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        An Artificial Neural Networks Model for Predicting Permeability Properties of Nano Silica–Rice Husk Ash Ternary Blended Concrete

        Alireza Najigivi,Alireza Khaloo,Azam Iraji zad,Suraya Abdul Rashid 한국콘크리트학회 2013 International Journal of Concrete Structures and M Vol.7 No.3

        In this study, a two-layer feed-forward neural network was constructed and applied to determine a mapping associating mix design and testing factors of cement?nano silica (NS)?rice husk ash ternary blended concrete samples with their performance in conductance to the water absorption properties. To generate data for the neural network model (NNM), a total of 174 field cores from 58 different mixes at three ages were tested in the laboratory for each of percentage, velocity and coefficient of water absorption and mix volumetric properties. The significant factors (six items) that affect the permeability properties of ternary blended concrete were identified by experimental studies which were: (1) percentage of cement; (2) content of rice husk ash; (3) percentage of 15 nm of SiO₂ particles; (4) content of NS particles with average size of 80 nm; (5) effect of curing medium and (6) curing time. The mentioned significant factors were then used to define the domain of a neural network which was trained based on the Levenberg?Marquardt back propagation algorithm using Matlab software. Excellent agreement was observed between simulation and laboratory data. It is believed that the novel developed NNM with three outputs will be a useful tool in the study of the permeability properties of ternary blended concrete and its maintenance.

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        Improved charge collection efficiency of hollow sphere/nanoparticle composite TiO2 electrodes for solid state dye sensitized solar cells

        Golnaz Sadoughi,Raheleh Mohammadpour,Azam Iraji zad,Nima Taghavinia,Shabnam Dadgostar,Mahmoud Samadpour,Fariba Tajabadi 한국물리학회 2013 Current Applied Physics Vol.13 No.2

        The photoanodes of solid state dye sensitized solar cells (ss-DSCs) embedded with different contents of TiO2 hollow spheres (HSs) were prepared and the photovoltaic performances were systematically characterized. TiO2 hollow spheres were synthesized by a facile sacrificial templating method, grounded and added in different ratios to TiO2 nanoparticle (NP) paste, from which composite HS/NP electrodes were fabricated. The composite photoanodes include hollow spheres of 300e700 nm with enhanced light scattering characteristics in visible range which leads to improved light absorption in conventional thin film electrodes of ss-DSC. By optimizing the amount of HSs in the paste, 40% improvement in efficiency was obtained in comparison to ss-DSC utilized pure NP electrodes. By increasing the fraction of HSs in the electrode the current density increased by 56% (from 2.5 to 3.9 mA cm2). The improved photovoltaic performance of ss-DSC is primarily due to different morphology and altered charged trap distribution in HSs in comparison to NP which leads to significant enhancement in electron transport time and electron lifetime as well as charge collection efficiency and light absorption properties.

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