Within this work, to promote the efficiency of organic-based solar cells, a series of novel A-π-D type small molecules were scrutinised. The acceptors which we designed had a moiety of N, N-dimethylaniline as the donor and catechol moiety as the acceptor linked through various conjugated π-linkers. We performed DFT (B3LYP) as well as TD-DFT (CAM-B3LYP) computations using 6-31G (d,p) for scrutinising the impact of various π-linkers upon optoelectronic characteristics, stability, and rate of charge transport. In comparison with the reference molecule, various π-linkers led to a smaller HOMO–LUMO energy gap. Compared to the reference molecule, there was a considerable red shift in the molecules under study (A1–A4). Therefore, based on

The performance of H2S sensor based on poly methyl methacrylate (PMMA)-CdS nanocomposite fabricated by spray pyrolysis technique has been reported. XRD pattern diffraction peaks of nano CdS has been indexed to the hexagonally wurtzite structured The nanocomposite exhibits semiconducting behavior with optical energy gap of4.06eV.SEM morphology appears almost tubes like with CdS/PMMA network. That means the addition of CdS to polymer increases the roughness in the film and provides high surface to volume ratio, which helps gas molecule to adsorb on these tubes. The resistance of PMMA-CdS nanocomposite showed a considerable change when exposed to H2S gas. Fast response time to detect H2S gas was achieved by using PMMA-CdS thin film sensor. The

Several methods have been developed for routing problem in MANETs wireless network, because it considered very important problem in this network ,we suggested proposed method based on modified radial basis function networks RBFN and Kmean++ algorithm. The modification in RBFN for routing operation in order to find the optimal path between source and destination in MANETs clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. The re

Non uniform channelization is a crucial task in cognitive radio receivers for obtaining separate channels from the digitized wideband input signal at different intervals of time. The two main requirements in the channelizer are reconfigurability and low complexity. In this paper, a reconfigurable architecture based on a combination of Improved Coefficient Decimation Method (ICDM) and Coefficient Interpolation Method (CIM) is proposed. The proposed Hybrid Coefficient Decimation-Interpolation Method (HCDIM) based filter bank (FB) is able to realize the same number of channels realized using (ICDM) but with a maximum decimation factor divided by the interpolation factor (L), which leads to less deterioration in stop band at

A perturbed linear system with property of strong observability ensures that there is a sliding mode observer to estimate the unknown form inputs together with states estimation. In the case of the electro-hydraulic system with piston position measured output, the above property is not met. In this paper, the output and its derivatives estimation were used to build a dynamic structure that satisfy the condition of strongly observable. A high order sliding mode observer (HOSMO) was used to estimate both the resulting unknown perturbation term and the output derivatives. Thereafter with one signal from the whole system (piton position), the piston position make tracking to desire one with a simple linear output feedback controller after ca

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

   The petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli