Search Results (742)

Oily wastewater is a critical environmental concern, and the high costs and fouling of conventional membranes drive the search for low-cost, efficient alternatives. This study evaluates surface-modified quartz particles for oil–water separation, focusing on hydrophilic and hydrophobic coatings. Quartz samples underwent washing, hydrophobic coating, and hydrophilic coating, with morphological and elemental changes assessed using scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM–EDS). Oil and grease (O&G) content was determined via the EPA 1664 method under high-solids conditions. The untreated oil–water mixture contained 142,955.9 mg/L O&G. Hydrophilic-coated quartz achieved the greatest reduction, producing water with only 751.3 mg/L O&G, indicating excellent oil rejection and water selectivity. Washed quartz performed similarly at 837.1 mg/L. Hydrophobic-coated quartz, while yielding higher residual oil in water (64,198.9 mg/L), demonstrated strong oil affinity, making it more suitable for oil recovery applications. Raw quartz, tested without heavy oil loading, showed a baseline of 13.4 mg/L. These results confirm that surface engineering of quartz enables tunable separation properties, where hydrophilic surfaces favor water purification and hydrophobic surfaces enhance oil capture. The findings provide a pathway for scalable, cost-effective, and application-specific oily wastewater treatment solutions. Full article

Background/Objectives: Recent evidence challenges the classical chemiosmotic theory, suggesting that proton movement along membrane surfaces—not bulk-phase gradients—drives bioenergetic processes. Proton accumulation on membranes like the myelin sheath and endoplasmic reticulum (ER) may represent a universal mechanism for cellular energy storage. This study investigates whether phospholipids from these membranes, combined with anionic bee venom proteins, enhance proton absorption, potentially elucidating a novel bioenergetic pathway. Methods: Five phospholipids (phosphatidylethanolamine, phosphatidylserine, phosphatidylinositol, sphingomyelin, phosphatidylcholine) from rat liver were isolated to model myelin/ER membranes. Anionic proteins (pI 5.65–5.80) were purified from bee venom via cation exchange chromatography. Liposomes (with/without proteins) were prepared, and proton absorption was quantified by pH changes in suspensions versus pure water. Statistical significance was assessed via ANOVA and t-tests. Results: All phospholipid liposomes examined in this study absorbed protons under the tested conditions, with phosphatidylethanolamine showing the highest capacity (pH increase: 7.00 → 7.18). Liposomes enriched with anionic proteins exhibited significantly greater proton absorption (e.g., phosphatidylserine + proteins: pH 8.15 vs. 7.15 alone; p < 2.43 × 10⁻⁶). Sphingomyelin-protein liposomes absorbed the most protons, suggesting that protein–phospholipid interactions modulate surface proton affinity. Conclusions: Anionic bee venom proteins amplify proton absorption by phospholipid membranes, supporting the hypothesis that lipid–protein complexes act as “proton capacitors”. This mechanism may underpin extramitochondrial energy storage in myelin and ER. Pharmacologically, targeting these interactions could mitigate bioenergetic deficits in aging or disease. Further research should define the structural basis of proton capture by membrane-anchored proteins. Full article

Dry ice, the solid form of carbon dioxide (CO₂), is widely used in cold chain logistics, industrial cleaning, and biomedical preservation. Its production, however, is closely linked to carbon capture, energy-intensive liquefaction, and solidification processes. This review critically evaluates and compares the existing methods of CO₂ capture, including chemical absorption, physical absorption, adsorption, and membrane-based separation as they pertain to dry ice production. This study further assesses liquefaction cycles using refrigerants such as ammonia and R744, highlighting thermodynamic and environmental trade-offs. Solidification techniques are examined in the context of energy consumption, process integration, and product quality. The comparative analysis is supported by extensive tabulated data on operating conditions, CO₂ purity, and sustainability metrics. This review identifies key technical and environmental challenges, such as solvent regeneration, CO₂ leakage, and energy recovery. Thus, it also explores emerging innovations, including hybrid cycles and renewable energy integration, to advance the sustainability of dry ice production. This, in turn, offers strategic insight for optimizing dry ice manufacturing in alignment with low-carbon industrial goals. Full article

Chronic respiratory diseases claim nearly four million lives annually, making them the third leading cause of death worldwide. Extracorporeal membrane oxygenation (ECMO) is often the last line of support for patients with severe lung failure. Still, its performance is limited by an incomplete understanding of gas exchange in hollow fiber membrane (HFM) oxygenators. Computational fluid dynamics (CFD) has become a robust oxygenator design and optimization tool. However, most models oversimplify O₂ and CO₂ transport by ignoring their physiological coupling, instead relying on fixed saturation curves or constant-content assumptions. For the first time, this study introduces a novel physiologically informed CFD model that integrates the Bohr and Haldane effects to capture the coupled transport of oxygen and carbon dioxide as functions of local pH, temperature, and gas partial pressures. The model is validated against in vitro experimental data from the literature and assessed against established CFD models. The proposed CFD model achieved excellent agreement with experiments across blood flow rates (100–500 $\mathrm{mL}/\min$ ), with relative errors below 5% for oxygen and 10–15% for carbon dioxide transfer. These results surpassed the accuracy of all existing CFD approaches, demonstrating that a carefully formulated single-phase model combined with physiologically informed diffusivities can outperform more complex multiphase simulations. This work provides a computationally efficient and physiologically realistic framework for oxygenator optimization, potentially accelerating device development, reducing reliance on costly in vitro testing, and enabling patient-specific simulations. Full article

Effective thermal management is crucial for optimizing the performance, efficiency, and durability of fuel-cell technologies, including proton-exchange membrane fuel cells (PEMFCs) and solid-oxide fuel cells (SOFCs). The operation of fuel cells involves complex heat generation mechanisms, primarily driven by electrochemical reactions, which can lead to significant energy loss as heat. This review examines the specific heat generation sources and challenges associated with different fuel-cell types, highlighting the critical importance of effective thermal management strategies. Key techniques for thermal regulation, including active and passive cooling systems, are examined in detail. Active cooling methods like liquid cooling and air cooling are effective in dissipating excess heat, while passive methods leverage advanced materials and optimized designs to enhance natural heat dissipation. Furthermore, innovative heat recovery systems are explored, demonstrating their potential to enhance overall energy efficiency by capturing and repurposing waste heat. The integration of machine learning techniques has arisen as a promising avenue for advancing temperature control in fuel cells. Reinforcement learning, deep learning algorithms, and support vector machines, along with artificial neural networks, are discussed in the context of their application in managing temperature dynamics and optimizing thermal performance. The review also emphasizes the significance of real-time monitoring, as well as adaptive control strategies to respond effectively to the dynamic operating conditions of fuel cells. Understanding and applying these thermal management strategies is essential for the successful commercialization of fuel cells across various sectors, ranging from automotive to stationary power generation. With the growing demand for clean energy solutions, progress in thermal management techniques will be crucial in improving the dependability and practicality of fuel-cell systems. Full article

Designing efficient nanoparticle-enhanced CO₂ capture systems is challenging due to the diversity of nanoparticles, solvent formulations, reactor configurations, and operating conditions. This study presents the first ANN-based meta-analysis framework developed to predict CO₂ absorption enhancement across multiple reactor systems, including batch reactors, packed columns, and membrane contactors. A curated dataset of 312 experimental data points was compiled from literature, and an artificial neural network (ANN) model was trained using six input variables: nanoparticle type, concentration, system configuration, base fluid, pressure, and temperature. The proposed model achieved high predictive accuracy (R² > 0.92; RMSE: 4.2%; MAE: 3.1%) and successfully captured complex nonlinear interactions. Feature importance analysis revealed nanoparticle concentration (28.3%) and system configuration (22.1%) as the most influential factors, with functionalized nanoparticles such as Fe₃O₄@SiO₂-NH₂ showing superior performance. The model further predicted up to 130% enhancement for ZnO in optimized membrane contactors. This AI-driven tool provides quantitative insights and a scalable decision-support framework for designing advanced nanoparticle–solvent systems, reducing experimental workload, and accelerating the development of sustainable CO₂ capture technologies. Full article

Understanding the molecular structure and water transport behavior in anion-exchange membranes (AEMs) is essential for advancing efficient and cost-effective alkaline fuel cells. In this study, large-scale all-atom molecular dynamics simulations of QPAF-4, a promising AEM material, were performed at multiple water uptakes (λ = 2, 3, 6, and 13). The simulated systems comprised approximately 1.4 to 2.1 million atoms and spanned approximately 26 nm, thus enabling direct comparison with both wide-angle X-ray scattering (WAXS) and small-angle X-ray scattering (SAXS) experiments. The simulations successfully reproduced experimentally observed structure factors, accurately capturing microphase-separated morphologies at the mesoscale ($~$8 nm). Decomposition of the SAXS profile into atom pairs suggests that increasing water uptake may facilitate the aggregation of fluorinated alkyl chains. Furthermore, the calculated pair distribution functions showed excellent agreement with WAXS data, suggesting that the atomistic details were accurately reproduced. The water dynamics exhibited strong dependence on hydration level: At low water uptake, mean squared displacement showed persistent subdiffusive behavior even at long timescales ($~$200 ns), whereas almost normal diffusion was observed when water uptake was high. These results suggest that water mobility may be significantly influenced by nanoconfinement and strong interactions exerted by polymer chains and counterions under dry conditions. These findings provide a basis for the rational design and optimization of high-performance membrane materials. Full article

This study developed a dual-antibody sandwich ELISA detection method for Photobacterium damselae, an important pathogen in aquaculture, based on two outer membrane proteins of outer membrane protein C (OmpC) and β-barrel assembly machinery A (BamA) from the strain of P. damselae XP11. By optimizing the reaction concentrations of the capture antibody of rabbit anti-OmpC or anti-BamA and the HRP-labeled detection antibody of rabbit anti-BamA, it was found that using 1.0 μg/mL of rabbit anti-OmpC or 0.9 μg/mL of rabbit anti-BamA as capture antibodies, and 0.90 μg/mL of HRP-labeled rabbit anti-BamA as the detection antibody, could specifically detect different isolates of P. damselae. The detection limit of this method for the supernatant protein of P. damselae disrupted by ultrasound was 0.2 μg/mL. Repeatability tests showed that the coefficient of variation for detecting 25 strains of bacteria was below 9.1%. Compared with the OmpC-BamA sandwich ELISA detection method, the BamA–BamA combination exhibited better specificity. The results of this study provide an important reference for the rapid detection of P. damselae and other bacterial pathogens in aquaculture. Full article

Sulfides are frequently encountered in natural mineral water and different wastewater streams, and their presence significantly impedes subsequent water treatment or utilization. Sulfide removal, or at least its reduction, can be accomplished in different ways, but there is one straightforward method where sulfide is captured on a carbon-based sorbent, with the consequent sorbent regeneration producing electricity in liquid fuel cell mode. This multi-functional approach combines sulfide removal, energy generation, and water pre-treatment for various applications. The present work aims to show sulfide removal from sulfide-containing wastewater streams from alcohol and beverage manufacturing. The clean water could be used for biogas production. Sorbent regeneration was performed in fuel cell mode and was accompanied by electricity production. The experiments, conducted in a liquid-phase fuel cell, used electrode compartments that were separated by an anion-exchange membrane. Electroconductive charcoal, produced via the pyrolysis of residues from tire production and doped with zinc oxide, was used as a sorbent. The experimental treatments of vinasse, whey, and stillage for sulfide removal by this method show the sustainable performance of the sorbent for up to twelve consecutive runs. The biogas yield produced from vinasse was increased more than three times for the treated substrate compared to the reference case. Full article

Nanoporous gold nanoparticles (np-AuNPs) combine inertness, a nanoscale structure, and a porous framework with high surface area, conductivity, and biocompatibility, making them ideal for biosensing, catalysis, fuel cells, and drug delivery. Their open pore structure and low-coordinated atoms enhance biomolecule capture and mass transfer, while their tunable size, pore volume, and ease of surface modification make them promising biosensor transducers. However, synthesizing colloidal np-AuNPs in a simple way with controllable size and scalability remains challenging. The existing approaches mostly rely on specialized equipment, complex setups, and expert knowledge, while still facing challenges in terms of scalability. In this study, we present a simple, seedless, wet-chemical synthesis of colloidal np-AuNPs via the co-reduction of Au/Ag alloys followed by dealloying. By adjusting the Au:Ag ratio, we produced np-AuNPs sized ~120–530 nm, which were immobilized on electrodes for detecting lipopolysaccharide (LPS), a toxic component of Gram-negative bacterial membranes. The LPS biosensor exhibited excellent sensitivity towards detecting wild-type LPS, with a low limit of detection (LOD) of 0.1244 ng/L. This work demonstrates the effective synthesis and application of np-AuNPs in LPS biosensing. Full article

Liposomes are nanoscale, spherical vesicles composed of phospholipid bilayers, typically ranging from 50 to 200 nm in diameter. Their unique ability to encapsulate both hydrophilic and hydrophobic molecules makes them powerful nanocarriers for drug delivery, diagnostics, and vaccine formulations. Several FDA-approved formulations such as Doxil^® (Baxter Healthcare Corporation, Deerfield, IL, USA), AmBisome^® (Gilead Sciences, Inc., Foster City, CA, USA), and Onivyde^® (Ipsen Biopharmaceuticals, Inc., Basking Ridge, NJ, USA) highlight their clinical significance. This review provides a comprehensive synthesis of how molecular dynamics (MD) simulations, particularly coarse-grained (CG) and atomistic approaches, advance our understanding of liposomal membranes. We explore key membrane biophysical properties, including area per lipid (APL), bilayer thickness, segmental order parameter ($S_{CD}$), radial distribution functions (RDFs), bending modulus, and flip-flop dynamics, and examine how these are modulated by cholesterol concentration, PEGylation, and curvature. Special attention is given to curvature-induced effects in spherical vesicles, such as lipid asymmetry, interleaflet coupling, and stress gradients across the leaflets. We discuss recent developments in vesicle modeling using tools such as TS2CG, CHARMM-GUI Martini Maker, and Packmol, which have enabled the simulation of large-scale, compositionally heterogeneous systems. The review also highlights simulation-guided strategies for designing stealth liposomes, tuning membrane permeability, and enhancing structural stability under physiological conditions. A range of CG force fields, MARTINI, SPICA, SIRAH, ELBA, SDK, as well as emerging machine learning (ML)-based models, are critically assessed for their strengths and limitations. Despite the efficiency of CG models, challenges remain in capturing long-timescale events and atomistic-level interactions, driving the development of hybrid multiscale frameworks and AI-integrated techniques. By bridging experimental findings with in silico insights, MD simulations continue to play a pivotal role in the rational design of next-generation liposomal therapeutics. Full article

Red blood cell (RBC), accounting for approximately 45% of total blood volume, are essential for oxygen delivery and carbon dioxide removal. Their unique biconcave morphology, high surface area-to-volume ratio, and remarkable deformability enable them to navigate microvessels narrower than their resting diameter, ensuring efficient microcirculation. RBC deformability is primarily determined by membrane viscoelasticity, cytoplasmic viscosity, and cell geometry, all of which can be altered under various physiological and pathological conditions. Reduced deformability is a hallmark of numerous diseases, including sickle cell disease, malaria, diabetes mellitus, sepsis, ischemia–reperfusion injury, and storage lesions in transfused blood. As these mechanical changes often precede overt clinical symptoms, RBC deformability is increasingly recognized as a sensitive biomarker for disease diagnosis, prognosis, and treatment monitoring. Over the past decades, diverse techniques have been developed to measure RBC deformability. These include single-cell methods such as micropipette aspiration, optical tweezers, atomic force microscopy, magnetic twisting cytometry, and quantitative phase imaging; bulk approaches like blood viscometry, ektacytometry, filtration assays, and erythrocyte sedimentation rate; and emerging microfluidic platforms capable of high-throughput, physiologically relevant measurements. Each method captures distinct aspects of RBC mechanics, offering unique advantages and limitations. This review synthesizes current knowledge on the pathophysiological significance of RBC deformability and the methods for its measurement. We discuss disease contexts in which deformability is altered, outline mechanical models describing RBC viscoelasticity, and provide a comparative analysis of measurement techniques. Our aim is to guide the selection of appropriate approaches for research and clinical applications, and to highlight opportunities for developing robust, clinically translatable diagnostic tools. Full article

Arthrobotrys flagrans, a typical nematode-trapping fungus (NTF) that produces a three-dimensional adhesive network to capture nematodes, has excellent potential for the development of biocontrol agents against both plant and animal parasitic nematodes. Proteins containing the common fungal extracellular membrane (CFEM) domain are important for the nematodes’ trapping by A. flagrans. The loss of AfCFEM1 and AfCFEM3 resulted in a significant upregulation of proteins associated with fungal pathogenicity, forming a denser adhesive material on the trap surface and ultimately increasing nematode mortality. However, the disruption of AfCFEM2 led to the opposite result. Furthermore, the deletion of AfCFEM1-3 not only affected trap morphology, resulting in an increased proportion of irregular traps (i.e., trap cells not fused to the hyphae), but also led to a thinner cell wall of the traps. In addition, the compensatory effects among the CFEM family and other families were demonstrated. This study revealed that the AfCFEM1-3 genes in A. flagrans participated in the formation of traps, adhesive material and cell wall, and pathogenicity, providing new insights into the functions of AfCFEM in the process of nematode trapping by NTF. Full article

Low inner leaves in the thick canopy of dense Chinese fir plantations frequently show premature senescence and dieback regardless of age. To elucidate the underlying mechanisms, a 28-day growth chamber experiment was conducted under dark conditions to induce leaf senescence. Changes in leaf area, photosynthetic performance, and the responses of carbon metabolism and the antioxidant defense system were analyzed. Leaf area decreased significantly with time in darkness. The photosystem II reaction center was damaged, and fluorescence parameters and chlorophyll contents decreased, resulting in reduced light energy capture and conversion efficiencies. Photosynthetic rate, apparent quantum yield, stomatal conductance, transpiration rate, and light use efficiency all decreased, while the light compensation point and intercellular CO₂ concentration increased. Antioxidant enzyme activities initially increased but eventually collapsed as the stress continued and H₂O₂ and malondialdehyde accumulated, causing membrane conductivity, i.e., membrane permeability, to increase by 122%. Meanwhile, reduced non-structural carbohydrates, especially total non-structural carbohydrates content, decreased by 45.32%, triggering sugar starvation and accelerating aging. Our study provided new physiological evidence for light-stress response mechanisms in Chinese fir. Specifically, it revealed that dark-induced leaf senescence was mainly caused by irreversible damage to the photosynthetic apparatus and oxidative stress, which together led to carbon starvation and ultimately death. Full article

Carbon dioxide (CO₂) released from natural or even anthropogenic sources may lead to an increase in the average global temperature and ultimately a climate shift. Thus, protecting the environment by reducing CO₂ concentration is a global concern. The recent approach of integrating CO₂ through capture, utilization, and storage seems to be an effective eradication technique. Even though a wide range of CO₂ capture strategies have been successfully adopted, there is an urgent need to compare these based on their advantages and weaknesses to define the development direction for future perspectives. Several materials have been used for capturing CO₂. Thus, we have elaborated and compared the current state of CO₂ capture strategies, including post-combustion CO₂ capture and direct air CO₂ capture. Strategies adopted under post-combustion CO₂ capture, including liquid- and solid-based sorbents, membrane-based separators, and electrochemical reduction, have been explained in detail, including their advantages, weaknesses, and potential risks. Thus, this review presents a thorough analysis of CO₂ capture in terms of material developments and manufacturing techniques, with some research gaps for future development. Full article