Abstract:
Fractal analysis has emerged as a potential analytical tool in almost all branches of science and technology. The paper is the first report of using fractal dimension as a surrogate technique for estimating particle size. A regression equation is set connecting the soot particle size and fractal dimension, after investigating the Field Emission Scanning Electron Microscopic (FESEM) images of carbonaceous soot from five different sources. Since the fractal dimension is an invariant property under the scale transformation, an ordinary photograph of the soot should also yield the same fractal dimension. This enables one to determine the average size of the soot particles, using the regression equation, by calculating the fractal dimension from the photograph. Hence, instead of frequent measurement of average particle size from FESEM, this technique of estimating the particle size from the fractal dimension of the soot photograph, is found to be a potentially cost-effective and non-contact method.
Citation:
M. S. Swapna, S. Sankararaman, “Fractal analysis – a surrogate technique for material characterization”, Nanosystems: Physics, Chemistry, Mathematics, 8:6 (2017), 809–815
\Bibitem{SwaSan17}
\by M.~S.~Swapna, S.~Sankararaman
\paper Fractal analysis -- a surrogate technique for material characterization
\jour Nanosystems: Physics, Chemistry, Mathematics
\yr 2017
\vol 8
\issue 6
\pages 809--815
\mathnet{http://mi.mathnet.ru/nano107}
\crossref{https://doi.org/10.17586/2220-8054-2017-8-6-809-815}
\isi{https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=Publons&SrcAuth=Publons_CEL&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=000419787600015}
Linking options:
https://www.mathnet.ru/eng/nano107
https://www.mathnet.ru/eng/nano/v8/i6/p809
This publication is cited in the following 10 articles:
Ammini Renjini, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, “Graph features based classification of bronchial and pleural rub sound signals: the potential of complex network unwrapped”, Phys Eng Sci Med, 2024
S. Sankararaman, “Power spectral fractalysis: a surrogate method for laser-induced plasma temperature analysis”, Eur. Phys. J. Spec. Top., 230:21-22 (2021), 3881
S Sankararaman, Ernesto Estrada, “Unveiling the potential of phase portrait-based recurrence network: a revelation through lung sound analysis”, Journal of Complex Networks, 10:1 (2021)
M. S. Swapna, S. Sreejyothi, Vimal Raj, S. Sankararaman, “Is SARS CoV-2 a Multifractal?—Unveiling the Fractality and Fractal Structure”, Braz J Phys, 51:3 (2021), 731
M S Swapna, S Sankararaman, “The efflorescent carbon allotropes: fractality preserved blooming through alkali treatment and exfoliation”, Nano Ex., 1:2 (2020), 020010
A. Renjini, Vimal Raj, M. S. Swapna, S. Sreejyothi, S. Sankararaman, “Phase portrait for high fidelity feature extraction and classification: A surrogate approach”, Chaos: An Interdisciplinary Journal of Nonlinear Science, 30:11 (2020)
M S Swapna, H V Saritha Devi, G Ambadas, S Sankararaman, “Tunable fluorescence from natural carbon source: Pandanus”, Pramana - J Phys, 92:5 (2019)
Igor Olenych, Yurii Olenych, Andriy Kostruba, Yaroslav Pryima, 2019 XIth International Scientific and Practical Conference on Electronics and Information Technologies (ELIT), 2019, 97
Vimal Raj, M. S. Swapna, S. Soumya, S. Sankararaman, “Fractal study on Saraswati supercluster”, Indian J Phys, 93:11 (2019), 1385
M. S. Swapna, V. P. N. Nampoori, S. Sankararaman, “Photoacoustics: a nondestructive evaluation technique for thermal and optical characterisation of metal mirrors”, J Opt, 47:3 (2018), 405
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