Multifractal analysis of ZnO nanoparticles

ZnO nanoparticles (NPs) have variety of applications in different fields due to its size, structure, as well as physical and chemical properties. One of its prominent characteristics is its antibacterial behavior. Nonlinear Dynamical Theory (NLD) has a vast scope in the field of material science, especially when subtle correlations are searched for to extract hidden information. Since nano-ZnO materials may be used in inhibiting pathogens, its nonlinear features can be quantified and calibrated with the help of NLD tools. Multi-fractal Analysis (MFA) is an important diagnostic tool of NLD for not only analyzing nonlinear signal or images, but also predicting any spurious events likely to occur in the system under study. Thus, the analysis of the surface texture of the ZnO nano particles formed, using the TEM images and relate it with the variations of the XRD signal using NLD tools, is our first attempt reported here. Further, tools of MFA are used, for the first time, to see if there exists any correlation between the texture of the nano particles formed and the Zone of Inhibition (Zol) we obtain as an output after allowing certain pathogens inhibit in the presence of the same nano particles. Analysis of TEM images guide us to predict the texture and structure of crystallites of ZnO:Cu samples which are responsible for overall behavior of inhibiting pathogens. In this paper, MFA of Zol images, TEM images, and signal of four different Cu-doped ZnO nanoparticles are carried out and their outcomes are calibrated for estimating the size and pattern of unknown NPs synthesized under similar physical and chemical condition. Moreover, that MFA can be used reliably to predict spurious or abnormal surface structure or bacterial inhibition is also established.