C
C. Santhosh
Researcher at Manipal University
Publications - 102
Citations - 1899
C. Santhosh is an academic researcher from Manipal University. The author has contributed to research in topics: Laser-induced breakdown spectroscopy & Laser. The author has an hindex of 19, co-authored 102 publications receiving 1507 citations. Previous affiliations of C. Santhosh include Banaras Hindu University & Cochin University of Science and Technology.
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Measurements of plasma temperature and electron density in laser-induced copper plasma by time-resolved spectroscopy of neutral atom and ion emissions
TL;DR: In this paper, a 355 nm pulsed Nd:YAG laser with a pulse duration of 6 ns focussed onto a copper solid sample in air at atmospheric pressure is studied spectroscopically, and the temperature and electron density characterizing the plasma are measured by time-resolved spectroscopy of neutral atom and ion line emissions in the time window of 300-2000 ns.
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Analytical predictive capabilities of Laser Induced Breakdown Spectroscopy (LIBS) with Principal Component Analysis (PCA) for plastic classification
TL;DR: In this article, a Laser Induced Breakdown Spectroscopy (LIBS) technique has been applied for the identification of four widely used plastics, polyethylene terephthalate (PET), high-density polyethylenes (PE), polypropylene (PP) and polystyrene (PS), whose recycling is required from commercial and biosafety points of view.
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Structural analysis of cation–π interactions in DNA binding proteins
TL;DR: The structural analysis of cation-pi interaction forming residues shows that Lys, Trp, and Tyr prefer to be in the binding site of protein-DNA complexes, and the accessible surface areas of cationside interaction forming cationic residues are significantly less than that of other residues.
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Magnetically separable core–shell ZnFe2O4@ZnO nanoparticles for visible light photodegradation of methyl orange
TL;DR: In this paper, magnetic separability, surface area of 41m2/g and visible light absorption make ZnFe2O4@ZnO nanoparticles a good solar photocatalyst.
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Principal component analysis and artificial neural network analysis of oral tissue fluorescence spectra: classification of normal premalignant and malignant pathological conditions.
G. S. Nayak,Sudha D. Kamath,Keerthilatha M. Pai,Arindam Sarkar,Satadru Ray,Jacob Kurien,Lawrence D'Almeida,B. R. Krishnanand,C. Santhosh,V. B. Kartha,Krishna Kishore Mahato +10 more
TL;DR: The spectral analysis and classification for discrimination among normal, premalignant, and malignant conditions were performed using principal component analysis (PCA) and artificial neural network (ANN) separately on the same set of spectral data.