Multifractal analysis of ZnO nanoparticles

Saha, Rajat; Debanath, Mrinal K.; Saikia, Eeshankur

doi:10.1016/j.msec.2019.110177

Cited by 10 publications

(10 citation statements)

References 46 publications

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“…Figure 9(c,d) show Legendre Spectrum of the XRD of the FZnO and its BZnO samples respectively. A relatively smaller value of Δα and higher value of Δf l in case of FZnO predicts rich pattern formation 23 . Figure 9(e,f) show respective Hausdorff spectrum of the HRTEM images.…”

Section: Resultsmentioning

confidence: 95%

“…where µ(box) is the box measure and ɛ is the dimension of the box 23 . The higher the value of α, the more regular is the signal.…”

Section: Methodsmentioning

confidence: 99%

“…It is a plot between Legendre fractal dimensions f l (α) and holder exponent α, and are obtained from XRD data in our case here. The Shape of the multifractal spectrum of singularities can be well captured by the width of the spectrum Δα l which describes the range of probability and the difference of dimension Δf l , which quantifies the self-similarity in the fractals 23,24 . It is a very useful tool to describe and analyze the variations of nonlinear fractals of a system.…”

Section: Methodsmentioning

confidence: 99%

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Antibacterial and nonlinear dynamical analysis of flower and hexagon-shaped ZnO microstructures

Saha

Debanath

Paul

et al. 2020

Sci Rep

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The present study reports the antibacterial properties of flower-shaped ZnO (FZnO) microstructures and its comparison with that of hexagon-shaped bulk ZnO (BZnO) nanostructures. The samples are prepared successfully by wet chemical method and the surface morphologies, structures and size of the ZnO samples are characterized by X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), BET adsorption isotherm, and Photoluminescence (PL) Spectroscopy. The SEM and TEM images of the sample have confirmed flower-shaped structure of the ZnO. The materials are also analyzed by using an innovative tool called Lacunarity, a nonlinear dynamical (NLD) tool for proper understanding of the inherent surface properties of the particles formed, comparing the results estimated with the BET results obtained, thereby confirming our proposition to use it as an important parameter in predictive models. In this new approach, geometry of the surface structure is being associated with biological properties, in order to come up with easier ways to identify materials for any such applications where rich surface structure is desired. The photocatalytic activity of the flower-shaped material is carried out to find out its optical properties as another marker for confirming the antimicrobial activities. It has been reported for the first time that the prominent antibacterial activities are favoured by the FZnO microstructure having lesser Lacunarity, significantly better than its bulk counterpart, for inhibiting gram negative-Escherichia coli microorganism. Nanotechnology, at present, pertains to creation of useful materials, devices, and systems through appropriate manipulation of matter. A significant number of researchers have reported that formation of ZnO nanostructures in different shapes, such as, nanorod, nanoplates, nanowire 1 , flower-shaped ZnO microstructures 2 , etc. In the present work, two important attributes, capping and molarity, are used to control the particle size and their agglomeration 3. It is reported in W Yu et al. (2016), that photo-generated electrons in ZnO are much lighter than their corresponding holes, which indicates that it belongs to the n-type semiconductor 4. This result paves the way for obtaining excitation energy of electrons in ZnO that determines its optical property. ZnO materials are good inhibitors of microorganisms, and it is believed that this activity is enhanced in case of ZnO due to its high surface morphology. The capped ZnO usually shows up higher antibacterial activity than the uncapped one 5. In the present work, flower-shaped ZnO (FZnO) microstructures in PVP matrix and uncapped hexagon-shaped bulk ZnO (BZnO) nanostructures are synthesized for the study of their antimicrobial properties. The as-prepared samples are characterized by X-ray diffraction (XRD) 6 , Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) to find their size and shape 7,8. Further, the FZnO are characterized by UV-spectra, Photoluminescence (PL) Spec...

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Section: Resultsmentioning

confidence: 95%

“…where µ(box) is the box measure and ɛ is the dimension of the box 23 . The higher the value of α, the more regular is the signal.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Antibacterial and nonlinear dynamical analysis of flower and hexagon-shaped ZnO microstructures

Saha

Debanath

Paul

et al. 2020

Sci Rep

Self Cite

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“…Different applications of multifractal analysis in process engineering have been reported 26–29. Karasinski et al.…”

Section: Introductionmentioning

confidence: 99%

“…Different applications of multifractal analysis in process engineering have been reported [26][27][28][29]. Karasinski et al [27] applied multifractal analysis to binary images to quantify the degree of particle dispersion in nanocomposites.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of the Cane Sugar Crystallization Process by Multifractal Analysis of Temperature Time Series

et al. 2021

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The monitoring and diagnosis of crystallization processes are difficult due to the interaction of nucleation and crystal growth phenomena. In recent years, image and time series analysis using fractal methodologies showed potential as an alternative for monitoring crystal growth, although the available results are scarce. In this work, the multifractal detrended fluctuation analysis (MF‐DFA) was applied to temperature time series obtained from a laboratory‐scale cane sugar crystallization operated at different operating conditions. MF‐DFA reflects that the crystallization process exhibits multifractal properties associated with the dynamic behavior of the underlying phenomena. Thus, multifractal analysis can identify how operational changes influence the crystal growth and formed crystal mass.

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Detection, Prediction & Intervention of Attention Deficiency in the Brain Using tDCS

Kakoti

Syiemlieh

Saikia

2021

Machine Learning for Healthcare Applications

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Multifractal analysis of ZnO nanoparticles

Cited by 10 publications

References 46 publications

Antibacterial and nonlinear dynamical analysis of flower and hexagon-shaped ZnO microstructures

Antibacterial and nonlinear dynamical analysis of flower and hexagon-shaped ZnO microstructures

Diagnosis of the Cane Sugar Crystallization Process by Multifractal Analysis of Temperature Time Series

Detection, Prediction & Intervention of Attention Deficiency in the Brain Using tDCS

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