91. Development of Zinc Oxide-Multi-Walled Carbon Nanotube hybrid nanofluid for energy-efficient heat transfer application: A thermal lens studyMohanachandran Nair Sindhu Swapna, 2021, original scientific article Abstract: This paper addresses the need for developing an energy-efficient hybrid nanofluid with zinc oxide–multi-walled carbon nanotube (ZnO-MWCNT) for overcoming the bottleneck of efficient heat transfer in thermal systems. The concentration-dependent thermal diffusivity modifications are analyzed using the highly sensitive mode mismatched thermal lens technique. The hybrid composite is prepared by the solid-state mixing and annealing of a pure multi-walled carbon nanotube (MWCNT) and zinc oxide (ZnO), synthesized by the solution combustion method. The composite formation is studied by structural, morphological, and optical characterization techniques. Among the three nanofluids ZnO, MWCNT, and ZnO-MWCNT, the composite exhibits a drastic enhancement in thermal diffusivity at a lower solid volume fraction of 0.047 mg/ml containing 0.009 mg/ml of MWCNT. All the nanofluids show an optimum concentration beyond which the thermal diffusivity decreases with the nanoparticle concentration. Thus, this study suggests the potential application of ZnO-MWCNT hybrid nanofluids in thermal system design to enhance internal combustion engines' efficiency during cold-start.
Keywords: Zinc Oxide, MWCNT, hybrid nanofluid, thermal lens, diffusivity, engine efficiency
Published in RUNG: 30.06.2022; Views: 1750; Downloads: 0
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92. Graph based feature extraction and classification of wet and dry cough signals: A machine learning approachMohanachandran Nair Sindhu Swapna, 2021, original scientific article Abstract: This article proposes a unique approach to bring out the potential of graph-based features to reveal the
hidden signatures of wet (WE) and dry (DE) cough signals, which are the suggestive symptoms of various
respiratory ailments like COVID 19. The spectral and complex network analyses of 115 cough signals are
employed for perceiving the airflow dynamics through the infected respiratory tract while coughing. The
different phases of WE and DE are observed from their time-domain signals, indicating the operation of the
glottis. The wavelet analysis of WE shows a frequency spread due to the turbulence in the respiratory tract.
The complex network features namely degree centrality, eigenvector centrality, transitivity, graph density
and graph entropy not only distinguish WE and DE but also reveal the associated airflow dynamics. A better
distinguishability between WE and DE is obtained through the supervised machine learning techniques
(MLTs)—quadratic support vector machine and neural net pattern recognition (NN), when compared to
the unsupervised MLT, principal component analysis. The 93.90% classification accuracy with a precision
of 97.00% suggests NN as a better classifier using complex network features. The study opens up the
possibility of complex network analysis in remote auscultation.
Keywords: wet cough, dry cough, complex network, quadratic SVM, neural net
Published in RUNG: 30.06.2022; Views: 1354; Downloads: 0
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93. RF sputtered boron carbide thin film for UVB and UVC shielding: A greener approachMohanachandran Nair Sindhu Swapna, 2022, original scientific article Abstract: The paper reports the development of RF sputtered boron carbide coatings as refractory and UV-shielder for high-temperature goggles and spacecraft applications. The advancement in the design and fabrication of machinery and UV optics necessitates the development of low-cost, eco-friendly preparation of wear-resistant refractory coatings with strong absorption in the UV region.
Boron carbide coatings have proven their potential as abrasives besides their electronic applications. In the present work, boron carbide coatings are prepared by RF sputtering technique using the target prepared by low-temperature hydrothermal synthesis using cotton as carbon precursor. The sample synthesized and the film prepared are subjected to structure, morphological, and optical characterizations. The X-ray diffraction, Fourier transform infrared,
micro-Raman and X-ray photoelectron studies confirm the formation of boron-rich boron carbide with the thermal stability of 87% at 800 C, revealed through the thermogravimetric analysis. The Tauc plot analysis gives the bandgap energy of the boron carbide target and film as 2.66 eV and 2.70 eV, respectively. The UV–Vis spectroscopic study also reveals the potential of the sample and the
film in blocking UVB and UVC. The CIE plot from the photoluminescence study suggests the sample to be a blue light emitter.
Keywords: Boron carbide, RF sputtering, uv shielding, thin films
Published in RUNG: 30.06.2022; Views: 1437; Downloads: 0
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94. Fractal and time-series analyses based rhonchi and bronchial auscultation: A machine learning approachMohanachandran Nair Sindhu Swapna, 2022, original scientific article Abstract: Objectives: The present work reports the study of 34 rhonchi (RB) and
Bronchial Breath (BB) signals employing machine learning techniques, timefrequency, fractal, and non-linear time-series analyses. Methods: The timefrequency analyses and the complexity in the dynamics of airflow in BB
and RB are studied using both Power Spectral Density (PSD) features and
non-linear measures. For accurate prediction of these signals, PSD and nonlinear measures are fed as input attributes to various machine learning
models. Findings: The spectral analyses reveal fewer, low-intensity frequency
components along with its overtones in the intermittent and rapidly damping
RB signal. The complexity in the dynamics of airflow in BB and RB is investigated
through the fractal dimension, Hurst exponent, phase portrait, maximal
Lyapunov exponent, and sample entropy values. The greater value of entropy
for the RB signal provides an insight into the internal morphology of the airways
containing mucous and other obstructions. The Principal Component Analysis
(PCA) employs PSD features, and Linear Discriminant Analysis (LDA) along
with Pattern Recognition Neural Network (PRNN) uses non-linear measures
for predicting BB and RB. Signal classification based on phase portrait
features evaluates the multidimensional aspects of signal intensities, whereas
that based on PSD features considers mere signal intensities. The principal
components in PCA cover about 86.5% of the overall variance of the data class,
successfully distinguishing BB and RB signals. LDA and PRNN that use nonlinear time-series parameters identify and predict RB and BB signals with 100%
accuracy, sensitivity, specificity, and precision. Novelty: The study divulges the
potential of non-linear measures and PSD features in classifying these signals
enabling its application to be extended for low-cost, non-invasive COVID-19
detection and real-time health monitoring.
Keywords: lung signal, fractal analysis, sample entropy, nonlinear timeseries, machine learning techniques
Published in RUNG: 30.06.2022; Views: 1633; Downloads: 0
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95. Fractal and inertia moment analyses for thin film quality monitoringMohanachandran Nair Sindhu Swapna, 2022, original scientific article Abstract: The widespread applications of thin films in optronics demand innovative techniques for its characterizations. The work reported here proposes electronic speckle pattern interferometry and fractal-based methods for assessing the quality of thin films taking the industrially relevant molybdenum oxide (MoO3) incorporated niobium oxide (Nb2O5) films. The films with different levels of MoO3 incorporation (1, 2, 3, 5, and 10 wt. %) are prepared by radio frequency sputtering. The study reveals the structure modifications of Nb2O5 from the orthorhombic to monoclinic phases with an associated morphological variation revealed through atomic force microscopy and field-emission scanning electron microscopy analyses. The films’ specklegrams are recorded under thermal stress; the inertia moment (IM) and fractal analyses are computed and compared with the root-mean-square surface roughness of the films. The lacunarity analysis of the AFM films agrees well with the specklegrams. Thus, the lower IM and lacunarity values of the specklegrams can be regarded as indicators of the good quality of thin films.
Keywords: cross-correlation, fractal dimension, inertia moment, lacunarity, speckle, surface roughness.
Published in RUNG: 30.06.2022; Views: 1520; Downloads: 0
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96. Fluorescent emission from a natural carbon matrix incorporating sodiumMohanachandran Nair Sindhu Swapna, 2019, original scientific article Abstract: The process of functionalization of metals in natural carbon matrices has become an important area of research due to its improved properties and applications. Carbon materials possessing photoluminescence (PL) properties find a wide range of applications in photonics. Among the various carbon materials available in nature, cellulose has critical importance since it is the most abundant and wide-spread biopolymer on Earth, and also, the important component in plants’ skeleton. In the present work, the functionalized carbonaceous material is prepared by the hydrothermal treatment of natural cellulosic source Aloe Vera and the metallic element sodium is properly incorporated into it by adding sodium borohydride to observe the fluorescence emission changes. The incorporation of metal ions in the carbon matrix leads to structural modifications and properties as evidenced by field emission scanning electron microscopy, Energy dispersive spectroscopy, X-ray dot mapping, X-ray Photoelectron spectroscopy, and X-ray diffraction analysis. The optical emission characteristics are studied using Photoluminescence spectroscopy, CIE plot, power spectrum, color purity, and quantum yield. The excitation wavelength dependent photoluminescence emission mechanism shown by the carbon–metal incorporated products obtained from the cellulosic raw materials makes them suitable for biomedical and biosensing applications because of the non-toxic and eco-friendly nature.
Keywords: Fluorescent emission, sodium carbide, cellulose, carbon matrix
Published in RUNG: 30.06.2022; Views: 1453; Downloads: 0
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97. Pharmacological application of thermal Lens technique - A thermal diffusivity studyMohanachandran Nair Sindhu Swapna, 2018, original scientific article Abstract: The photothermal phenomenon has emerged as a potential tool for the nondestructive evaluation of thermal and optical properties of materials. Thermal analysis of drugs is an unavoidable part of preformulation study, as temperature variations can induce structural changes of the constituents of drugs. Techniques based on photothermal phenomena are highly sensitive, as only the absorbed radiation contributes to the signal. Periodic illumination and subsequent nonradiative de-excitation generate thermal lens signals of various types within and around the sample. Variation of thermal diffusivity with a concentration of the commonly used drug terbutaline is studied through the single-beam thermal lens technique. The ultraviolet–visible spectrum of the drug shows strong absorption around 500 nm, which suggests the possible wavelengths that can be used for the study. It is found that concentration of the drug in liquid form decides its thermal stability, as its thermal diffusivity varies with concentration. The study gives information about the optimum value for the concentration of the drug noted above for which the chance of thermal stability is high.
Keywords: thermal lens, thermal diffusivity, pharmacology, drug
Published in RUNG: 30.06.2022; Views: 1339; Downloads: 0
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98. Fractal and spectroscopic analysis of soot from internal combustion enginesMohanachandran Nair Sindhu Swapna, SARITHA DEVI H V, RAJ VIMAL, Sankararaman S, 2018, original scientific article Abstract: Today diesel engines are used worldwide for various applications and very importantly in transportation. Hydrocarbons are the most widespread precursors among carbon sources employed in the production of carbon nanotubes (CNTs). The aging of internal combustion engine is an important parameter in deciding the carbon emission and particulate matter due to incomplete combustion of fuel. In the present work, an attempt has been made for the effective utilization of the aged engines for potential applicationapplications in fuel cells and nanoelectronics. To analyze the impact of aging, the particulate matter rich in carbon content areis collected from diesel engines of different ages. The soot with CNTs is purified by the liquid phase oxidation method and analyzed by Field Emission Scanning Electron Microscopy, High-Resolution Transmission Electron Microscopy, Energy Dispersive Spectroscopy, UV-Visible spectroscopy, Raman spectroscopy and Thermogravimetric analysis. The SEM image contains self-similar patterns probing fractal analysis. The fractal dimensions of the samples are determined by the box counting method. We could find a greater amount of single-walled carbon nanotubes (SWCNTs) in the particulate matter emitted by aged diesel engines and thereby giving information about the combustion efficiency of the engine. The SWCNT rich sample finds a wide range of applications in nanoelectronics and thereby pointing a potential use of these aged engines.
Keywords: Fractals, internal combustion engine, efficiency, soot, carbon nanoparticle
Published in RUNG: 30.06.2022; Views: 1564; Downloads: 0
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99. From futile to fruitful: Diesel soot as white light emitterMohanachandran Nair Sindhu Swapna, Sankararaman S, 2018, original scientific article Abstract: The present work describes a solution for the effective use of the hazardous particulate matter (diesel soot) from the internal combustion engines (ICEs) as a potential material emitting white light for white light emitting diodes (WLEDs). The washed soot samples are subjected to Field Emission Scanning Electron Microscopy (FESEM), High- Resolution Transmission Electron Microscopy (HR-TEM), Energy Dispersive Spectroscopy (EDS), UV-Visible, Photoluminescent (PL) Spectroscopy and quantum yield measurements. The CIE plot and Correlated Color Temperature (CCT) reveals the white fluorescence on photoexcitation. The sample on ultraviolet (UV) laser excitation, provides a visual confirmation of white light emission from the sample. The diesel soot collected from public transport buses of different years of manufacture invariably exhibit white fluorescence at an excitation of 350 nm. The sample show a quantum yield of 47.09%. The study is significant in the context of pollution and search for low-cost, rare-earth phosphor free material for white light emission and thereby turning the hazardous, futile material into a fruitful material that can be used for potential applications in photonics and electronics.
Keywords: White light emitter, Diesel soot, CIE plot, Quantum yield, Fluorescence
Published in RUNG: 30.06.2022; Views: 1452; Downloads: 0
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100. Blue light emitting diesel soot for photonic applicationsMohanachandran Nair Sindhu Swapna, Sankararaman S, 2018, original scientific article Abstract: The present work is the first report of producing blue light emission from phosphor free and low-cost material—the diesel soot from the internal combustion engines (ICEs). The structural morphology is analyzed by field emission scanning electron microscopy and high-resolution transmission electron microscopy. The optical characterization is done by recording UV–visible spectrum and photoluminescent Spectrum. The CIE plot and the power spectrum for the sample show blue emission. This is further verified by collecting diesel soot from the ICE of different year of make. A visual confirmation of blue emission is obtained by exciting the sample with UV laser. The presence of various allotropic forms of carbon in the sample is identified by x-ray diffraction, Fourier transform infrared and Raman spectroscopic analysis.
Keywords: blue light emitter, diesel soot, photoluminescence, CIE plot
Published in RUNG: 30.06.2022; Views: 1366; Downloads: 0
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