Search Results (2,507)

Starch particles (SPs) were extracted from underutilized wild yam (Dioscorea remotiflora) tubers using two methods: (1) acid hydrolysis (AH) alone and (2) acid hydrolysis assisted by ultrasound (AH-US). The SPs were chemically modified through esterification (using acetic anhydride [AA] and lauroyl chloride [LC]) and crosslinking (with citric acid [CA] and sodium hexametaphosphate [SHMP]). They were subsequently characterized by their yield, amylose content, and structural and physical properties. The yield of particles was 17.5–19.7%, and the residual amylose content was 2.8–3.2%. Particle sizes ranged from 0.46 to 0.55 µm, which exhibited mono-modal and bi-modal distributions for AH and AH-US treatments, respectively. Following chemical modification, yield notably increased, especially with substitution by LC (33.6–36.5%) and CA (32.6–38.7%). Modified SPs exhibited bi-modal particle distributions with micro- and nanoparticles and variable peak intensities depending on the chemical compound used. Unmodified SPs displayed irregular morphologies, showing disruptions (AH) or aggregation (AH-US). Chemical substitutions altered morphologies, leading to amorphous surfaces (CA: AH), clustering (LC), or fragmentation into smaller particles (SHMP) under AH-US treatment. FT-IR analysis indicated a decrease in hydroxyl groups’ peak area (A(-OH)), confirming the substitution of these groups in the starch structure. Crosslinking with CA resulted in the highest degree of substitution (AH: 0.43; AH-US: 0.44) and melting enthalpy (ΔH_f: 343.0 J/g for AH-US), revealing stronger interactions between SPs from both methods. These findings demonstrate that the extraction treatment of D. remotiflora SPs and the type of chemical modifier significantly influence the properties of SPs, underscoring their potential applications as natural biocarriers. Full article

The large yellow croaker (Larimichthys crocea) is susceptible to microbial contamination during storage due to its high protein and moisture contents. This study was designed to find a new way to reduce bacteria in large yellow croakers by combining slightly acidic electrolyzed water (SAEW) with nano-bubble (NB) technology. Exploring the effects of available chlorine concentration (ACC), processing time, and water temperature on the bacteria reduction effect of the SAEW-NB treatment for large yellow croakers. Also, the effects of the SAEW-NB combined treatment on sensory evaluation, total viable counts (TVCs), total volatile basic nitrogen (TVB-N), texture, taste profile, and volatile flavor compounds of large yellow croakers were analyzed during the storage period at 4 °C. The results show that the SAEW-NB treatment achieved significantly enhanced microbial reduction compared to individual treatments. Under the conditions of a 4 °C water temperature, 40 mg/L ACC, and 15 min treatment, the SAEW-NB treatment inhibited the increases in physical and chemical indexes such as TVC and TVB-N, maintained the fish texture, and delayed the production of off-flavor volatiles such as aldehydes, alcohols, esters, and ketones, compared with the control group (CG) during storage at 4 °C. In conclusion, the SAEW-NB treatment could better retard fish spoilage, extending the shelf life by approximately 2 days. It might be a promising new industrial approach for large yellow croakers’ storage. Full article

Widespread antibiotic residues are accumulating in the environment, potentially causing adverse effects for humans, animals, and the ecosystem, including an increase in antibiotic-resistant bacteria, resulting in worldwide concern. There are various commonly used physical, chemical, and biological treatments for the degradation of antibiotics. However, the elimination of toxic end products generated by physicochemical methods and the need for industrial applications pose significant challenges. Hence, environmentally sustainable, green, and readily available approaches for the transformation and degradation of these antibiotic compounds are being sought. Herein, we review the impact of sustainable fungal laccase-based bioremediation strategies. Fungal laccase enzyme is considered one of the most active enzymes for biotransformation and biodegradation of antibiotic residue in vitro. For industrial applications, the low laccase yields in natural and genetically modified hosts may constitute a bottleneck. Methods to screen for high-laccase-producing sources, optimizing cultivation conditions, and identifying key genes and metabolites involved in extracellular laccase activity are reviewed. These include advanced transcriptomics, proteomics, and metagenomics technologies, as well as diverse laccase-immobilization technologies with different inert carrier/support materials improving enzyme performance whilst shifting from experimental assays to in situ monitoring of residual toxicity. Still, more basic and applied research on laccase-mediated bioremediation of pharmaceuticals, especially antibiotics that are recalcitrant and prevalent, is needed. Full article

Diamond, renowned for its exceptional electrical, physical, and chemical properties, including ultra-wide bandgap, superior hardness, high thermal conductivity, and unparalleled stability, serves as an ideal candidate for next-generation high-power and high-temperature electronic devices. Among diamond-based devices, Schottky barrier diodes (SBDs) have garnered significant attention due to their simple architecture and superior rectifying characteristics. This review systematically summarizes recent advances in diamond SBDs, focusing on both metal–semiconductor (MS) and metal–interlayer–semiconductor (MIS) configurations. For MS structures, we critically analyze the roles of single-layer metals (including noble metals, transition metals, and other metals) and multilayer metals in modulating Schottky barrier height (SBH) and enhancing thermal stability. However, the presence of interface-related issues such as high densities of surface states and Fermi level pinning often leads to poor control of the SBH, limiting device performance and reliability. To address these challenges and achieve high-quality metal/diamond interfaces, researchers have proposed various interface engineering strategies. In particular, the introduction of interfacial layers in MIS structures has emerged as a promising approach. For MIS architectures, functional interlayers—including high-k materials (Al₂O₃, HfO₂, SnO₂) and low-work-function materials (LaB₆, CeB₆)—are evaluated for their efficacy in interface passivation, barrier modulation, and electric field control. Terminal engineering strategies, such as field-plate designs and surface termination treatments, are also highlighted for their role in improving breakdown voltage. Furthermore, we emphasize the limitations in current parameter extraction from current–voltage (I–V) properties and call for a unified new method to accurately determine SBH. This comprehensive analysis provides critical insights into interface engineering strategies and evaluation protocols for high-performance diamond SBDs, paving the way for their reliable deployment in extreme conditions. Full article

This paper presents a comprehensive review of the environmentally friendly management and reutilization of electronic waste (e-waste) plastics in flexible pavement construction. The discussion begins with an overview of e-waste management challenges and outlines key recycling approaches for converting plastic waste into asphalt-compatible materials. This review then discusses the types of e-waste plastics used for asphalt modification, their incorporation methods, and compatibility challenges. Physical and chemical treatment techniques, including the use of free radical initiators, are then explored for improving dispersion and performance. Additionally, in situations where advanced pretreatment methods are not applicable due to cost, safety, or technical constraints, the application of alternative approaches, such as the use of low-cost complementary additives, is discussed as a practical solution to enhance compatibility and performance. Finally, the influence of e-waste plastics on the conventional and rheological properties of asphalt binders, as well as the performance of asphalt mixtures, is also evaluated. Findings indicate that e-waste plastics, when combined with appropriate pretreatment methods and complementary additives, can enhance workability, cold-weather cracking resistance, high-temperature anti-rutting performance, and resistance against moisture-induced damage while also offering environmental and economic benefits. This review highlights the potential of e-waste plastics as sustainable asphalt modifiers and provides insights across the full utilization pathway, from recovery to in-field performance. Full article

The most prevalent growth of Candida cells is based on biofilm development, which causes the intensification of antifungal resistance against a large range of chemicals. Nanoparticles can be synthesized using green methods via various biological extracts and reducing agents to control Candida biofilms. This study aims to compare copper oxide nanoparticles (CuONPs) synthesized through chemical methods and those synthesized using Cinnamomum verum-based green methods against Candida infections and their biofilms isolated from Iraqi patients, with the potential to improve treatment outcomes. The physical and chemical properties of these nanoparticles were characterized using Fourier-transform infrared spectroscopy (FT-IR,) scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM) and X-ray diffraction (XRD). Four strains of Candida were isolated and characterized from Iraqi patients in Tikrit Hospital and selected based on their ability to form biofilm on polystyrene microplates. The activity of green-synthesized CuONPs using cinnamon extract was compared with both undoped and doped (Fe, Sn) chemically synthesized CuONPs. Four pathogenic Candida strains (Candida glabrata, Candida lusitaniae, Candida albicans, and Candida tropicalis) were isolated from Iraqi patients, demonstrating high biofilm formation capabilities. Chemically and green-synthesized CuONPs from Cinnamomum verum showed comparable significant antiplanktonic and antibiofilm activities against all strains. Doped CuONPs with iron or tin demonstrated lower minimum inhibitory concentration (MIC) values, indicating stronger antibacterial activity, but exhibited weaker anti-adhesive properties compared to other nanoparticles. The antiadhesive activity revealed that C. albicans strain seems to produce the most resistant biofilms while C. glabrata strain seems to be more resistant towards the doped CuONPs. Moreover, C. tropicalis was the most sensitive to all the CuONPs. Remarkably, at a concentration of 100 µg/mL, all CuONPs were effective in eradicating preformed biofilms by 47–66%. The findings suggest that CuONPs could be effective in controlling biofilm formation by Candida species resistant to treatment in healthcare settings. Full article

Flocculants are indispensable in water and wastewater treatment, enabling the aggregation and removal of suspended particles, colloids, and emulsions. However, the conventional development and application of flocculants rely heavily on empirical methods, which are time-consuming, resource-intensive, and environmentally problematic due to issues such as sludge production and chemical residues. Recent advances in machine learning (ML) have opened transformative avenues for the design, optimization, and intelligent application of flocculants. This review systematically examines the integration of ML into flocculant research, covering algorithmic approaches, data-driven structure–property modeling, high-throughput formulation screening, and smart process control. ML models—including random forests, neural networks, and Gaussian processes—have successfully predicted flocculation performance, guided synthesis optimization, and enabled real-time dosing control. Applications extend to both synthetic and bioflocculants, with ML facilitating strain engineering, fermentation yield prediction, and polymer degradability assessments. Furthermore, the convergence of ML with IoT, digital twins, and life cycle assessment tools has accelerated the transition toward sustainable, adaptive, and low-impact treatment technologies. Despite its potential, challenges remain in data standardization, model interpretability, and real-world implementation. This review concludes by outlining strategic pathways for future research, including the development of open datasets, hybrid physics–ML frameworks, and interdisciplinary collaborations. By leveraging ML, the next generation of flocculant systems can be more effective, environmentally benign, and intelligently controlled, contributing to global water sustainability goals. Full article

In recent years, significant attention has been directed toward the development of coating materials capable of tailoring surface properties for various functional applications. Transition metal nitrides, in particular, have garnered interest due to their superior physical and chemical properties, including high hardness, excellent wear resistance, and strong corrosion resistance. In this study, a fabrication process for CrN-based thin films was developed by combining reactive direct current magnetron sputtering (dcMS) with post-deposition annealing in air. CrN coatings were deposited by reactive dcMS using different argon-nitrogen (Ar:N₂) gas ratios (4:1, 3:1, 2:1, and 1:1), followed by annealing at 550 °C for 1.5 h in ambient air. XRD and EDS analysis revealed that this treatment results in the formation of a composite phase comprising CrN and Cr₂O₃. The resulting coating exhibited favorable mechanical and tribological properties, including a maximum hardness of 12 GPa, a low wear coefficient of 0.254 and a specific wear rate of 7.05 × 10⁻⁶ mm³/N·m, making it a strong candidate for advanced protective coating applications. Full article

The discharge of oily wastewater threatens the ecosystem and human health, and the efficient treatment of oily wastewater is confronted with problems of high mass transfer resistance at the oil-water-solid multiphase interface, significant light shielding effect, and easy deactivation of photocatalysts. Although traditional physical separation methods avoid secondary pollution by chemicals and can effectively separate floating oil and dispersed oil, they are ineffective in removing emulsified oil with small particle sizes. To address these complex challenges, photocatalytic technology and photocatalysis-based improved technologies have emerged, offering significant application prospects in degrading organic pollutants in oily wastewater as an environmentally friendly oxidation technology. In this paper, the degradation mechanism, kinetic mechanism, and limitations of conventional photocatalysis technology are briefly discussed. Subsequently, the surface interface modulation functions of metal doping and heterojunction energy band engineering, along with their applications in enhancing the light absorption range and carrier separation efficiency, are reviewed. Focus on typical studies on the separation and degradation of aqueous and oily phases using photocatalytic membrane technology, and illustrate the advantages and mechanisms of photocatalysts loaded on the membranes. Finally, other new approaches and converging technologies in the field are outlined, and the challenges and prospects for the future treatment of oily wastewater are presented. Full article

This paper serves as a comprehensive and practical resource to guide researchers in selecting suitable metals for use as photocathodes in radio-frequency (RF) and superconducting radio-frequency (SRF) electron guns. It offers an in-depth review of bulk and thin-film metals commonly employed in many applications. The investigation includes the photoemission, optical, chemical, mechanical, and physical properties of metallic materials used in photocathodes, with a particular focus on key performance parameters such as quantum efficiency, operational lifetime, chemical inertness, thermal emittance, response time, dark current, and work function. In addition to these primary attributes, this study examines essential parameters such as surface roughness, morphology, injector compatibility, manufacturing techniques, and the impact of chemical environmental factors on overall performance. The aim is to provide researchers with detailed insights to make well-informed decisions on materials and device selection. The holistic approach of this work associates, in tabular format, all photo-emissive, optical, mechanical, physical, and chemical properties of bulk and thin-film metallic photocathodes with experimental data, aspiring to provide unique tools for maximizing the effectiveness of laser cleaning treatment. Full article

The contamination of drinking water sources with selenium (Se) oxyanions, including selenite (Se(IV)) and selenate (Se(VI)), contains serious health hazards with an oral intake exceeding 400 µg/day and therefore requires urgent attention. Various natural and anthropogenic sources are responsible for high Se concentrations in aquatic environments. In addition, the chemical behavior and speciation of selenium can vary noticeably depending on the origin of the source water. The Se(VI) oxyanion is more soluble and therefore more abundant in surface water. Se levels in contaminated waters often exceed 50 µg/L and may reach several hundred µg/L, well above drinking water limits set by the World Health Organization (40 µg/L) and Germany (10 µg/L), as well as typical industrial discharge limits (5–10 µg/L). Overall, Se is difficult to remove using conventionally available physical, chemical, and biological treatment technologies. The recent literature has therefore highlighted promising advancements in Se removal using emerging technologies. These include advanced physical separation methods such as membrane-based treatment systems and engineered nanomaterials for selective Se decontamination. Additionally, other integrated approaches incorporating photocatalysis coupled adsorption processes, and bio-electrochemical systems have also demonstrated high efficiency in redox transformation and capturing of Se from contaminated water bodies. These innovative strategies may offer enhanced selectivity, removal, and recovery potential for Se-containing species. Here, a current review outlines the sources, distribution, and chemical behavior of Se in natural waters, along with its toxicity and associated health risks. It also provides a broad and multi-perspective assessment of conventional as well as emerging physical, chemical, and biological approaches for Se removal and/or recovery with further prospects for integrated and sustainable strategies. Full article

The treatment processes from a wastewater treatment plant (WWTP) are known for their complexity and highly nonlinear behavior, which makes them challenging to analyze, model, and especially, to control. This research studies how machine learning (ML) with a focus on deep learning (DL) techniques can be applied to optimize the treatment processes of WWTPs, highlighting those case studies that propose ML and DL methods that directly address this issue. This research aims to study the ML and DL systematic applications in optimizing the wastewater treatment processes from an industrial plant, such as the modeling of complex physical–chemical processes, real-time monitoring and prediction of critical wastewater quality indicators, chemical reactants consumption reduction, minimization of plant energy consumption, plant effluent quality prediction, development of data-driven type models as support in the decision-making process, etc. To perform a detailed analysis, 87 articles were included from an initial set of 324, using criteria such as wastewater combined with ML, DL, and artificial intelligence (AI), for articles from 2010 or newer. From the initial set of 324 scientific articles, 300 were identified using Litmaps, obtained from five important scientific databases, all focusing on addressing the specific problem proposed for investigation. Thus, this paper identifies gaps in the current research, discusses ML and DL algorithms in the context of optimizing wastewater treatment processes, and identifies future directions for optimizing these processes through data-driven methods. As opposed to traditional models, IA models (ML, DL, hybrid and ensemble models, digital twin, IoT, etc.) demonstrated significant advantages in wastewater quality indicator prediction and forecasting, in energy consumption forecasting, in temporal pattern recognition, and in optimal interpretability for normative compliance. Integrating advanced ML and DL technologies into the various processes involved in wastewater treatment improves the plant systems’ predictive capabilities and ensures a higher level of compliance with environmental standards. Full article

This study addresses the problem of agricultural waste utilization and nutrition for older adults by developing a food product based on a circular design approach. Pineapple core was used to produce a clean-label dietary powder without chemical or enzymatic treatment, relying on repeated rinsing and hot-air drying. The development process followed a structured analysis of physical, chemical, and sensory properties. The powder contained 83.46 g/100 g dietary fiber, 0° Brix sugar, pH 4.72, low water activity (aw < 0.45), and no detectable heavy metals or microbial contamination. Sensory evaluation by expert panelists confirmed that the product was acceptable in appearance, aroma, and texture, particularly for older adults. These results demonstrate the feasibility and safety of valorizing agri-waste into functional ingredients. The process was guided by the Transformative Circular Product Blueprint, which integrates clean-label processing, IoT-enabled solar drying, and decentralized production. This model supports traceability, low energy use, and adaptation at the community scale. This study contributes to sustainable food innovation and aligns with Sustainable Development Goals (SDGs) 3 (Good Health and Well-being), 9 (Industry, Innovation and Infrastructure), and 12 (Responsible Consumption and Production). Full article

There is a lack of systematic research on the comprehensive regulatory effects of urea and organic fertilizer application on soil quality and cotton yield in summer direct-seeded cotton fields in the Yangtze River Basin. Additionally, there is a redundancy of indicators in the cotton field soil quality evaluation system and a lack of reports on constructing a minimum dataset to evaluate the soil quality status of cotton fields. We aim to accurately and efficiently evaluate soil quality in cotton fields and screen nitrogen application measures that synergistically improve soil quality, cotton yield, and nitrogen fertilizer utilization efficiency. Taking the summer live broadcast cotton field in Jiangxi Province as the research object, four treatments, including CK without nitrogen application, CF with conventional nitrogen application, N1 with nitrogen reduction, and N2 with nitrogen reduction and organic fertilizer application, were set up for three consecutive years from 2022 to 2024. A total of 15 physical, chemical, and biological indicators of the 0–20 cm plow layer soil were measured in each treatment. A minimum dataset model was constructed to evaluate and verify the soil quality status of different nitrogen application treatments and to explore the physiological mechanisms of nitrogen application on yield performance and stability from the perspectives of cotton source–sink relationship, nitrogen use efficiency, and soil quality. The minimum dataset for soil quality evaluation in cotton fields consisted of five indicators: soil bulk density, moisture content, total nitrogen, organic carbon, and carbon-to-nitrogen ratio, with a simplification rate of 66.67% for the evaluation indicators. The soil quality index calculated based on the minimum dataset (MDS) was significantly positively correlated with the soil quality index of the total dataset (TDS) (R² = 0.904, p < 0.05). The model validation parameters RMSE was 0.0733, nRMSE was 13.8561%, and the d value was 0.9529, all indicating that the model simulation effect had reached a good level or above. The order of soil quality index based on MDS and TDS for CK, CF, N1, and N2 treatments was CK < N1 < CF < N2. The soil quality index of N2 treatment under MDS significantly increased by 16.70% and 26.16% compared to CF and N1 treatments, respectively. Compared with CF treatment, N2 treatment significantly increased nitrogen fertilizer partial productivity by 27.97%, 31.06%, and 21.77%, respectively, over a three-year period while maintaining the same biomass, yield level, yield stability, and yield sustainability. Meanwhile, N1 treatment had the risk of significantly reducing both boll density and seed cotton yield. Compared with N1 treatment, N2 treatment could significantly increase the biomass of reproductive organs during the flower and boll stage by 23.62~24.75% and the boll opening stage by 12.39~15.44%, respectively, laying a material foundation for the improvement in yield and yield stability. Under CF treatment, the cotton field soil showed a high degree of soil physical property barriers, while the N2 treatment reduced soil barriers in indicators such as bulk density, soil organic carbon content, and soil carbon-to-nitrogen ratio by 0.04, 0.04, 0.08, and 0.02, respectively, compared to CF treatment. In summary, the minimum dataset (MDS) retained only 33.3% of the original indicators while maintaining high accuracy, demonstrating the model’s efficiency. After reducing nitrogen by 20%, applying 10% total nitrogen organic fertilizer could substantially improve cotton biomass, cotton yield performance, yield stability, and nitrogen partial productivity while maintaining soil quality levels. This study also assessed yield stability and sustainability, not just productivity alone. The comprehensive nitrogen fertilizer management (reducing N + organic fertilizer) under the experimental conditions has high practical applicability in the intensive agricultural system in southern China. Full article

Goosegrass (Eleusine indica) is a major weed in Brazilian soybean, corn, and cotton systems, infesting over 60% of grain-producing areas and potentially reducing yields by more than 50%. Its competitiveness is due to its rapid emergence, fast tillering, C4 metabolism, and adaptability to various environmental conditions. A critical challenge relates to its widespread resistance to multiple herbicide modes of action, notably glyphosate and acetyl-CoA carboxylate (ACCase) inhibitors. Resistance mechanisms include 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) target-site mutations, gene amplification, reduced translocation, glyphosate detoxification, and mainly ACCase target-site mutations. This literature review summarizes the current knowledge on herbicide resistance in goosegrass and its management in Brazil, with an emphasis on integrating chemical and non-chemical strategies. Mechanical and physical controls are effective in early or local infestations but must be combined with chemical methods for lasting control. Herbicides applied post-emergence of weeds, especially systemic ACCase inhibitors and glyphosate, remain important tools, although widespread resistance limits their effectiveness. Sequential applications and mixtures with contact herbicides such as glufosinate and protoporphyrinogen oxidase (PPO) inhibitors can improve control. Pre-emergence herbicides are effective when used before or immediately after planting, with adequate soil moisture being essential for their activation and effectiveness. Given the complexity of resistance mechanisms, chemical control alone is not enough. Integrated weed management programs, combining diverse herbicides, sequential treatments, and local resistance monitoring, are essential for sustainable goosegrass management. Full article