Charge transfer complex states in diketopyrrolopyrrole polymers and fullerene blends: Implications for organic solar cell efficiency

The spectral photocurrent characteristics of two donor-acceptor diketopyrrolopyrrole (DPP)-based copolymers (PDPP-BBT and TDPP-BBT) blended with a fullerene derivative [6,6]-phenyl C-61-butyric acid methyl ester (PCBM) were studied using Fourier-transform photocurrent spectroscopy (FTPS) and monochromatic photocurrent (PC) method. PDPP-BBT: PCBM shows the onset of the lowest charge transfer complex (CTC) state at 1.42 eV, whereas TDPP-BBT: PCBM shows no evidence of the formation of a midgap CTC state. The FTPS and PC spectra of P3HT:PCBM are also compared. The larger singlet state energy difference of TDPP-BBT and PCBM compared to PDPP-BBT/P3HT and PCBM obliterates the formation of a midgap CTC state resulting in an enhanced photovoltaic efficiency over PDPP-BBT: PCBM. (C) 2011 American Institute of Physics. [doi:10.1063/1.3670043]

Tuning the Efficiency of Dendritic Nanocarriers using Conformational Constraints

A series of deoxycholic and cholic acid-derived oligomers were synthesized and their ability to extract hydrophilic dye molecules of different structure, size, and functional groups into nonpolar media was studied. The structure of the dye and dendritic effect in the extraction process was examined using absorption spectroscopy and dynamic light scattering (DLS). The efficiency of structurally preorganized oligomers in the aggregation process was evaluated by 1-anilinonaphthalene-8-sulfonic acid (ANS) fluorescence studies. The possible formation of globular structures for higher-generation molecules was investigated by molecular modeling studies and the results were correlated with the anomaly observed in the extraction process with this molecule. The ability of these molecules for selective extraction of specific dyes from blended colors is also reported.

Saccharomyces cerevisiae NineTeen Complex (NTC)-associated Factor Bud31/Ycr063w Assembles on Precatalytic Spliceosomes and Improves First and Second Step Pre-mRNA Splicing Efficiency

Pre-mRNA splicing occurs in spliceosomes whose assembly and activation are critical for splice site selection and catalysis. The highly conserved NineTeen complex protein complex stabilizes various snRNA and protein interactions early in the spliceosome assembly pathway. Among several NineTeen complex-associated proteins is the nonessential protein Bud31/Ycr063w, which is also a component of the Cef1p subcomplex. A role for Bud31 in pre-mRNA splicing is implicated by virtue of its association with splicing factors, but its specific functions and spliceosome interactions are uncharacterized. Here, using in vitro splicing assays with extracts from a strain lacking Bud31, we illustrate its role in efficient progression to the first catalytic step and its requirement for the second catalytic step in reactions at higher temperatures. Immunoprecipitation of functional epitope-tagged Bud31 from in vitro reactions showed that its earliest association is with precatalytic B complex and that the interaction continues in catalytically active complexes with stably bound U2, U5, and U6 small nuclear ribonucleoproteins. In complementary experiments, wherein precatalytic spliceosomes are selected from splicing reactions, we detect the occurrence of Bud31. Cross-linking of proteins to pre-mRNAs with a site-specific 4-thio uridine residue at the -3 position of exon 1 was tested in reactions with WT and bud31 null extracts. The data suggest an altered interaction between a similar to 25-kDa protein and this exonic residue of pre-mRNAs in the arrested bud31 null spliceosomes. These results demonstrate the early spliceosomal association of Bud31 and provide plausible functions for this factor in stabilizing protein interactions with the pre-mRNA.

Efficiency enhancement in DSSC using metal nanoparticles: A size dependent study

The photoelectrode of Eosin-Y sensitised DSSC was modified by incorporating Au-nanoparticles to enhance the power conversion efficiency via scattering from surface plasmon polaritons. Size dependence of Au nanoparticle on conversion efficiency was performed in DSSC for the first time by varying the particle size from 20 to 94 nm. It was found that, the conversion efficiency is highly dependent on the size of the Au nanoparticles. For larger particles (>50 nm), the efficiency was found to be increased due to constructive interference between the transmitted and scattered waves from the Au nanoparticle while for smaller particles, the efficiency decreases due to destructive interference. Also a reduction in the V-oc was observed in general, due to the negative shifting of the TiO2 Fermi level on the adsorption of Au nanoparticle. This shift was negligible for larger particles. When 94 nm size particles were employed the conversion efficiency was doubled from 0.74% to 1.52%. This study points towards the application of the scattering effect of metal nanoparticle to enhance the conversion efficiency in DSSCs. (C) 2011 Elsevier Ltd. All rights reserved.

Novel algorithm for online voltage stability assessment based on feed forward neural network

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

Enhanced efficiency of tri-layered dye solar cells with hydrothermally synthesized titania nanotubes as light scattering outer layer

In the present study dye sensitized solar cells (DSSCs) have been fabricated with a tri-layer photo anode consisting of hydrothermally prepared titania nano tubes (TNT) having a diameter of 9-10 nm and length of several micrometers as outer layer, P25 TiO2 powder as transparent light absorbing middle layer and a compact TiO2 inner layer to improve the adhesion of different layers on a transparent conducting oxide coated substrate. In comparison to cells fabricated using TNTs or P25 alone, the tri-layer DSSCs exhibit an enhanced efficiency of 7.15% with a current density of 17.12 mA cm(-2) under AM 1.5 illumination. The enhancement is attributed to the light scattering generated by TNTs aggregates, reduction in electron transport resistance at the TiO2/dye/electrolyte interface and an improvement in electron life-time. (c) 2012 Elsevier B.V. All rights reserved.

Loading of single-walled carbon nanotubes in cationic cholesterol suspensions significantly improves gene transfection efficiency in serum

We present here a series of cholesterol based cationic lipid suspensions that solubilize single-walled carbon nanotubes (SWCNT) efficiently in water. Each cationic lipid formulation was characterized in terms of their energy minimized molecular structures, bilayer widths of the aggregates based on X-ray diffraction. Then these aggregates were investigated pertaining to their DNA binding and release efficiency, effect of CNT inclusion on the stability of cationic cholesterol lipid-DNA complexes, Zeta potential values and changes in the chiro-optical property of DNA, effect on Raman spectral shift and changes in morphology by SEM and AFM. Each cationic lipid formulation was optimized for the amount of SWCNT solubilized in water, lipid-DNA ratio, amount of the plasmid DNA that can be transfected and the effect on the cellular toxicity. The resulting SWCNT-lipid formulations were then used for in vitro transfection of pEGFP-C3 in A549 (human alveolar basal epithelial) cells and HeLa (human cervical cancer) cells. Advantageously, the CNT-loaded formulations confer an excellent transfection efficiency even in high percentages of blood serum and showed significantly better gene transfer efficiency compared to one of the potent, well-known commercial transfection reagent, Lipofectamine2000.

Improvements in Efficiency of Surface Potential Computation for Independent DG MOSFET

A robust numerical solution of the input voltage equations (IVEs) for the independent-double-gate metal-oxide-semiconductor field-effect transistor requires root bracketing methods (RBMs) instead of the commonly used Newton-Raphson (NR) technique due to the presence of nonremovable discontinuity and singularity. In this brief, we do an exhaustive study of the different RBMs available in the literature and propose a single derivative-free RBM that could be applied to both trigonometric and hyperbolic IVEs and offers faster convergence than the earlier proposed hybrid NR-Ridders algorithm. We also propose some adjustments to the solution space for the trigonometric IVE that leads to a further reduction of the computation time. The improvement of computational efficiency is demonstrated to be about 60% for trigonometric IVE and about 15% for hyperbolic IVE, by implementing the proposed algorithm in a commercial circuit simulator through the Verilog-A interface and simulating a variety of circuit blocks such as ring oscillator, ripple adder, and twisted ring counter.

Mesh Simplification Based on Edge Collapsing Could Improve Computational Efficiency in Near Infrared Optical Tomographic Imaging

The diffusion equation-based modeling of near infrared light propagation in tissue is achieved by using finite-element mesh for imaging real-tissue types, such as breast and brain. The finite-element mesh size (number of nodes) dictates the parameter space in the optical tomographic imaging. Most commonly used finite-element meshing algorithms do not provide the flexibility of distinct nodal spacing in different regions of imaging domain to take the sensitivity of the problem into consideration. This study aims to present a computationally efficient mesh simplification method that can be used as a preprocessing step to iterative image reconstruction, where the finite-element mesh is simplified by using an edge collapsing algorithm to reduce the parameter space at regions where the sensitivity of the problem is relatively low. It is shown, using simulations and experimental phantom data for simple meshes/domains, that a significant reduction in parameter space could be achieved without compromising on the reconstructed image quality. The maximum errors observed by using the simplified meshes were less than 0.27% in the forward problem and 5% for inverse problem.

Quantum heat engines: A thermodynamic analysis of power and efficiency

We show that the operation and the output power of a quantum heat engine that converts incoherent thermal energy into coherent cavity photons can be optimized by manipulating quantum coherences. The gain or loss in the efficiency at maximum power depends on the details of the output power optimization. Quantum effects tend to enhance the output power and the efficiency as the photon occupation in the cavity is decreased.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Influence of tool rotation speed and feed rate on the forming limit of friction stir welded AA6061-T6 sheets

In this study, the influence of tool rotation speed and feed rate on the forming limit of friction stir welded Al 6061-T651 sheets has been investigated. The forming limit curve was evaluated by limit dome height test performed on all the friction stir welded sheets. The welding trials were conducted at a tool rotation speed of 1300 and 1400 r/min and feed rate of 90 and 100 mm/min. A third trial of welding was performed at a rotational speed of 1500 r/min and feed rate 120 mm/min. It is found that with increase in the tool rotation speed, from 1300 to 1400 r/min, for a constant feed rate, the forming limit of friction stir welded blank has improved and with increase in feed rate, from 90 to 100 mm/min, for a constant tool rotation speed, it has decreased. The forming limit of friction stir welded sheets is better than unwelded sheets. The thickness gradient after forming is severe in the cases of friction stir welded blanks made at higher feed rate and lower rotation speed. The strain hardening exponent of weld (n) increases with increase in tool rotation speed and it decreases with increase in feed rate. It has been demonstrated that the change in the forming limit of friction stir welded sheets with respect to welding parameters is due to the thickness distribution severity and strain hardening exponent of the weld region during forming. There is not much variation in the dome height among the friction stir welded sheets tested. When compared with unwelded sheets, dome height of friction stir welded sheets is higher in near-plane-strain condition, but it is lesser in stretching strain paths.

Dependence of electron recombination time and light to electricity conversion efficiency on shape of the nanocrystal light sensitizer

Tunability of electron recombination time and light to electricity conversion efficiency to superior values in semiconductor sensitized solar cells via optimized design of nanocrystal light sensitizer shape is discussed here.