CHEMICAL SYNTHESIS,SPECTRAL CHARACTERIZATION AND STABILITY OF SOME ELECTRICALLY CONDUCTING POLYMERS

The synthesis, characterization, thermal degradation and stability of polyaniline （PANI）, poly（m-nitroaniline）, poly（m-chloroaniline） and poly（o-methylaniline） were reported. Different properties were measured and compared with PANI to find out the effect of electron donating groups （-CH3） and electron withdrawing groups （-Cl, -NO2）. It was found that the presence of any type of substitution in the benzene ring of aniline increased the solubility but reduced the yield, thermal stability and electrical conductivity. Two probe methods were used to measure the electrical conductivity of these polymers. The structural properties of these polymers were characterized by using FTIR and UV-Vis spectroscopic methods. Thermal degradation and stability of these polymers were explained by using thermogravimetric analysis （TGA） and conductivity measurements.

Quantum photodetachment of hydrogen negative ion in a harmonic potential subjected to static electric field

Photodetachment of negative ions has attracted immense interest owing to its fundamental nature and practical implications with regard to technology. In this study, we explore the quantum dynamics of the photodetachment cross section of negative ion of hydrogen H-in the perturbed one dimensional linear harmonic potential via static electric field. To this end,the quantum formula for total photodetachment cross section of the H-ion is derived by calculating the dipole matrix element in spherical coordinates. In order to obtain the detached electron wave function, we have solved the time-independent Schr¨odinger wave equation for the perturbed Hamiltonian of the harmonic oscillator in momentum representation. To acquire the corresponding normalized final state detached electron wave function in momentum space, we have employed an approach analogous to the WKB(Wenzel–Kramers–Brillouin) approximation. The resulting analytical formula of total photodetachment cross section depicts interesting oscillator structure that varies considerably with incident-photon energy,oscillator potential frequency, and electric field strength as elucidated by the numerical results. The current problem having close analogy with the Stark effect in charged harmonic oscillator may have potential implications in atomic and molecular physics and quantum optics.

Semiquantitative determination of some nitrogen compounds by the formation of charge-transfer complexes of diphenylamine with p-dimethylaminobenzaldehyde by capillary solid-state spot-tests

The interactions of p-dimethylaminobenzaldehyde(p-DAB) and potassium hydrogen sulphate(PHS) in equimolar ratio with various concentration of diphenylamine(solid test material) have been investigated by capillary spot-tests technique in order to investigate the effect of temperature and volume of material in test-tube.The formation of the colored boundary in the capillary is taken for the detection of organic compounds by spot-tests at different temperature and volume of solid test material.

Development of deep neural network model to predict the compressive strength of FRCM confined columns

The present study describes a reliability analysis of the strength model for predicting concrete columns confinement influence with Fabric-Reinforced Cementitious Matrix(FRCM).through both physical models and Deep Neural Network model(artificial neural network(ANN)with double and triple hidden layers).The database of 330 samples collected for the training model contains many important parameters,i.e.,section type(circle or square),corner radius rc,unconfined concrete strength fco,thickness nt,the elastic modulus of fiber Ef,the elastic modulus of mortar Em.The results revealed that the proposed ANN models well predicted the compressive strength of FRCM with high prediction accuracy.The ANN model with double hidden layers(APDL-1)was shown to be the best to predict the compressive strength of FRCM confined columns compared with the ACI design code and five physical models.Furthermore,the results also reveal that the unconfined compressive strength of concrete,type of fiber mesh for FRCM,type of section,and the corner radius ratio,are the most significant input variables in the efficiency of FRCM confinement prediction.The performance of the proposed ANN models(including double and triple hidden layers)had high precision with R higher than 0.93 and RMSE smaller than 0.13,as compared with other models from the literature available.