl ether (MalVE) units and ethyl maleimide (EtMI) units, with a trithiocarbonate group at the ω-terminal. This trithiocarbonate group was converted to a thiol group for immobilization through Au–S bond formation. Structural characterization by ¹H NMR spectroscopy, size exclusion chromatography (SEC), MALDI-TOF mass spectrometry, and UV–vis spectroscopy confirmed the structure as designed. Quartz crystal microbalance (QCM) measurements verified the stable immobilization of thiol-terminated periodic glycopolymers on the gold surface, and allowed for estimation of graft density and quantitative analysis of glycan-protein interactions at the modified interface. The periodic glycopolymer-modified surfaces exhibited selective binding behavior toward concanavalin A (ConA) compared to bovine serum albumin (BSA), with apparent binding constants on the order of 10⁶–10⁷ L mol⁻¹. This enhanced binding behavior indicated that specific and multivalent interactions with proteins also occurred at periodic pendant maltose residues along the main chain. These results demonstrate that the gold surface modified with end-functional periodic glycopolymers synthesized by RAFT polymerization provides a versatile platform for quantitative analysis of glycan-protein interactions and suggests potential applications for periodic glycopolymers as functional materials. Full article

We evaluated a multi-output neural network framework for jointly analyzing maize grain yield (GY) and root lodging percentage (LP) using above-ground morphological traits measured under defined environmental conditions. To address model robustness, the multi-output neural network was compared with linear regression, elastic net, random forest, and XGBoost using repeated five-fold cross-validation, an 80/20 holdout split, and independent year-wise validation. Under repeated cross-validation, XGBoost provided the strongest average predictive performance for both traits, with R² values of 0.57 for GY and 0.67 for LP. The multi-output neural network showed moderate performance, with R² values of 0.49 for GY and 0.57 for LP. Final holdout performance for the neural network for GY and LP was R² = 0.64 and R² = 0.92, respectively. Year-wise validation showed weak temporal transferability because the two seasons differed not only in environmental conditions, but also in lodging mechanism. Repeated permutation importance identified ear width (EW), kernel row number (RNE), thousand kernel mass (KM1000), and kernel number per ear (KNE) as important predictors of GY, while LP prediction was most strongly associated with internode major diameter (IDmajor), ear length (EL), and the number of green leaves (NGL). Across both permutation importance and SHAP, only RNE and NGL were consistently shared between GY and LP. Supplementary ALE diagnostics indicated that RNE showed increasing model-estimated effects for both predicted GY and LP, whereas NGL showed a positive association with predicted GY but a decreasing or nonlinear association with predicted LP. These results show that joint modeling can support exploratory trait interpretation, but the predictive relationships remain environment-specific and should not be interpreted as causal or broadly transferable without further multi-environment validation. Full article

Microplastics (MPs) are increasingly detected in dairy products, raising food-safety concerns. Their behavior in complex food matrices and interactions with probiotic microorganisms remain poorly understood. This exploratory study evaluated storage-dependent changes in operationally defined, digestion-resistant recoverable residues in yogurt containing Bifidobacterium longum subsp. infantis (ATCC 15697). Yogurt samples were prepared with polypropylene (PP), polyethylene (PE), and polystyrene (PS), individually and in combination, and analyzed over 21 days of refrigerated storage. Gravimetric values served as relative, operational indicators of recoverable residues—not validated absolute polymer masses—while polymer identity was qualitatively confirmed by pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS). B. longum subsp. infantis remained viable throughout storage (6.3–8.2 log₁₀ CFU/g). All MP-containing groups showed consistent storage-associated decreases in recoverable residue fractions, greatest in PP, followed by PE and PS; probiotic-free controls remained stable. Polymer-specific Py-GC/MS signals were detectable at all time points. Because polymer identity was retained and the workflow was not validated for absolute recovery, findings are interpreted as storage-associated changes in extractability, filterability, and/or residue recovery—not as polymer degradation, mineralization, or biological removal. These in vitro observations are limited to the yogurt matrix and do not support extrapolation to livestock exposure, human dietary risk, or farm-to-fork transfer. Within these limits, the findings provide a preliminary, hypothesis-generating perspective on probiotic–microplastic interactions in fermented dairy products. Full article

This study investigates numerically a Coupled Solar Ventilation Evaporative Cooling system for hot and arid climates. The system uses a solar wall chimney to produce natural ventilation and generate hot and dry airflow, which is then directed through a roof-mounted humid hay packed bed to enhance evaporative air conditioning. The resulting cold is transferred via a thermally conductive inner roof plate while a membrane condenser recovers moisture for reusing. A mathematical model was developed to describe heat and mass transfer in the hay packed bed, including solar chimney airflow, pressure drop and the evaporation energy balance. Parametric simulations were carried out for inlet air temperature of 40–60 °C, airflow rates of 0.25–0.45 m³/s, hay moisture contents of 0.006–0.014 kg/kg dry basis and air humidity ratio of 0.002–0.006 kg/kg dry air. Results show that evaporative cooling becomes effective only above certain inlet temperature. Increasing airflow from 0.25 to 0.45 m³/s reduced hay temperature from 30 to 26.8 °C when inlet air temperature exceeded 43.5 °C. Higher hay moisture content enhanced cooling performance, reaching about 26 °C, while higher inlet air humidity reduced evaporation and limited cooling. The operating maps obtained from the numerical simulations provide practical guidance for preliminary system sizing and for optimal operating parameters selection in solar-driven evaporative cooling systems. The mathematical model treats the solar chimney, the evaporative packed bed, the conditioned room and the membrane condenser within the same steady state calculation. The solar energy balance and the pressure balance are used to relate the inlet air temperature and the airflow rate to solar irradiance, ambient temperature and chimney geometry. The model also includes the heat transferred from the room through the roof plate, the sensible heat of the supplied water and the mass transfer and pressure drop effects of the membrane condenser. Full article

Models of thermal runaway propagation in lithium-ion batteries are widely used for thermal safety analysis. Current methods, primarily lumped-parameter and 3D models, face challenges in balancing accuracy with computational efficiency. Three-dimensional models offer high accuracy at high computational cost, while lumped-parameter models are faster but less accurate. For instance, the battery shell is included in lumped-parameter models but often omitted in 3D models. This study focuses on a 37 Ah ternary lithium-ion battery, with Li(NiCoMn)_1/3O₂ as the cathode material and graphite as the anode material. The propagation of thermal runaway in the battery array is triggered by nail penetration. A lithium-ion battery thermal runaway propagation model is proposed, combining the lumped-parameter method with 3D modeling. The model primarily describes the heat transfer characteristics of the shell using a series connection of thermal capacitance and several thermal resistances. The shell temperature is then calculated by weighting the temperatures associated with the thermal capacitance and thermal resistances using specific weight coefficients. The joint model is detailed and applied to study thermal runaway propagation in one- and two-dimensional battery arrays. For the one-dimensional array, based on the three-dimensional simulation data and calculation time, the joint model shows only a 1.32% average deviation in propagation time compared to full 3D simulation, while maintaining good temperature agreement. It also reduces solution time by 70.22%. These findings confirm that the proposed model effectively enhances both the efficiency and accuracy of thermal runaway simulations, supporting improved safety analysis for lithium-ion battery systems. Full article