A review on biogenic green synthesis of ZnO nanoparticles by plant biomass and their applications

 Materials Today, 33, 2022, 104747

Nanobiotechnology has recently gained prominence as a fundamental branch of modern science and a novel epoch in the field of material researches. Due to a wide range of applications it attracts attention of many scientists from all over the world. Bionanomaterials are prepared using a variety of physical, chemical, and biological techniques and methods. Many different metal and metal oxide nanoparticles are reported to be produced by biological systems, including bacteria, fungi, actinomycetes, yeasts, viruses, and plants. Among all of them, biocompatible zinc oxide nanoparticles (ZnO NPs), obtained through biosynthesis with the aid of plant-derived materials, appears to be a highly successful way to create a fast, clean, non-toxic, and environmentally friendly platform for the production and application of these bionanomaterials. This review focuses on the plant extract-derived ZnO NPs synthesis, with a special emphasis on the recent advances and applications of these nanomaterials.

Green Synthesis of Silver Nanoparticles Using Allium cepa var. Aggregatum Natural Extract: Antibacterial and Cytotoxic Properties

 Nanomaterials 2022, 12(10), 1725

The chemical content of plant excerpts can be efficiently employed to reduce the metal ions to nanoparticles in the one-pot green production method. Here, green production of silver nanoparticles (AC-AgNPs) is performed by means of Allium cepa var. Aggregatum (shallot) extract as a stabilizer and reducer. The shape, size, and morphology of resultant AC-AgNPs are examined by optical spectroscopy analysis such as UV for nucleation and coalescence processes of the AC-AgNPs. Through FTIR functional group is determined and through DLS size is defined, it was confirmed that metallic AgNPs were successfully synthesized through the green synthesis route, and these results agreed well with the results obtained in the XRD pattern along with TEM spectroscopy, where the TEM images confirm the formation of sphere-like nanostructures along with SAED analysis. The chemical characterization is performed with XPS; the obtained molecular species in the materials are determined from the energy profile. Antioxidant activity of AC-AgNPs versus DPPH substrate is carried out. Antibacterial activity is well established against Gram-negative and Gram-positive organisms. Cell viability is accomplished, followed by an MTT assay, and a cytotoxicity assay of AC-AgNPs on MCF—7 cell lines is also carried out. Highlights: (1). This study highlights the eco-friendly synthesis of silver nanoparticles from Allium cepa var. Aggregatum Natural Extract. (2). The synthesized AC-AgNPs were characterized by UV-VIS, FT-IR, XRD, TEM, and XPS. (3). The synthesized nanoparticles were well dispersed in nature and the size range of 35 ± 8 nm. (4). The anti-candidal activity of biosynthesized silver nanoparticles was evaluated against the following Gram-Negative organisms: Escherichia coli (E. coli), and the following Gram-positive organisms: Staphylococcus aureus strains. The biosynthesized AC-AgNPs showed enhanced antiseptic features anti both Gram-positive and negative organisms. (5). Besides, the in vitro cytotoxic outcomes of AC-AgNPs were assessed versus MCF-7 cancerous cells, and the reduction in the feasibility of cancer cells was established via MTT assay, which suggests potential biomedical applications.

Modelling and Optimization of Biogenic Synthesis of Gold Nanoparticles from Leaf Extract of Swertia chirata Using Artificial Neural Network

Journal of Cluster Science (2018) 29:1151–1159

DOI: 10.1007/s10876-018-1429-8

Swertia chirata is a medicinal plant studied for its ability to synthesize polyshaped gold nanoparticles (AuNP). The process of AuNP biosynthesis was studied using artificial neural networks (ANN) with different activation function on output node (logistic or linear) and different training algorithm (back propagation or Levenberg–Marquardt). The maximum biosyn- thesis was checked under the optimized condition of 17.24% leaf extract, pH 4.61, gold chloride concentration 4 mM and temperature 53.61 °C. A significant improvement in the model efficiency for predicting AuNP biosynthesis around 37.60%, in terms of root mean square error was obtained with the developed ANN-linear2 model, compared to the traditional response surface methodology.