Morphology and electrochemical performance of graphene nanosheet array for Li-ion thin film battery

Highly branched and porous graphene nanosheet synthesized over different substrates as anode for Lithium ion thin film battery. These films synthesized by microwave plasma enhanced chemical vapor deposition at temperature 700 degrees C. Scanning electron microscopy and X-ray photo electron spectroscopy are used to characterize the film surface. It is found that the graphene sheets possess a curled and flower like morphology. Electrochemical performances were evaluated in swezelock type cells versus metallic lithium. A reversible capacity of 520 mAh/g, 450 mAh/g and 637 mAh/g was obtained after 50 cycles when current rate at 23 mu A cm(2) for CuGNS, NiGNS and PtGNS electrodes, respectively. Electrochemical properties of thin film anode were measured at different current rate and gave better cycle life and rate capability. These results indicate that the prepared high quality graphene sheets possess excellent electrochemical performances for lithium storage. (C) 2013 Elsevier Ltd. All rights reserved.

Numerical and experimental investigation and optimization of an open wheeled race car cooling air duct

In this study the cooling performance due to air flow and aerodynamics of the Formula Student open wheeled race car has been investigated and optimized with the help of CFD simulations and experimental validation. The race car in context previously suffered from overheating problems. Flow analysis was carried out based on the detailed race car 3D model (NITK Racing 2012 formula student race car). Wind tunnel experiments were carried out on the same. The results obtained from the computer simulations are compared with experimental results obtained from wind tunnel testing of the full car. Through this study it was possible to locate the problem areas and hence choose the best configuration for the cooling duct. The CFD analysis helped in calculating the mass flow rate, pressure and velocity distribution for different velocities of the car which is then used to determine the heat dissipated by the radiator. Area of flow separation could be visualized and made sure smooth airflow into the radiator core area. This significantly increased the cooling performance of the car with reduction in drag.

Optimization of rheological properties of photopolymerizable alumina suspensions for ceramic microstereolithography

Microstereolithography (MSL) is a rapid prototyping technique to fabricate complex three-dimensional (3D) structure in the microdomain involving different materials such as polymers and ceramics. The present effort is to fabricate microdimensional ceramics by the MSL system from a non-aqueous colloidal slurry of alumina. This slurry predominantly consists of two phases i.e. sub-micrometer solid alumina particles and non-aqueous reactive difunctional and trifunctional acrylates with inert diluent. The first part of the work involves the study of the stability and viscosity of the slurry using different concentrations of trioctyl phosphine oxide (TOPO) as a dispersant. Based on the optimization, the highest achievable solid loadings of alumina has been determined for this particular colloidal suspension. The second part of the study highlights the fabrication of several micro-dimensional alumina structures by the MSL system. (C) 2013 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

Optimum steering input determination and path-tracking of all-wheel steer vehicles on uneven terrains based on constrained optimization

In this paper we propose a framework for optimum steering input determination of all-wheel steer vehicles (AWSV) on rough terrains. The framework computes the steering input which minimizes the tracking error for a given trajectory. Unlike previous methodologies of computing steering inputs of car-like vehicles, the proposed methodology depends explicitly on the vehicle dynamics and can be extended to vehicle having arbitrary number of steering inputs. A fully generic framework has been used to derive the vehicle dynamics and a non-linear programming based constrained optimization approach has been used to compute the steering input considering the instantaneous vehicle dynamics, no-slip and contact constraints of the vehicle. All Wheel steer Vehicles have a special parallel steering ability where the instantaneous centre of rotation (ICR) is at infinity. The proposed framework automatically enables the vehicle to choose between parallel steer and normal operation depending on the error with respect to the desired trajectory. The efficacy of the proposed framework is proved by extensive uneven terrain simulations, for trajectories with continuous or discontinuous velocity profile.

Modified roaming optimization for multi-modal optima

This paper explains the algorithm of Modified Roaming Optimization (MRO) for capturing the multiple optima for multimodal functions. There are some similarities between the Roaming Optimization (RO) and MRO algorithms, but the MRO algorithm is created to overcome the problems facing while applying the RO to the problems possessing large number of solutions. The MRO mainly uses the concept of density to overcome the challenges posed by RO. The algorithm is tested with standard test functions and also discussions are made to improve the efficacy of the MRO algorithm. This paper also gives the results of MRO applied for solving Inverse Kinematics (IK) problem for SCARA and PUMA robots.

Improved photovoltaic performance of CdSe/CdS/PbS quantum dot sensitized ZnO nanorod array solar cell

Single crystalline zinc oxide (ZnO) nanorod array has been used for the fabrication of CdSe/CdS/PbS/ZnO quantum dot sensitized solar cell (QDSSC). The ZnO nanorod array photoanodes are sensitized with consecutive layer of PbS, CdS and CdSe quantum dots by employing simple successive ion layer adsorption and reaction (SILAR) and chemical bath deposition (CBD) techniques. The performances of the QDSSCs are examined in detail using polysulfide electrolyte with copper sulfide (CuS) counter electrode. The combination of two successive layers of PbS with CdSe/CdS/ZnO shows an improved short circuit current density (12.223 mA cm(-2)) with a maximum power to conversion efficiency of 2.352% under 1 sun illumination. This enhancement is mainly attributed due to the better light harvesting ability of the PbS quantum dots and make large accumulation of photo-injected electrons in the conduction band of ZnO, and CdSe/CdS layers lower the recombination of photo-injected electrons with the electrolyte, these are well evidenced with the photovoltaic studies and electrochemical impedance spectroscopy. (C) 2013 Elsevier B.V. All rights reserved.

REDUCING COMPUTATIONAL EFFORT IN SOLVING GEOMECHANICS PROBLEMS WITH UPPER BOUND FINITE ELEMENTS LIMIT ANALYSIS AND LINEAR OPTIMIZATION

This paper presents a simple technique for reducing the computational effort while solving any geotechnical stability problem by using the upper bound finite element limit analysis and linear optimization. In the proposed method, the problem domain is discretized into a number of different regions in which a particular order (number of sides) of the polygon is chosen to linearize the Mohr-Coulomb yield criterion. A greater order of the polygon needs to be selected only in that region wherein the rate of the plastic strains becomes higher. The computational effort required to solve the problem with this implementation reduces considerably. By using the proposed method, the bearing capacity has been computed for smooth and rough strip footings and the results are found to be quite satisfactory.

Automatic Data Allocation and Buffer Management for Multi-GPU Machines

Multi-GPU machines are being increasingly used in high-performance computing. Each GPU in such a machine has its own memory and does not share the address space either with the host CPU or other GPUs. Hence, applications utilizing multiple GPUs have to manually allocate and manage data on each GPU. Existing works that propose to automate data allocations for GPUs have limitations and inefficiencies in terms of allocation sizes, exploiting reuse, transfer costs, and scalability. We propose a scalable and fully automatic data allocation and buffer management scheme for affine loop nests on multi-GPU machines. We call it the Bounding-Box-based Memory Manager (BBMM). BBMM can perform at runtime, during standard set operations like union, intersection, and difference, finding subset and superset relations on hyperrectangular regions of array data (bounding boxes). It uses these operations along with some compiler assistance to identify, allocate, and manage data required by applications in terms of disjoint bounding boxes. This allows it to (1) allocate exactly or nearly as much data as is required by computations running on each GPU, (2) efficiently track buffer allocations and hence maximize data reuse across tiles and minimize data transfer overhead, and (3) and as a result, maximize utilization of the combined memory on multi-GPU machines. BBMM can work with any choice of parallelizing transformations, computation placement, and scheduling schemes, whether static or dynamic. Experiments run on a four-GPU machine with various scientific programs showed that BBMM reduces data allocations on each GPU by up to 75% compared to current allocation schemes, yields performance of at least 88% of manually written code, and allows excellent weak scaling.

Phase and Dimensionality of Tin Oxide at graphene nanosheet array and its Electrochemical performance as anode for Lithium Ion Battery

We incorporated tin oxide nanostructures into the graphene nanosheet matrix and observed that the phase of tin oxide varies with the morphology. The highest discharge capacity and coulumbic efficiency were obtained for SnO phase of nanoplates morphology. Platelet morphology of tin oxide shows more reversible capacity than the nanoparticle (SnO2 phase) tin oxide. The first discharge capacity obtained for SnO@GNS is 1393 and 950 mAh/g for SnO2@GNS electrode at a current density of 23 mu A/cm(2). A stable capacity of about 1022 and 715 mAh/g was achieved at a current rate of 23 mu A/cm(2) after 40 cycles for SnO@GNS and SnO2@GNS anodes, respectively. (C) 2014 Elsevier Ltd. All rights reserved.

Solving Axisymmetric Stability Problems by Using Upper Bound Finite Elements, Limit Analysis, and Linear Optimization

A numerical formulation has been proposed for solving an axisymmetric stability problem in geomechanics with upper bound limit analysis, finite elements, and linear optimization. The Drucker-Prager yield criterion is linearized by simulating a sphere with a circumscribed truncated icosahedron. The analysis considers only the velocities and plastic multiplier rates, not the stresses, as the basic unknowns. The formulation is simple to implement, and it has been employed for finding the collapse loads of a circular footing placed over the surface of a cohesive-frictional material. The formulation can be used to solve any general axisymmetric geomechanics stability problem.

Quantum simulation using fidelity-profile optimization

Experimental quantum simulation of a Hamiltonian H requires unitary operator decomposition (UOD) of its evolution unitary U = exp(-iHt) in terms of native unitary operators of the experimental system. Here, using a genetic algorithm, we numerically evaluate the most generic UOD (valid over a continuous range of Hamiltonian parameters) of the unitary operator U, termed fidelity-profile optimization. The optimization is obtained by systematically evaluating the functional dependence of experimental unitary operators (such as single-qubit rotations and time-evolution unitaries of the system interactions) to the Hamiltonian (H) parameters. Using this technique, we have solved the experimental unitary decomposition of a controlled-phase gate (for any phase value), the evolution unitary of the Heisenberg XY interaction, and simulation of the Dzyaloshinskii-Moriya (DM) interaction in the presence of the Heisenberg XY interaction. Using these decompositions, we studied the entanglement dynamics of a Bell state in the DM interaction and experimentally verified the entanglement preservation procedure of Hou et al. Ann. Phys. (N.Y.) 327, 292 (2012)] in a nuclear magnetic resonance quantum information processor.

Freeform Skeletal Shape Optimization of Compliant Mechanisms

Compliant mechanisms are elastic continua used to transmit or transform force and motion mechanically. The topology optimization methods developed for compliant mechanisms also give the shape for a chosen parameterization of the design domain with a fixed mesh. However, in these methods, the shapes of the flexible segments in the resulting optimal solutions are restricted either by the type or the resolution of the design parameterization. This limitation is overcome in this paper by focusing on optimizing the skeletal shape of the compliant segments in a given topology. It is accomplished by identifying such segments in the topology and representing them using Bezier curves. The vertices of the Bezier control polygon are used to parameterize the shape-design space. Uniform parameter steps of the Bezier curves naturally enable adaptive finite element discretization of the segments as their shapes change. Practical constraints such as avoiding intersections with other segments, self-intersections, and restrictions on the available space and material, are incorporated into the formulation. A multi-criteria function from our prior work is used as the objective. Analytical sensitivity analysis for the objective and constraints is presented and is used in the numerical optimization. Examples are included to illustrate the shape optimization method.

Fabrication and characterization of gold coated hollow silicon microneedle array for drug delivery

In this paper, we present the fabrication and characterization of Ti and Au coated hollow silicon microneedles for transdermal drug delivery applications. The hollow silicon microneedles are fabricated using isotropic etching followed by anisotropic etching to obtain a tapered tip. Silicon microneedle of 300 mu m in height, with 130 mu m outer diameter and 110 mu m inner diameter at the tip followed by 80 mu m inner diameter and 160 mu m outer diameter at the base have been fabricated. In order to improve the biocompatibility of microneedles, the fabricated microneedles were coated with Ti (500 nm) by sputtering technique followed by gold coating using electroplating. A breaking force of 225 N was obtained for the fabricated microneedles, which is 10 times higher than the skin resistive force. Hence, fabricated microneedles can easily be inserted inside the skin without breakage. The fluid flow through the microneedles was studied for different inlet pressures. A minimum inlet pressure of 0.66 kPa was required to achieve a flow rate of 50 mu l in 2 s with de-ionized water as a fluid medium. (C) 2014 Elsevier B.V. All rights reserved.

Smoothed Functional Algorithms for Stochastic Optimization Using q-Gaussian Distributions

Smoothed functional (SF) schemes for gradient estimation are known to be efficient in stochastic optimization algorithms, especially when the objective is to improve the performance of a stochastic system However, the performance of these methods depends on several parameters, such as the choice of a suitable smoothing kernel. Different kernels have been studied in the literature, which include Gaussian, Cauchy, and uniform distributions, among others. This article studies a new class of kernels based on the q-Gaussian distribution, which has gained popularity in statistical physics over the last decade. Though the importance of this family of distributions is attributed to its ability to generalize the Gaussian distribution, we observe that this class encompasses almost all existing smoothing kernels. This motivates us to study SF schemes for gradient estimation using the q-Gaussian distribution. Using the derived gradient estimates, we propose two-timescale algorithms for optimization of a stochastic objective function in a constrained setting with a projected gradient search approach. We prove the convergence of our algorithms to the set of stationary points of an associated ODE. We also demonstrate their performance numerically through simulations on a queuing model.

A perturbed martingale approach to global optimization

A new global stochastic search, guided mainly through derivative-free directional information computable from the sample statistical moments of the design variables within a Monte Carlo setup, is proposed. The search is aided by imparting to the directional update term additional layers of random perturbations referred to as `coalescence' and `scrambling'. A selection step, constituting yet another avenue for random perturbation, completes the global search. The direction-driven nature of the search is manifest in the local extremization and coalescence components, which are posed as martingale problems that yield gain-like update terms upon discretization. As anticipated and numerically demonstrated, to a limited extent, against the problem of parameter recovery given the chaotic response histories of a couple of nonlinear oscillators, the proposed method appears to offer a more rational, more accurate and faster alternative to most available evolutionary schemes, prominently the particle swarm optimization. (C) 2014 Elsevier B.V. All rights reserved.