Predicting of the refractive index of haemoglobin using the Hybrid GA-SVR approach.

The optical properties of blood play crucial roles in medical diagnostics and treatment, and in the design of new medical devices. Haemoglobin is a vital constituent of the blood whose optical properties affect all of the optical properties of human blood. The refractive index of haemoglobin has been reported to strongly depend on its concentration which is a function of the physiology of biological cells. This makes the refractive index of haemoglobin an essential non-invasive bio-marker of diseases. Unfortunately, the complexity of blood tissue makes it challenging to experimentally measure the refractive index of haemoglobin. While a few studies have reported on the refractive index of haemoglobin, there is no solid consensus with the data obtained due to different measuring instruments and the conditions of the experiments. Moreover, obtaining the refractive index via an experimental approach is quite laborious. In this work, an accurate, fast and relatively convenient strategy to estimate the refractive index of haemoglobin is reported. Thus, the GA-SVR model is presented for the prediction of the refractive index of haemoglobin using wavelength, temperature, and the concentration of haemoglobin as descriptors. The model developed is characterised by an excellent accuracy and very low error estimates. The correlation coefficients obtained in these studies are 99.94% and 99.91% for the training and testing results, respectively. In addition, the result shows an almost perfect match with the experimental data and also demonstrates significant improvement over a recent mathematical model available in the literature. The GA-SVR model predictions also give insights into the influence of concentration, wavelength, and temperature on the RI measurement values. The model outcome can be used not only to accurately estimate the refractive index of haemoglobin but also could provide a reliable common ground to benchmark the experimental refractive index results.

Fabrication of Water Jet Resistant and Thermally Stable Superhydrophobic Surfaces by Spray Coating of Candle Soot Dispersion.

A facile synthesis method for highly stable carbon nanoparticle (CNP) dispersion in acetone by incomplete combustion of paraffin candle flame is presented. The synthesized CNP dispersion is the mixture of graphitic and amorphous carbon nanoparticles of the size range of 20-50 nm and manifested the mesoporosity with an average pore size of 7 nm and a BET surface area of 366 m2g-1. As an application of this material, the carbon nanoparticle dispersion was spray coated (spray-based coating) on a glass surface to fabricate superhydrophobic (water contact angle > 150° and sliding angle < 10 °) surfaces. The spray coated surfaces were found to exhibit much improved water jet resistance and thermal stability up to 400 °C compared to the surfaces fabricated from direct candle flame soot deposition (candle-based coating). This study proved that water jet resistant and thermally stable superhydrophobic surfaces can be easily fabricated by simple spray coating of CNP dispersion gathered from incomplete combustion of paraffin candle flame and this technique can be used for different applications with the potential for the large scale fabrication.