Bayesian Modeling Coherenced Green Synthesis of NiO Nanoparticles Using Camellia sinensis for Efficient Antimicrobial Activity

Among various nanoparticles reported, nickel has been notable for its antimicrobial and photocatalytic exercises. However, to reduce the toxicity of the direct use of nickel, Camellia sinensis (tea) plant extract has been used in this work for the synthesis of nickel oxide nanoparticles (NiO NPs). The synthesis of NiO NPs has been confirmed by the UV absorption peak at 346 nm and photoluminescence peak at 341 nm. TEM images confirm the formation of NiO NPs with an average particle size of 2 nm. SEM pictures are indicating the formation of well-defined nanosheet-like NiO NPs. Statistical tools could be used to reinforce the confidence that the materials have been characterized correctly. Here, the bivariate Gaussian model has been applied to interrelate among absorbance and intensity with the wavelength, which was obtained in UV-Vis and photoluminescence spectra, respectively. A more generalized Bayesian estimate along with 95% highest probability density interval of the maximum absorption or emission wavelength observed at the highest absorbance or intensity has been calculated and investigated by using the observed values through Markov chain Monte Carlo simulations. Further, NiO NPs show efficient antimicrobial activity against both gram-negative and gram-positive bacteria strain . The synthesized NiO NPs using tea leaf extract could provide a green pathway against bacterial pathogens.