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.

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.

Essential oils (EOs) have been investigated for their effectiveness against fungal fruit pathogens. The present review article summarises the EOs that inhibit Alternaria alternata and Colletotrichum gloeosporioides in the pre- and post-harvest stages of fruits. Thirty-nine scientific papers focusing on the extraction conditions and the antifungal activity of EOs were selected. The retrieved studies came mainly from China and Brazil. Hydrodistillation has been identified as the most used extractive method. The yields and chemical profiles were variable among the species. The in vitro studies were larger than the in vivo studies. The application of EOs reduced the incidence of fungal diseases in tomatoes (Lycopersicon esculentum), papaya (Carica papaya) and mango (Mangifera indica). EOs resulted as a potential ecological alternative for treating fungal diseases in fruits requiring further investigation.

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.

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.

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.

The rise of large-scale Transformers has led to challenges regarding computational costs and energy consumption. In this context, spiking neural networks (SNNs) offer potential solutions due to their energy efficiency and processing speed. However, the inaccuracy of surrogate gradients and feature space quantization pose challenges for directly training deep SNN Transformers. To tackle these challenges, we propose a method (called LDD) to align ANN and SNN features across different abstraction levels in a Transformer network. LDD incorporates structured feature knowledge from ANNs to guide SNN training, ensuring the preservation of crucial information and addressing inaccuracies in surrogate gradients through designing layer-wise distillation losses. The proposed approach outperforms existing methods on the CIFAR10 (96.1%), CIFAR100 (82.3%), and ImageNet (80.9%) datasets, and enables training of the deepest SNN Transformer network using ImageNet.

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.

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.

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.