Theoretical investigation of structures and electronic states of a series of phenyl-capped oligothiophenes

The structures and electronic states of a series of phenyl-capped oligothiophenes (PnTs) and their ionic species were investigated by means of the density functional theory (DFT). The calculations were performed on the oligomers formed by n repeating units, where n ranges from 2 to 6, using the B3LYP/6-31G** level of theory. The results obtained show that the end-substitution plays a fine-tuning effect on the geometries, electronics, and excitation states. It was found that the oligomers in the doped state have more satisfactory structural and electronic characteristics for the conducting polymers. The conjugated system in the doped oligomers has more aromaticity, with expanded and planar chains. The calculated energy gap values between the frontal molecular orbitals for the PnTs indicate that with increasing the oligomer chain length, the conductive band gap decreases. The calculated ?rst excitation energies of the PnTs at the TD-B3LYP/6-31G** level reveal that the doped PnTs have lower excitation energies than the neutral states. The oligomer chains with a phenyl ring as the end-capped group display red shifts in their absorption spectra. The end-caped substituted oligothiophenes display better characteristics than the unsubstituted ones. It could be anticipated that the phenyl-caped substitution would be helpful to charge-carrier hopings between chains, and thereby, enhance the conductivity.     

Design a robust sliding mode controller based on the state and parameter estimation for the nonlinear epidemiological model of Covid-19

In this research, the challenging problem of Covid-19 mitigation is looked at from an engineering point of view. At first, the behavior of coronavirus in the Iranian and Russian societies is expressed by a set of ordinary differential equations. In the proposed model, the control input signals are vaccination, social distance and facial masks, and medical treatment. The unknown parameters of the system are estimated by long short-term memory (LSTM) algorithm. In the LSTM algorithm, the problem of long-term dependency is prevented. The uncertainty and measurement noises are inherent characteristics of epidemiological models. For this reason, an extended Kalman filter (EKF) is developed to estimate the state variables of the proposed model. In continuation, a robust sliding mode controller is designed to control the spread of coronavirus under vaccination, social distance and facial masks, and medical treatment. The stability of the closed-loop system is guaranteed by the Lyapunov theorems. The official confirmed data provided by the Iranian and Russian ministries of health are employed to simulate the proposed algorithms. It is understood from simulation results that global vaccination has the potential to create herd immunity in long term. Under the proposed controller, daily Covid-19 infections and deaths become less than 500 and 10 people, respectively.

     

Determination of the structure factor for the rare gas fluids based on the ORPA theory and LIR equation of state

Linear isotherm regularity is applied to generate an expression for the direct correlation function (DCF), based on the optimized random-phase approximation theory. We use the Lennard-Jones potential in the modelling of real fluids, in which its molecular parameters are state-dependent. Based on the perturbation theory, we assume that the core contribution of the DCF is related to the geometric effect via a linear form, which arises from the excluded volume, and the tail contribution is related to the long-range intermolecular interactions of the system via a non-linear form. We use this model to predict the behaviour of the structure factor, S(k), in a wide range of k values for the xenon and krypton liquids. Finally, we compare our results with the experimental and theoretical data available in literature. The model is also successful in the presentation of the Ornstein–Zernike behaviour of S(k) at the low-k region.