This study investigated the green synthesis of silver nanoparticles (Ag-NPs) and zinc oxide nanoparticles (ZnO-NPs) using an aqueous extract of stingless bee honey (SBH) as a reducing and stabilising agent. The rich compositions of SBH containing flavonoids, phenolics, organic acids, sugars, and enzymes makes the SBH extract an ideal biocompatible precursor for the NPs synthesis. Physicochemical characterisation of the synthesised NPs was performed using UV-Vis spectroscopy, FESEM, TEM, XRD, and FTIR spectroscopy. The results revealed that the Ag-NPs and ZnO-NPs exhibited polydispersity, with size ranges between 25-50 nm and 15-30 nm, respectively. A majority of the NPs possessed a spherical morphology. Furthermore, the study evaluated the antimicrobial activity of the SBH-based NPs against gram-positive (Staphylococcus aureus, ATCC 43300) and gram-negative (Escherichia coli, ATCC 25922) bacteria. The findings demonstrated significantly higher antimicrobial efficacy of the Ag-NPs with a zone of inhibition (ZOI) of 16.91 mm against S. aureus, and 17.43 mm against E. coli compared to the ZnO-NPs which having a ZOI of 13.05 mm and 14.01 mm, respectively. Notably, cytotoxicity assays revealed no adverse effects of the synthesised NPs on normal mouse fibroblast (3T3) and human lung fibroblast (MRC5) cells up to 100 μg/ml of concentration. These findings suggest the potential of SBH-based Ag-NPs and ZnO-NPs as safe and effective antibacterial agents for various applications, including pharmaceuticals, cosmetics, ointments, and lotions.
Phosphate (PO4(III)) contamination in water bodies poses significant environmental challenges, necessitating efficient and accurate methods to predict and optimize its removal. The current study addresses this issue by predicting the adsorption capacity of PO4(III) ions onto biochar-based materials using five probabilistic machine learning models: eXtreme Gradient Boosting LSS (XGBoostLSS), Natural Gradient Boosting, Bayesian Neural Networks (NN), Probabilistic NN, and Monte-Carlo Dropout NN. Utilizing a dataset of 2952 data points with 16 inputs, XGBoostLSS demonstrated the highest R2 (0.95) on new adsorbents. SHapely Additive exPlanations analysis showed that adsorption experimental conditions had the most significant impact (43%), followed by synthesis conditions (29%) and adsorbent characteristics (28%). Optimized conditions included an initial PO4(III) concentration of 125 mg/L, carbon content of 11.5%, oxygen content of 23%, a contact time of 1440 min, a heating rate of 5 °C/min, 200 rpm, and a surface area of 410 m2/g, using Ra-LDO adsorbent synthesized from rape cabbage feedstock. This study developed and presented a practical online framework for predicting PO4(III) removal onto biochar using a web-based graphical user interface.
The objective of this study was to visualize trends and current research status of hydrothermal biochar research through a bibliometric analysis by using CiteSpace software. The original article data were collected from the Web of Science core database published between 2009 and 2020. A visual analysis network of national co-authored, institutional co-authored and author co-authored articles was created, countries, institutions and authors were classified accordingly. By visualizing the cited literature and journal co-citation networks, the main subject distribution and core journals were identified respectively. By visualizing journal co-citations, the main research content was identified. Further the cluster analysis revealed the key research directions of knowledge structure. Keyword co-occurrence analysis and key occurrence analysis demonstrate current research hotspots and new research frontiers. Through the above analysis, the cooperation and contributions of hydrothermal biochar research at different levels, from researchers to institutions to countries to macro levels, were explored, the disciplinary areas of knowledge and major knowledge sources of hydrothermal biochar were discovered, and the development lineage, current status, hotspots and trends of hydrothermal biochar were clarified. The results obtained from the study can provide a reference for scholars to gain a deeper understanding of hydrothermal biochar.
Microalgae cultivation in open ponds requires a large footprint, while most photobioreactors need improvement in the ratio of surface to volume and energy consumption. In this study, polyethersulfone (PES) and poly(vinylidene fluoride) (PVDF) hollow fiber membranes with a large surface area were rearranged into open-ended and dead-ended configurations to improve the air-liquid interface cultivation of Navicula incerta. N. incerta were successfully grown on the porous membrane surface with the nutrients circulating inside the lumen. Fourier-transform infrared spectra showed the accumulation of polysaccharides, proteins and humic acids. Hydrophilic polysaccharides reduced water contact angles on PES and PVDF membranes to 37.2 ± 2.6° and 55.7 ± 3.3°, respectively. However, the porosity of PES (80.1 ± 1.1%) and PVDF (61.3 ± 4.5%) membranes were not significantly affected even after cultivation and harvesting of N. incerta. Scanning electron images further confirmed that N. incerta, cell debris and extracellular organic matter accumulated on the membrane. With large pores and a hydrophobic surface, PVDF hollow fiber membranes offered a greater improvement in N. incerta cell growth rate compared to PES hollow fiber membranes despite using different configurations. In the dead-ended configuration, they even attained the greatest improvement in N. incerta growth rate, up to 54.0%. However, PES hollow fiber membranes only achieved improvement in harvesting efficiency within the range of 18.7-38.0% due to weak cell adhesion. PVDF hollow fiber membranes significantly promoted the growth of microalgae N. incerta through the air-liquid interface system, leading to potential applications in wastewater treatment.
The excessive and unorganised utilisation of pesticides have posed negative impacts on soil and water at higher levels. Pesticides are a major class of persistent organic compounds with high resistance to natural biodegradation and enhanced tendency to bio accumulate. The severe health hazards imposed on the living organisms hinder the ecosystem and lead to chronic and irreversible health issues. Photocatalytic method is reported as a potential alternative with a variety of techniques and materials that are safer, easier, durable, cost-effective and efficient. Nanomaterials play a key role in this domain due to their versatility. In particular, nanostructured materials of organized shapes and morphological properties have gained enormous attention in research and real-time applications. Specifically, nanomaterials like nanotubes, nanorods and nanowires have unique properties and anisotropic structure that make them more suitable for treating pesticide wastes with photocatalysis. Variety of tuning methods and materials are emerging to enhance the activity of titanium and zinc based nanocatalysts in remediation methods. In the present article, four pesticides, namely, atrazine, chlorpyrifos, paraquat and naphthalene are chosen due to their common occurrence and usage in agricultural applications. These pesticides are highly toxic and need special attention to explore appropriate remediation methods. The report also details the latest innovations reported by several research studies in exploring the potential of specially synthesised nanoparticles for photocatalytic removal of pesticide pollutants from environment. For zinc-based hybrid nanomaterials, the maximum disintegration reported were 99%, 98%, 73.3% and 92.3% for atrazine, chlorpyrifos, paraquat and naphthalene, respectively.