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Conducting polymers (CPs) have wide applications in various devices such as sensors, supercapacitors, energy storage devices, dye-sensitized solar cells (DSSCs) and others. Here, detailed Time-dependent Density Func-tional Theory (TDDFT) studies on a novel functionalised conducting polymer, 2-(3-nitrophenyl)-4,7-di(thiophen-2-yl)-1H-benzo[d]imidazole) (BIMN) is reported. BIMN is a D-A-D (Donor-Acceptor-Donor) type conjugated molecule. The poly-BIMN polymer provides lower oxidation potential, lower bandgap and higher optical contrast, and is found to be useful in optical devices. The performance of various GGA, hybrid, and meta-GGA functionals to calculate the optical bandgap were studied, and the the hybrid-GGA functional PBE0 was selected to perform all calculations. All calcu-lations were performed on the ORCA 5 package. TZV basis set were used for all calculations. The 450 nm peak in the the experimental UV-Visible spectrum was resonably reproduced by the TDDFT calculations. The evolution of the bandgap for one to six rings of the oligomer was studied. Reasonable chain length saturation was obtained at 4 rings, and a bandgap of 420 nm was found for the 6-ring oligomer. Despite the calculations performed in gas phase, there results are in good agreement with the reported experimental values. It is suggested that modelling 4 rings, especially of these D-A-D molecules, is sufficient for predicting the optical bandgap. [ABSTRACT FROM AUTHOR]

Reliability, efficiency, and cost-effectiveness of smart grids are enhanced with power demand softening by means of efficient load management in electric vehicles. In such initiatives, the involvement of EV users may reduce due to the lack of adaptable user-centric approaches. During the connection sessions, the EV charging time is determined using a deep learning algorithm-based smart charging strategy proposed in this paper. Here, the total energy cost of the vehicle is minimized by making charging decisions considering demand time series, pricing, environment, driving, and other auxiliary data. The memorization technique is used for the estimation of the optimal solution of the existing connection sessions in the initial stage. The deep learning models are trained with this existing data and optimal decisions to make suitable decisions in real-time scenarios where car usage or future energy price values are undetermined. A significant reduction in the charging cost is observed by training the neural network with the proposed model. The results obtained are compared to the optimal charging costs computed and are found to be closely similar. [ABSTRACT FROM AUTHOR]

A methodology is outlined for computing state-resolved transport collision integrals from potential energy surfaces (PES). This method is then applied to the O+O2 system to compute the vibrational state to state (StS) collisional transport quantities based on the Varandas and Pais PES [1] and the recent ab initio surfaces developed by Varga et al. [2]. State-based potentials that describe the interaction of an O atom with an O2 molecule at a particular vibrational level is extracted from the Varandas and Pais PES and the singlet 1 ¹ A′ surface by Varga et al., and are used to compute StS scattering profiles. Using these scattering results, StS diffusion cross-sections and the state-based Ω(1,1) collision integrals are computed for the two PESs used in this study. The cross-sections and collision integrals showed a dependence on the vibrational state of the O2 molecule. Further, differences were also observed in these transport collisional properties for the two PESs considered. [ABSTRACT FROM AUTHOR]

Sustainable or green building design and construction is a technique of rationally using resources to createhealthier, high quality and more energy efficient buildings. Green building technique is about searching forequilibrium between high quality construction and low environment impact. A lighter footprint means the structure is long lasting which is beneficial today, tomorrow and in the long run. We view green building as a goal and process, which means it, combines both materials and processes to maximize efficiencies, resilience and savings. Green building when looked from outside might look the same as conventional building, but it differs in the operational savings including concerns for human comfort, indoor environment and pleasant stay. Green building saves 40-50% energy by reducing C02 emission into the atmosphere. Grey water reuse and harvesting of rain water can save up to20-30% water. We have explored numerous themes and problems in the expanse of sustainable building construction. We collected data on different types of buildings and their importance. Based on the investigations we decided to design a museum, particularly, children's science museum as a green and sustainable building which has educational, social, environmental benefits. In the present investigation it is explored to find solutions for efficient water management, energy conservation, alternative green materials and resources and improved indoor environment quality in buildings. The project envisions preparing a layout of preliminary theme-museum building. This uses all the site details obtained. So the layout of museum is prepared by listing various spaces, their standing, area calculation, zoning and connectivity. As the future of the nation is shaped by today's children, it is highly necessary to educate them for sustainable development. Hence the concept of green and sustainable building practices will serve for the upcoming generation. [ABSTRACT FROM AUTHOR]