Ultra-antiwetting Membrane for Hypersaline Water Crystallization in Membrane Distillation.

Membrane distillation (MD) has great potential in the management of hypersaline water for zero liquid discharge (ZLD) due to its high salinity tolerance. However, the membrane wetting issue significantly restricts its practical application. In this study, a composite membrane tailored for extreme concentrations and even crystallization of hypersaline water is synthesized by coating a commercial hydrophobic porous membrane with a composite film containing a dense polyamide layer, a cation exchange layer (CEL), and an anion exchange layer (AEL). When used in direct contact MD for treating a 100 g L-1 NaCl hypersaline solution, the membrane achieves supersaturation of feed solution and a salt crystal yield of 38.0%, with the permeate concentration at <5 mg L-1. The composite membrane also demonstrates ultrahigh antiwetting stability in 360 h of long-term operation. Moreover, ion diffusion analysis reveals that the ultrahigh wetting resistance of the composite membrane is attributed to the bipolar AEL and CEL that eliminate ion crossover. The literature review elucidates that the composite membrane is superior to state-of-the-art membranes. This study demonstrates the great potential of the composite membrane for direct crystallization of hypersaline water, offering a promising approach to filling the gap between reverse osmosis and conventional thermal desalination processes for ZLD application.

Comparative Analysis of Hydrosol Volatile Components of Citrus × Aurantium 'Daidai' and Citrus × Aurantium L. Dried Buds with Different Extraction Processes Using Headspace-Solid-Phase Microextraction with Gas Chromatography-Mass Spectrometry.

This work used headspace solid-phase microextraction with gas chromatography-mass spectrometry (HS-SPME-GC-MS) to analyze the volatile components of hydrosols of Citrus × aurantium 'Daidai' and Citrus × aurantium L. dried buds (CAVAs and CADBs) by immersion and ultrasound-microwave synergistic-assisted steam distillation. The results show that a total of 106 volatiles were detected in hydrosols, mainly alcohols, alkenes, and esters, and the high content components of hydrosols were linalool, α-terpineol, and trans-geraniol. In terms of variety, the total and unique components of CAVA hydrosols were much higher than those of CADB hydrosols; the relative contents of 13 components of CAVA hydrosols were greater than those of CADB hydrosols, with geranyl acetate up to 15-fold; all hydrosols had a citrus, floral, and woody aroma. From the pretreatment, more volatile components were retained in the immersion; the relative contents of linalool and α-terpineol were increased by the ultrasound-microwave procedure; and the ultrasound-microwave procedure was favorable for the stimulation of the aroma of CAVA hydrosols, but it diminished the aroma of the CADB hydrosols. This study provides theoretical support for in-depth exploration based on the medicine food homology properties of CAVA and for improving the utilization rate of waste resources.

Ammonia recovery via direct contact membrane distillation: Modeling and performance optimization.

Ammonia recovery from wastewater has positive environmental benefits, avoiding eutrophication and reducing production energy consumption, which is one of the most effective ways to manage nutrients in wastewater. Specifically, ammonia recovery by membrane distillation has been gradually adopted due to its excellent separation properties for volatile substances. However, the global optimization of direct contact membrane distillation (DCMD) operating parameters to maximize ammonia recovery efficiency (ARE) has not been attempted. In this work, three key operating factors affecting ammonia recovery, i.e., feed ammonia concentration, feed pH, and DCMD running time, were identified from eight factors, by a two-level Plackett-Burman Design (PBD). Subsequently, Box-Behnken design (BBD) under the response surface methodology (RSM) was used to model and optimize the significant operating parameters affecting the recovery of ammonia though DCMD identified by PBD and statistically verified by analysis of variance (ANOVA). Results showed that the model had a high coefficient of determination value (R2 = 0.99), and the interaction between NH4Cl concentration and feed pH had a significant effect on ARE. The optimal operating parameters of DCMD as follows: NH4Cl concentration of 0.46 g/L, feed pH of 10.6, DCMD running time of 11.3 h, and the maximum value of ARE was 98.46%. Under the optimized conditions, ARE reached up to 98.72%, which matched the predicted value and verified the validity and reliability of the model for the optimization of ammonia recovery by DCMD process.

Improving membrane distillation performance by Fe(II) activated sodium percarbonate oxidation during the treatment of shale gas produced water.

Membrane distillation (MD) offers promise for recycling shale gas produced water (SGPW), while membrane fouling is still a major obstacle in standalone MD. Herein, sodium percarbonate (SPC) oxidation was proposed as MD pretreatment, and the performance of the single MD, SPC-MD hybrid process and Fe(II)/SPC-MD hybrid process for SGPW treatment were systematically evaluated. Results showed that compared to raw SGPW, the application of SPC and Fe(II)/SPC led to the decrease of the fluorescent organics by 28.54 % and 54.52 %, respectively. The hydrophobic fraction decreased from 52.75 % in raw SGPW to 37.70 % and 27.20 % for SPC and Fe(II)/SPC, respectively, and the MD normalized flux increased from 0.19 in treating raw SGPW to 0.65 and 0.81, respectively. The superiority of SPC oxidation in reducing the deposited membrane foulants and restoring membrane properties was further confirmed through scanning electron microscopy observation, attenuated total reflection fourier transform infrared, water contact angle and surface tension analyses of fouled membranes. Correlation analysis revealed that hydrophobic/hydrophilic matters and fluorescent organics in SGPW took a crucial role in MD fouling. The mechanism of MD fouling mitigation by Fe(II)/SPC oxidation was attributed to the decrease in concentrations and hydrophobicity of organic by synergistic oxidation, coagulation and adsorption.

The Effect of Technological Conditions on ABE Fermentation and Butanol Production of Rye Straw and the Composition of Volatile Compounds.

The objective of this study was to evaluate the effect of pretreatment and different technological conditions on the course of ABE fermentation of rye straw (RS) and the composition of volatile compounds in the distillates obtained. The highest concentration of ABE and butanol was obtained from the fermentation of pretreated rye straw by alkaline hydrolysis followed by detoxification and enzymatic hydrolysis. After 72 h of fermentation, the maximum butanol concentration, productivity, and yield from RS were 16.11 g/L, 0.224 g/L/h, and 0.402 g/g, respectively. Three different methods to produce butanol were tested: the two-step process (SHF), the simultaneous process (SSF), and simultaneous saccharification with ABE fermentation (consolidation SHF/SSF). The SHF/SSF process observed that ABE concentration (21.28 g/L) was higher than in the SSF (20.03 g/L) and lower compared with the SHF (22.21 g/L). The effect of the detoxification process and various ABE fermentation technologies on the composition of volatile compounds formed during fermentation and distillation were analyzed.

Innovative hyper-thermophilic aerobic submerged membrane distillation bioreactor for wastewater reclamation.

For the first time, a hyper-thermophilic aerobic (>60 °C) bioreactor has been integrated with direct submerged membrane distillation (MD), highlighting its potential as an advanced wastewater treatment solution. The hyper-thermophilic aerobic bioreactor, operating up to 65 °C, is tailored for high organic removal, while MD efficiently produces clean water. Throughout the study, high removal rates of 99.5% for organic matter, 96.4% for ammonia, and 100% for phosphorus underscored the impressive adaptability of microorganisms to challenging hyper-thermophilic conditions and a successful combination with the MD process. Despite the extreme temperatures and substantial salinity accumulation reaching up to 12,532 µS/cm, the biomass of microorganisms increased by 1.6 times over a 92-day period, representing their remarkable resilience. The distillation flux ranged from 6.15 LMH to 8.25 LMH, benefiting from the temperature gradient in the hyper-thermophilic setting and the design of the tubular submerged MD membrane module. The system also excels in pH control, utilizing fewer alkali and nutritional resources than conventional systems. Meiothermus, Firmicutes, and Bacteroidetes, the three dominant species, played a crucial role, showcasing their significance in adapting to high salinity and decomposing organic matter.

An in-depth analysis of membrane distillation research (1990-2023): Exploring trends and future directions through bibliometric approach.

This bibliometric analysis offers a comprehensive investigation into membrane distillation (MD) research from 1990 to 2023. Covering 4389 publications, the analysis sheds light on the evolution, trends, and future directions of the field. It delves into authorship patterns, publication trends, prominent journals, and global contributions to reveal collaborative networks, research hotspots, and emerging themes within MD research. The findings demonstrate extensive global participation, with esteemed journals such as Desalination and the Journal of Membrane Science serving as key platforms for disseminating cutting-edge research. The analysis further identifies crucial themes and concepts driving MD research, ranging from membrane properties to strategies for mitigating membrane fouling. Co-occurrence analysis further highlights the interconnectedness of research themes, showcasing advancements in materials, sustainable heating strategies, contaminant treatment, and resource management. Overlay co-occurrence analysis provides temporal perspective on emerging research trends, delineating six key topics that will likely shape the future of MD. These include innovations in materials and surface engineering, sustainable heating strategies, emerging contaminants treatment, sustainable water management, data-driven approaches, and sustainability assessments. Finally, the study serves as a roadmap for researchers and engineers navigating the dynamic landscape of MD research, offering insights into current trends and future trajectories, ultimately aiming to propel MD technology towards enhanced performance, sustainability, and global relevance.

Membrane fouling analysis of air-gap membrane distillation (AGMD) for recovery of water and removal of antibiotics from a model wastewater containing antibiotics and humic acid.

The study investigates the efficiency of air-gap membrane distillation (AGMD) in water recovery and antibiotics removal from wastewater, focusing on high-concentration scenarios. Experimental findings reveal enhanced membrane performance with increasing the feed temperature, resulting in vapor permeate fluxes of up to 5 kg/m2.h at higher temperatures. Despite experiencing flux reduction caused by fouling from humic acid (HA) in the feed antibiotics solution, the antibiotics consistently maintain near-complete rejection rates (>99%) over 48 h. The foulant on the membrane surface was illustrated by SEM imaging. To know the temperature polarization and the fouling resistance, mathematical modeling was used, and it validates experimental results, elucidating temperature polarization effects and mass transfer coefficients. An increase in feed flow rates reduced thermal boundary layers, enhancing heat flux. Higher temperatures reduced HA fouling resistance. Therefore, AGMD proves effective in water recovery and antibiotics removal, with mathematical models aiding fouling understanding for future research and detailed computational fluid dynamics (CFD) models.

Comparison of quantity, quality and antibacterial activity of essential oil Mentha longifolia (L.) L. under different traditional and modern extraction methods.

Extraction is the first and most important step in obtaining the effective ingredients of medicinal plants. Mentha longifolia (L.) L. is of considerable economic importance as a natural raw material for the food and pharmaceutical industries. Since the effect of different extraction methods (traditional and modern methods) on the quantity, quality and antimicrobial activity of the essential oil of this plant has not been done simultaneously; the present study was designed for the first time with the aim of identifying the best extraction method in terms of these features. For this purpose, extracting the essential oil of M. longifolia with the methods of hydrodistillation with Clevenger device (HDC), steam distillation with Kaiser device (SDK), simultaneous distillation with a solvent (SDE), hydrodistillation with microwave device (HDM), pretreatment of ultrasonic waves and Clevenger (U+HDC) and supercritical fluid (SF) were performed. Chemical compounds were identified by gas chromatography coupled with mass spectrometer (GC-MS). Antimicrobial activity of essential oils against various clinical microbial strains was evaluated by agar diffusion method and determination of the minimum inhibitory concentration and minimum bactericidal concentration (MIC and MBC). The results showed that the highest and lowest yields of M. longifolia leaf essential oil belonged to HDC (1.6083%) and HDM (0.3416%). The highest number of compounds belonged to SDK essential oil and was equal to 72 compounds (with a relative percentage of 87.13%) and the lowest number of compounds was related to the SF essential oil sample (7 compounds with a relative percentage of 100%). Piperitenone (25.2-41.38%), piperitenone oxide (22.02-0%), pulegone (10.81-0%) and 1,8-cineole (5-35.0%) are the dominant and main components of M. longifolia essential oil were subjected to different extraction methods. Antimicrobial activity results showed that the lowest MIC value belonged to essential oils extracted by HDM, SDK, SDE and U+HDC methods with a value of 1000 µg/mL was observed against Gram-negative bacteria Shigella dysenteriae, which was 5 times weaker than rifampin and 7 times weaker than gentamicin. Therefore, it can be concluded that in terms of efficiency of the HDC method, in terms of the percentage of compounds of the HDM method, and in terms of microbial activity, the SDK, HDM and U+HDC methods performed better.

Maximizing the wetting resistance of fluorine-free omniphobic membranes for hypersaline wastewater desalination.

Membrane distillation (MD) equipped with omniphobic (non-wetting) membranes has found a niche in water reclamation from hypersaline industrial wastewater. Here, we examined the efficacy of non-fluorinated materials as surface coating agents for omniphobic MD membrane fabrication, and identified necessary mechanisms to attain a maximized wetting resistance using fluorine-free materials. We first prepared MD membranes with different surface chemistries using a series of linear alkylsilanes and polydimethylsiloxane (PDMS) as representative fluorine-free, low surface energy materials. Membranes modified with a longer chain alkylsilane exhibited a lower surface energy and demonstrated a greater wetting resistance in direct contact MD experiments using feedwaters of various surface tensions. Despite the nearly identical surface energy measured for the longest alkylsilane and PDMS, PDMS-modified membrane exhibited an extended antiwetting performance as compared to the membrane treated with the longest alkylsilane. To elucidate the source of the distinctive wetting resistance, we examined the nucleation and condensation kinetics on the surfaces with the different surface chemistries via environmental scanning electron microscopy. Our analysis suggests that the membranes treated with long chain alkylsilanes contain surface defects (i.e., hydrophilic regions) whereas the high mobility of the PDMS effectively minimizes the defect exposure, slowing down the condensation and subsequent surface wetting.

Influence of photothermal nanomaterials localization within the electrospun membrane structure on purification of saline oily wastewater based on photothermal vacuum membrane distillation.

Today, synergistic combination of special nanomaterials (NMs) and electrospinning technique has emerged as a promising strategy to address both water scarcity and energy concerns through the development of photothermal membranes for wastewater purification and desalination. This work was organized to provide a new perspective on membrane design for photothermal vacuum membrane distillation (PVMD) through optimizing membrane performance by varying the localization of photothermal NMs. Poly(vinylidene fluoride) omniphobic photothermal membranes were prepared by localizing graphene oxide nanosheets (GO NSh) (1) on the surface (0.2 wt%), (2) within the nanofibers structure (10 wt%) or (3) in both positions. Considering the case 1, after 7 min exposure to the 1 sun intensity light, the highest temperature (∼93.5 °C) was recorded, which is assigned to the accessibility of GO NSh upon light exposure. The case 3 yielded to a small reduction in surface temperature (∼90.4 °C) compared to the case 1, indicating no need to localize NMs within the nanofibers structure when they are localized on the surface. The other extreme belonged to the case 2 with the lowest temperature of ∼71.3 °C, which is consistent with the less accessibility of GO NSh during irradiation. It was demonstrated that the accessibility of photothermal NMs plays more pronounced role in the membrane surface temperature compared to the light trapping. However, benefiting from higher surface temperature during PVMD due to enhanced accessibility of photothermal NMs is balanced out by decrease in the permeate flux (case 1: 1.51 kg/m2 h and case 2: 1.83 kg/m2 h) due to blocking some membrane surface pores by the binder. A trend similar to that for flux was also followed by the efficiency. Additionally, no change in rejection was observed for different GO NSh localizations.

Preparation of High-Purity Docosahexaenoic Acid Ethyl Ester from Algal Oil through Enzymatic Ethanolysis.

Docosahexaenoic acid plays a crucial role in infant brain function, and the market demand of high-purity docosahexaenoic acid is continuously increasing. The availability of docosahexaenoic acid in natural fish oil is limited, prompting the exploration of alternative sources like microalgae. For algal oil, enzymatic ethanolysis is preferred to chemical methods because the former is milder and can avoid docosahexaenoic acid oxidation. However, enzymatic methods have generally low yield due to the poor substrate-specificity of lipase to long-chain polyunsaturated fatty acids, affecting the yield and purity of docosahexaenoic acid. Therefore, we developed an efficient process to produce high-purity docosahexaenoic acid ethyl ester from algal oil, by screening lipases, optimizing enzymatic ethanolysis and applying molecular distillation. Lipase UM1 was the best lipase to produce ethyl ester from algal oil with the highest ethyl ester yield (95.41%). Meanwhile, it was a catalyst for the reaction of long-chain polyunsaturated fatty acids with ethanol. The fatty acid docosahexaenoic acid conversion rates exceeded 90%. After molecular distillation, a final product containing 96.52% ethyl ester was obtained with a docosahexaenoic acid content up to 80.11%. Our findings provide an highly effective enzymatic method for the production of high-purity docosahexaenoic acid ethyl esters, with potential commercial applications.

Performances of PTFE and PVDF membranes in achieving the discharge limit of mixed anodic oxidation coating wastewaters treated by membrane distillation.

The mixed wastewater generated by anodic oxidation coating facilities contains high levels of various contaminants, including iron, aluminum, conductivity, chemical oxygen demand (COD), and sulfate. In this study, the effectiveness of the membrane distillation (MD) process using polytetrafluoroethylene (PTFE) and polyvinylidene fluoride (PVDF) membranes was investigated to treat mixed wastewater from an anodized coating factory. The results indicate that both hydrophobic membranes effectively removed targeted contaminants. However, the PTFE membrane achieved higher removal efficiencies, with over 99% removal of sulfate, conductivity, iron, and aluminum, 85.7% of COD, and 86% of total organic carbon (TOC). In contrast, the PVDF membrane exhibited a significant decline in removal efficiency as the temperature increased and performed well only at lower feed temperatures. The PTFE membranes outperformed the PVDF membranes in treating chemically intensive anodic oxidation wastewaters. This superiority can be attributed to the PTFE membrane's morphology and structure, which are less influenced by feed water temperature and chemicals. Additionally, its slippery surface imparts anti-adhesion properties, effectively preventing membrane fouling, and maintaining the treated water quality and flux for longer operation time.

Insights into the silica scaling behaviors in membrane distillation and anti-scaling mechanism of functional polymers.

Silica scaling imposes a significant limitation on the efficacy of membrane distillation (MD) in the treatment of hypersaline wastewater. The complex dynamic behaviors of silica at the membrane-water-air interface and the poor understanding of molecular-level anti-scaling mechanism hampers the development of effective antiscalants for mitigating silica scaling in MD. Despite using functional polymers to prevent silica polymerization, the inhibition mechanisms are unclear. Here, the kinetic process of silica scaling during MD and the potential anti-scaling mechanism of poly-ethylenimine (PEI) were investigated at the molecular level via molecular dynamics simulations. The investigation reveals that silica scales were more likely to adhere to the water-PTFE interface with a free energy potential well of -40.0 kJ mol-1 than that of the water-air interface with a -11.4 kJ mol-1 potential well. Silica scales falling at the water-air interface also migrated on the water-air interface until captured by the PTFE membrane. In this work, a representative functional amino-rich polymer PEI was constructed as silica inhibitors and its scale inhibition mechanism was elucidated. Notably, the inclusion of PEI increased the free-energy barriers for the silica polymerization reaction from 72.0 kJ mol-1 to 86.1 kJ mol-1, compared to scenarios without the antiscalants. Moreover, quantitative structure-activity relationships (QSAR) model of ΔGwater-silica was developed to predict the anti-scaling efficiencies of typical antiscalants based on machine learning method. These findings provide valuable insights into enhancing the efficiency of silica scaling mitigation strategies.

Profiling of seized Cannabis sativa L. flowering tops by means of microwave-assisted hydro distillation and gas chromatography analyses.

This research aimed to support police forces in their battle against illicit drug trafficking by means of a multi-technique approach, based on gas chromatography. In detail, this study was focused on the profiling of volatile substances in narcotic Cannabis sativa L. flowering tops. For this purpose, the Scientific Investigation Department, RIS Carabinieri of Messina, provided 25 seized samples of Cannabis sativa L. The content of Δ9-tetrahydrocannabinol (THC), useful to classify cannabis plant as hemp (≤ 0.2 %) or as marijuana (> 0.2 %), was investigated. Essential oils of illicit drug samples were extracted using a microwave-assisted hydro-distillation (MAHD) system; GC-MS and GC-FID analytical techniques were used for the characterization of the terpenes and terpenoids fingerprint. Furthermore, the enantiomeric and carbon isotopic ratios of selected chiral compounds were investigated using a heart-cutting multidimensional GC (MDGC) approach. The latter exploited a combination of an apolar column in the first dimension, and a chiral cyclodextrin-based column in the second one, prior to parallel isotope-ratio mass spectrometry (C-IRMS) and MS detection. Finally, all the data were gathered into a statistical model, to demonstrate the existence of useful parameters to be used for the classification of seized samples.

Prototype-based sample-weighted distillation unified framework adapted to missing modality sentiment analysis.

Missing modality sentiment analysis is a prevalent and challenging issue in real life. Furthermore, the heterogeneity of multimodality often leads to an imbalance in optimization when attempting to optimize the same objective across all modalities in multimodal networks. Previous works have consistently overlooked the optimization imbalance of the network in cases when modalities are absent. This paper presents a Prototype-Based Sample-Weighted Distillation Unified Framework Adapted to Missing Modality Sentiment Analysis (PSWD). Specifically, it fuses features with a more efficient transformer-based cross-modal hierarchical cyclic fusion module. Subsequently, we propose two strategies, namely sample-weighted distillation and prototype regularization network, to address the issues of missing modality and optimization imbalance. The sample-weighted distillation strategy assigns higher weights to samples that are located closer to class boundaries. This facilitates the obtaining of complete knowledge by the student network from the teacher's network. The prototype regularization network calculates a balanced metric for each modality, which adaptively adjusts the gradient based on the prototype cross-entropy loss. Unlike conventional approaches, PSWD not only connects the sentiment analysis study in the missing modality to the full modality, but the proposed prototype regularization network is not reliant on the network structure and can be expanded to more multimodal studies. Massive experiments conducted on IEMOCAP and MSP-IMPROV show that our method achieves the best results compared to the latest baseline methods, which demonstrates its value for application in sentiment analysis.

Progress in membrane distillation processes for dye wastewater treatment: A review.

Textile and cosmetic industries generate large amounts of dye effluents requiring treatment before discharge. This wastewater contains high levels of reactive dyes, low to none-biodegradable materials and chemical residues. Technically, dye wastewater is characterised by high chemical and biological oxygen demand. Biological, physical and pressure-driven membrane processes have been extensively used in textile wastewater treatment plants. However, these technologies are characterised by process complexity and are often costly. Also, process efficiency is not achieved in cost-effective biochemical and physical treatment processes. Membrane distillation (MD) emerged as a promising technology harnessing challenges faced by pressure-driven membrane processes. To ensure high cost-effectiveness, the MD can be operated by solar energy or low-grade waste heat. Herein, the MD purification of dye wastewater is comprehensively and yet concisely discussed. This involved research advancement in MD processes towards removal of dyes from industrial effluents. Also, challenges faced by this process with a specific focus on fouling are reviewed. Current literature mainly tested MD setups in the laboratory scale suggesting a deep need of further optimization of membrane and module designs in near future, especially for textile wastewater treatment. There is a need to deliver customized high-porosity hydrophobic membrane design with the appropriate thickness and module configuration to reduce concentration and temperature polarization (CP and TP). Also, energy loss should be minimized while increasing dye rejection and permeate flux. Although laboratory experiments remain pivotal in optimizing the MD process for treating dye wastewater, the nature of their time intensity poses a challenge. Given the multitude of parameters involved in MD process optimization, artificial intelligence (AI) methodologies present a promising avenue for assistance. Thus, AI-driven algorithms have the potential to enhance overall process efficiency, cutting down on time, fine-tuning parameters, and driving cost reductions. However, achieving an optimal balance between efficiency enhancements and financial outlays is a complex process. Finally, this paper suggests a research direction for the development of effective synthetic and natural dye removal from industrially discharged wastewater.

Contrasting mixed scaling patterns and mechanisms of nanofiltration and membrane distillation.

Oriented towards the pressing needs for hypersaline wastewater desalination and zero liquid discharge (ZLD), the contrasting mixed scaling of thermal-driven vacuum membrane distillation (VMD) and pressure-driven nanofiltration (NF) were investigated in this work. Bulk crystallization was the main mechanism in VMD due to the high salinity and temperature, but the time-independent resistance by the adsorption of silicate and organic matter dominated the initial scaling process. Surface crystallization and the consequent pore-blocking were the main scaling mechanisms in NF, with the high permeate drag force, hydraulic pressure, and cross-flow rate resulting in the dense scaling layer mainly composed of magnesium-silica hydrate (MSH). Silicate enhanced NF scaling with a 75% higher initial flux decline rate attributed to the MSH formation and compression, but delayed bulk crystallization in VMD. Organic matter presented an anti-scaling effect by delaying bulk crystallization in both VMD and NF, but specifically promoted CaCO3 scaling in NF. Furthermore, the incipient scaling was intensified as silicate and organic matter coexisted. The scaling mechanism shifted from surface to bulk crystallization due to the membrane concentration in both VMD and NF. This work fills the research gaps on mixed scaling mechanisms in different membrane processes, which offers insights for scaling mitigation and thereby supports the application of ZLD.

Steam distillation process for flavor enhancement of milk coffee: Effects of condensation temperature on volatile compounds and flavor characteristics.

To enhance the flavor characteristics of milk coffee, steam distillation was applied to roasted ground coffee to obtain extracts that were then added to the hot water extract of the residue. The effects of different condensation temperatures for steam distillation on the volatile compounds of condensates and the flavor characteristics of the milk coffees prepared with each condensate were investigated. The volatile compounds were analyzed by gas chromatography/mass spectrometry, and principal component analysis (PCA) was performed on the mean peak areas of the volatiles that showed significant differences between the samples. The five types of milk coffees prepared with/without condensates were evaluated by consumer panelists using the check-all-that-apply question combined with the milk coffee flavor lexicon. The results showed that the concentration of volatile compounds tended to be higher in response to decreasing condensation temperature in steam distillation. The volatile compounds were grouped into four patterns based on their concentration in the condensates, which was affected by the volatility of the compounds and the duration of the condensation process in steam distillation. PCA clarified the characteristic volatile compounds that contribute to differences between the three condensates. The check-all-that-apply results indicated that the samples prepared with the condensates enhanced some specific coffee flavors, although acceptances for them were not enhanced. Implementing a steam distillation step in the milk coffee production process could lead to enhancing the coffee flavor strength of milk coffee products, and changing the condensation temperature for steam distillation was effective for providing different flavor characteristics of milk coffee. PRACTICAL APPLICATION: Changing the condensation temperature for steam distillation is effective in differentiating the flavor characteristics of milk coffee. Increasing the condensation temperature resulted in decreased concentrations of volatile compounds, which enhanced the milk and rich flavor. Decreasing the condensation temperature resulted in increased concentrations of volatile compounds, which provided a stronger coffee flavor to the milk coffee, possibly leading to a reduction in the use of coffee for milk coffee production. The check-all-that-apply question combined with the milk coffee flavor lexicon could effectively evaluate consumers' perceptions of the milk coffee flavor characteristics and their acceptances in a single survey.

Teacher-student collaborated multiple instance learning for pan-cancer PDL1 expression prediction from histopathology slides.

Programmed cell death ligand 1 (PDL1), as an important biomarker, is quantified by immunohistochemistry (IHC) with few established histopathological patterns. Deep learning aids in histopathological assessment, yet heterogeneity and lacking spatially resolved annotations challenge precise analysis. Here, we present a weakly supervised learning approach using bulk RNA sequencing for PDL1 expression prediction from hematoxylin and eosin (H&E) slides. Our method extends the multiple instance learning paradigm with the teacher-student framework, which assigns dynamic pseudo-labels for intra-slide heterogeneity and retrieves unlabeled instances using temporal ensemble model distillation. The approach, evaluated on 12,299 slides across 20 solid tumor types, achieves a weighted average area under the curve of 0.83 on fresh-frozen and 0.74 on formalin-fixed specimens for 9 tumors with PDL1 as an established biomarker. Our method predicts PDL1 expression patterns, validated by IHC on 20 slides, offering insights into histologies relevant to PDL1. This demonstrates the potential of deep learning in identifying diverse histological patterns for molecular changes from H&E images.