Three-Dimensional Nanoarchitecture of BiFeO3 Anchored TiO2 Nanotube Arrays for Electrochemical Energy Storage and Solar Energy Conversion

Here, we report the synthesis of TiO2/BiFeO3 nano-heterostnicture (NH) arrays by anchoring BiFeO3 (BFO) particles on on TiO2 nanotube surface and investigate their pseudocapacitive and photoelectrochemical properties considering their applications in green energy fields. The unique TiO2/BFO NHs have been demonstrated both as energy conversion and storage materials. The capacitive behavior of the NHs has been found to be significantly higher than that of the pristine TiO2 NTs, which is mainly due to the anchoring of redox active BFO nanoparticles. A specific capacitance of about 440 F g(-1) has been achieved for this NHs at a current density of 1.1 A g(-1) with similar to 80% capacity retention at a current density of 2.5 A g(-1). The NHs also exhibit high energy and power performance (energy density of 46.5 Wh kg(-1) and power density of 1.2 kW kg(-1) at a current density of 2.5 A g(-1)) with moderate cycling stability (92% capacity retention after 1200 cycles). Photoelectrochemical investigation reveals that the photocurrent density of the NHs is almost 480% higher than the corresponding dark current and it shows significantly improved photoswitching performance as compared to pure TiO2 nanotubes, which has been demonstrated based the interfacial type-II band alignment between TiO2 and BFO.

Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning

Despite significant advances in recent years, structure-from-motion (SfM) pipelines suffer from two important drawbacks. Apart from requiring significant computational power to solve the large-scale computations involved, such pipelines sometimes fail to correctly reconstruct when the accumulated error in incremental reconstruction is large or when the number of 3D to 2D correspondences are insufficient. In this paper we present a novel approach to mitigate the above-mentioned drawbacks. Using an image match graph based on matching features we partition the image data set into smaller sets or components which are reconstructed independently. Following such reconstructions we utilise the available epipolar relationships that connect images across components to correctly align the individual reconstructions in a global frame of reference. This results in both a significant speed up of at least one order of magnitude and also mitigates the problems of reconstruction failures with a marginal loss in accuracy. The effectiveness of our approach is demonstrated on some large-scale real world data sets.

Tailoring energy absorption capacity of CNT forests through application of electric field

This study examines the effect of electric field on energy absorption capacity of carbon nanotube forests (CNTFs), comprising of vertically aligned multiwalled carbon nanotubes, under both quasistatic (strain rate, (epsilon) over dot = 10(-3) s(-1)) and dynamic ((epsilon) over dot = similar to 10(3) s(-1)) loading conditions. Under quasistatic condition, the CNTFs were cyclically loaded and unloaded while electric field was applied along the length of carbon nanotube (CNT) either throughout the loading cycle or explicitly during either the loading or the unloading segment. The energy absorbed per cycle by CNTF increased monotonically with electric field when the field was applied only during the loading segment: A 7 fold increase in the energy absorption capacity was registered at an electric field of 1 kV/m whereas no significant change in it was noted for other schemes of electro-mechanical loading. The energy absorption capacity of CNTF under dynamic loading condition also increased monotonically with electric field; however, relative to the quasistatic condition, less pronounced effect was observed. This intriguing strain rate dependent effect of electric field on energy absorption capacity of CNTF is explained in terms of electric field induced strengthening of CNTF, originating from the time dependent electric field induced polarization of CNT. (C) 2015 Elsevier Ltd. All rights reserved.

Strain-Induced Hierarchy of Energy Levels in CdS/ZnS Nanocrystals

Aside of size and shape, the strain induced by the mismatch of lattice parameters between core and shell in the nanocrystalline regime is an additional degree of freedom to engineer the electron energy levels. Herein, CdS/ZnS core/shell nanocrystals (NCs) with shell thickness up to four monolayers are studied. As a manifestation of strain, the low temperature radiative lifetime measurements indicate a reduction in Stokes shift from 36 meV for CdS to 5 meV for CdS/ZnS with four monolayers of overcoating. Concomitant crossover of S- and P-symmetric hole levels is observed which can be understood in the framework of theoretical calculations predicting flipping the hierarchy of ground hole state by the strain in CdS NCs. Furthermore, a nonmonotonic variation of higher energy levels in strained CdS NCs is discussed.

Effect of Surface Energy Anisotropy on the Stability of Growth Fronts in Multiphase Alloys

Eutectic growth offers a variety of examples for pattern formation which are interesting both for theoreticians as well as experimentalists. One such example of patterns is ternary eutectic colonies which arise as a result of instabilities during growth of two solid phases. Here, in addition to the two major components being exchanged between the solid phases during eutectic growth, there is an impurity component which is rejected by both solid phases. During progress of solidification, there develops a boundary layer of the third impurity component ahead of the solidification front of the two solid phases. Similar to Mullins-Sekerka type instabilities, such a boundary layer tends to make the global solidification envelope unstable to morphological perturbations giving rise to two-phase cells. This phenomenon has been studied numerically in two dimensions for the conditions of directional solidification, by Plapp and Karma (Phys Rev E 66:061608, 2002) using phase-field simulations. While, in the work by Plapp and Karma (Phys Rev E 66:061608, 2002) all interfaces are isotropic, in our presentation, we extend the phase-field model by considering interfacial anisotropy in the solid-solid and solid-liquid interfaces and characterize the role of interfacial anisotropy on the stability of the growth front through phase-field simulations in two dimensions.

Graph Modification Problems: A Modern Perspective

We give an overview of recent results and techniques in parameterized algorithms for graph modification problems.

Estimation of activation energy for electroporation and pore growth rate in liquid crystalline and gel phases of lipid bilayers using molecular dynamics simulations

Molecular dynamics simulations of electroporation in POPC and DPPC lipid bilayers have been carried out at different temperatures ranging from 230 K to 350 K for varying electric fields. The dynamics of pore formation, including threshold field, pore initiation time, pore growth rate, and pore closure rate after the field is switched off, was studied in both the gel and liquid crystalline (L-alpha) phases of the bilayers. Using an Arrhenius model of pore initiation kinetics, the activation energy for pore opening was estimated to be 25.6 kJ mol(-1) and 32.6 kJ mol(-1) in the L-alpha phase of POPC and DPPC lipids respectively at a field strength of 0.32 V nm(-1). The activation energy decreases to 24.2 kJ mol(-1) and 23.7 kJ mol(-1) respectively at a higher field strength of 1.1 V nm(-1). At temperatures below the melting point, the activation energy in the gel phase of POPC and DPPC increases to 28.8 kJ mol(-1) and 34.4 kJ mol(-1) respectively at the same field of 1.1 V nm(-1). The pore closing time was found to be higher in the gel than in the L-alpha phase. The pore growth rate increases linearly with temperature and quadratically with field, consistent with viscosity limited growth models.

Query Click and Text Similarity Graph for Query Suggestions

Query suggestion is an important feature of the search engine with the explosive and diverse growth of web contents. Different kind of suggestions like query, image, movies, music and book etc. are used every day. Various types of data sources are used for the suggestions. If we model the data into various kinds of graphs then we can build a general method for any suggestions. In this paper, we have proposed a general method for query suggestion by combining two graphs: (1) query click graph which captures the relationship between queries frequently clicked on common URLs and (2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users' need. Simulation results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It can be used for recommendation tasks like query, image, and product suggestion.

Kinematics and dynamics of Jansen leg mechanism: A bond graph approach

The Jansen mechanism is a one degree-of-freedom, planar, 12-link, leg mechanism that can be used in mobile robotic applications and in gait analysis. This paper presents the kinematics and dynamics of the Jansen leg mechanism. The forward kinematics, accomplished using circle intersection method, determines the trajectories of various points on the mechanism in the chassis (stationary link) reference frame. From the foot point trajectory, the step length is shown to vary linearly while step height varies non-linearly with change in crank radius. A dynamic model for the Jansen leg mechanism is proposed using bond graph approach with modulated multiport transformers. For given ground reaction force pattern and crank angular speed, this model helps determine the motor torque profile as well as the link and joint stresses. The model can therefore be used to rate the actuator torque and in design of the hardware and controller for such a system. The kinematics of the mechanism can also be obtained from this dynamic model. The proposed model is thus a useful tool for analysis and design of systems based on the Jansen leg mechanism. (C) 2015 Elsevier B.V. All rights reserved.

Relationship between entropy and diffusion: A statistical mechanical derivation of Rosenfeld expression for a rugged energy landscape

Diffusion-a measure of dynamics, and entropy-a measure of disorder in the system are found to be intimately correlated in many systems, and the correlation is often strongly non-linear. We explore the origin of this complex dependence by studying diffusion of a point Brownian particle on a model potential energy surface characterized by ruggedness. If we assume that the ruggedness has a Gaussian distribution, then for this model, one can obtain the excess entropy exactly for any dimension. By using the expression for the mean first passage time, we present a statistical mechanical derivation of the well-known and well-tested scaling relation proposed by Rosenfeld between diffusion and excess entropy. In anticipation that Rosenfeld diffusion-entropy scaling (RDES) relation may continue to be valid in higher dimensions (where the mean first passage time approach is not available), we carry out an effective medium approximation (EMA) based analysis of the effective transition rate and hence of the effective diffusion coefficient. We show that the EMA expression can be used to derive the RDES scaling relation for any dimension higher than unity. However, RDES is shown to break down in the presence of spatial correlation among the energy landscape values. (C) 2015 AIP Publishing LLC.

Hydrogen energy future with formic acid: a renewable chemical hydrogen storage system

Formic acid, the simplest carboxylic acid, is found in nature or can be easily synthesized in the laboratory (major by-product of some second generation biorefinery processes); it is also an important chemical due to its myriad applications in pharmaceuticals and industry. In recent years, formic acid has been used as an important fuel either without reformation (in direct formic acid fuel cells, DFAFCs) or with reformation (as a potential chemical hydrogen storage material). Owing to the better efficiency of DFAFCs compared to several other PEMFCs and reversible hydrogen storage systems, formic acid could serve as one of the better fuels for portable devices, vehicles and other energy-related applications in the future. This perspective is focused on recent developments in the use of formic acid as a reversible source for hydrogen storage. Recent developments in this direction will likely give access to a variety of low-cost and highly efficient rechargeable hydrogen fuel cells within the next few years by the use of suitable homogeneous metal complex/heterogeneous metal nanoparticle-based catalysts under ambient reaction conditions. The production of formic acid from atmospheric CO2 (a greenhouse gas) will decrease the CO2 content and may be helpful in reducing global warming.

Error exponent analysis of energy-based Bayesian decentralized spectrum sensing under fading

This paper considers decentralized spectrum sensing, i.e., detection of occupancy of the primary users' spectrum by a set of Cognitive Radio (CR) nodes, under a Bayesian set-up. The nodes use energy detection to make their individual decisions, which are combined at a Fusion Center (FC) using the K-out-of-N fusion rule. The channel from the primary transmitter to the CR nodes is assumed to undergo fading, while that from the nodes to the FC is assumed to be error-free. In this scenario, a novel concept termed as the Error Exponent with a Confidence Level (EECL) is introduced to evaluate and compare the performance of different detection schemes. Expressions for the EECL under general fading conditions are derived. As a special case, it is shown that the conventional error exponent both at individual sensors, and at the FC is zero. Further, closed-form lower bounds on the EECL are derived under Rayleigh fading and lognormal shadowing. As an example application, it answers the question of whether to use pilot-signal based narrowband sensing, where the signal undergoes Rayleigh fading, or to sense over the entire bandwidth of a wideband signal, where the signal undergoes lognormal shadowing. Theoretical results are validated using Monte Carlo simulations. (C) 2015 Elsevier B.V. All rights reserved.

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Graph algorithms have been shown to possess enough parallelism to keep several computing resources busy-even hundreds of cores on a GPU. Unfortunately, tuning their implementation for efficient execution on a particular hardware configuration of heterogeneous systems consisting of multicore CPUs and GPUs is challenging, time consuming, and error prone. To address these issues, we propose a domain-specific language (DSL), Falcon, for implementing graph algorithms that (i) abstracts the hardware, (ii) provides constructs to write explicitly parallel programs at a higher level, and (iii) can work with general algorithms that may change the graph structure (morph algorithms). We illustrate the usage of our DSL to implement local computation algorithms (that do not change the graph structure) and morph algorithms such as Delaunay mesh refinement, survey propagation, and dynamic SSSP on GPU and multicore CPUs. Using a set of benchmark graphs, we illustrate that the generated code performs close to the state-of-the-art hand-tuned implementations.