Fabrication of optochemical and electrochemical sensors using thin films of porphyrin and phthalocyanine derivatives

This paper describes the fabrication of thin films of porphyrin and metallophthalocyanine derivatives on different substrates for the optochemical detection of HCl gas and electrochemical determination of L-cysteine (CySH). Solid state gas sensor for HCl gas was fabricated by coating meso-substituted porphyrin derivatives on glass slide and examined optochemical sensing of HCl gas. The concentration of gaseous HCl was monitored from the changes in the absorbance of Soret band. Among the different porphyrin derivatives, meso- tetramesitylporphyrin (MTMP) coated film showed excellent sensitivity towards HCl and achieved a detection limit of 0.03ppm HCl. Further, we have studied the self-assembly of 1,8,15,22-tetraaminometallophthalocyanine (4α-MTAPc; M = Co and Ni) from DMF on GC electrode. The CVs for the self-assembled monolayers (SAMs) of 4α-CoIITAPc and 4α-NiIITAPc show two pairs of well-defined redox couple corresponding to metal and ring. Using the 4α-CoIITAPc SAM modified electrode, sensitive and selective detection of L-cysteine was demonstrated. Further, the SAM modified electrode also successfully separates the oxidation potentials of AA and CySH with a peak separation of 320mV.

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Texture enhancement is an important component of image processing that finds extensive application in science and engineering. The quality of medical images, quantified using the imaging texture, plays a significant role in the routine diagnosis performed by medical practitioners. Most image texture enhancement is performed using classical integral order differential mask operators. Recently, first order fractional differential operators were used to enhance images. Experimentation with these methods led to the conclusion that fractional differential operators not only maintain the low frequency contour features in the smooth areas of the image, but they also nonlinearly enhance edges and textures corresponding to high frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we apply the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other first order fractional differential operators, we find that our new algorithms provide higher signal to noise values and superior image quality.

A numerical method for the fractional Fitzhugh–Nagumo monodomain model

A fractional FitzHugh–Nagumo monodomain model with zero Dirichlet boundary conditions is presented, generalising the standard monodomain model that describes the propagation of the electrical potential in heterogeneous cardiac tissue. The model consists of a coupled fractional Riesz space nonlinear reaction-diffusion model and a system of ordinary differential equations, describing the ionic fluxes as a function of the membrane potential. We solve this model by decoupling the space-fractional partial differential equation and the system of ordinary differential equations at each time step. Thus, this means treating the fractional Riesz space nonlinear reaction-diffusion model as if the nonlinear source term is only locally Lipschitz. The fractional Riesz space nonlinear reaction-diffusion model is solved using an implicit numerical method with the shifted Grunwald–Letnikov approximation, and the stability and convergence are discussed in detail in the context of the local Lipschitz property. Some numerical examples are given to show the consistency of our computational approach.