11. Thermal Lensing of Multi-Walled Carbon Nanotube Solutions as Heat-Transfer NanofluidsMohanachandran Nair Sindhu Swapna, RAJ VIMAL, CABRERA HUMBERTO, SANKARARAMAN SANKARANARAYANA IYER, 2021, original scientific article Abstract: This paper unwraps nanofluids’ particle dynamics with
multi-walled carbon nanotubes (MWCNTs) in base fluids such as
acetone, water, and ethylene glycol. Having confirmed the
morphology and structure of the MWCNTs by field emission
scanning electron microscopy, X-ray diffraction, and Raman
spectroscopic analyses, the nanofluids are prepared in three different concentrations. The nonzero absorbance at the laser wavelength, revealed through the UV−visible spectrum, makes the thermal diffusivity study of the sample by the sensitive nondestructive single beam thermal lens (TL) technique possible. The TL signal analysis by time series and fractal techniques divulges the complex particle dynamics, through phase portrait, sample entropy, fractal dimension, and Hurst exponent. The study unveils the effect of the amount of nanoparticles and the viscosity of the medium on thermal diffusivity and particle dynamics. The observed inverse relation between thermal diffusivity and viscosity is in good agreement with the
Sankar−Swapna model. The complexity of particle dynamics in MWCNT nanofluids reflected through sample entropy, and fractal
dimension shows an inverse relation to the base fluid’s viscosity. This paper investigates the role of viscosity of the base fluid on particle dynamics and thermal diffusivity of the nanofluid to explore its applicability in various thermal systems, thereby suggesting a method to tune the sample entropy through proper selection of base fluid.
Keywords: MWCNT, thermal lens, fractals, nonlinear time series, phase portrait, sample entropy
Published in RUNG: 28.06.2022; Views: 1376; Downloads: 0
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12. Distance-based configurational entropy of proteins from molecular dynamics simulationsFederico Fogolari, Alessandra Corazza, Sara Fortuna, Miguel Angel Soler, Bryan VanSchouwen, Giorgia Brancolini, Stefano Corni, Giuseppe Melacini, Gennaro Esposito, 2015, original scientific article Abstract: Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes.
In particular:
reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;
the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;
backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);
the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface.
This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.
Keywords: entropy, protein, molecular dynamics, simulations, MD
Published in RUNG: 12.10.2016; Views: 4253; Downloads: 221
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13. Accurate estimation of the entropy of rotation-translation probability distributionsFederico Fogolari, Cedrix Jurgal Dongmo Foumthuim, Sara Fortuna, Miguel Angel Soler, Alessandra Corazza, Gennaro Esposito, 2016, original scientific article Abstract: The estimation of rotational and translational entropies in the context of ligand binding has been the subject of long-time investigations. The high dimensionality (six) of the problem and the limited amount of sampling often prevent the required resolution to provide accurate estimates by the histogram method. Recently, the nearest-neighbor distance method has been applied to the problem, but the solutions provided either address rotation and translation separately, therefore lacking correlations, or use a heuristic approach. Here we address rotational–translational entropy estimation in the context of nearest-neighbor-based entropy estimation, solve the problem numerically, and provide an exact and an approximate method to estimate the full rotational–translational entropy.
Keywords: entropy, probability distribution, molecular dynamics, nearest-neighbor
Published in RUNG: 11.10.2016; Views: 4379; Downloads: 0
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