Electromagnetic characteristics of carbon nanotubes with strain

Electromagnetic characteristics like absorption and electric field distributions of metallic carbon nanotubes are simulated using the discrete dipole approximation. Absorption of electromagnetic energy over a range of frequencies are studied for both parallel and perpendicular incidence of light to the axis of carbon nanotube. Our simulations show 30% enhancement of electric field in the radial direction for nanotubes with axial strain of 0.2 when compared to unstrained nanotubes in case of parallel incidence of light. Simulations for perpendicular incidence of light show an oscillatory behavior for the electric field in the axial direction. Analysis of simulation results indicate potential applications in designing nanostructured antennae and electromagnetic transmission/shielding using CNT-composite.

Radiative and non-radiative effects of a substrate on localized plasmon resonance of particles

Experiments have shown strong effects of some substrates on the localized plasmons of metallic nano particles but they are inconclusive on the affecting parameters. Here, we have used discrete dipole approximation in conjunction with Sommerfeld integral relations to explain the effect of the substrates as a function of the parameters of incident radiation. The radiative coupling can both quench and enhance the resonance and its dependence on the angle and polarization of incident radiation with respect to the surface is shown. Non-radiative interaction with the substrate enhances the plasmon resonance of the particles and can shift the resonances from their free-space energies significantly. The non-radiative interaction of the substrate is sensitive to the shape of particles and polarization of incident radiation with respect to substrate. Our results show that the plasmon resonances in coupled and single particles can be significantly altered from their free-space resonances and are quenched or enhanced by the choice of substrate and polarization of incident radiation. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4736544]

Electromagnetic Characteristics of Polyaniline/SWCNT Composites

Electromagnetic field interactions with the composites made up of polyaniline (PANI) and single wall carbon nanotube (SWCNT) are simulated using the discrete dipole approximation. Recent observations on polymer nano-composites explain the interface interactions between the PANI host and the carbon nanostructures. These types of composite have potential applications in organic solar cell, gas sensor, bio-sensor and electro-chromic devices. Various nanostructures of PANI is possible in the form of nanowires, nanodisks, nanofibers and nanotubes have been reported. In the present study, we considered two types of composite, one is the PANI wrapped CNT and the other is CNT immersed in PANI nanotube. We use Modified Thole's parameters for calculating frequency dependent atomic polarizability of composites. Absorption spectra of the composites are studied by illuminating a wide range of electromagnetic energy spectrum. From the absorption spectra, we observe plasmon excitation in near-infrared region similar to that in SWCNTs reported recently. The interactions between the PANI and CNT in the composite, resulting electromagnetic absorptions are simulated.

Metallic Nanoparticles Arranged in a Helical Geometry: Route Towards Strong and Broadband Chiro-optical Response

Recent advances in nanotechnology have paved ways to various techniques for designing and fabricating novel nanostructures incorporating noble metal nanoparticles, for a wide range of applications. The interaction of light with metal nanoparticles (NPs) can generate strongly localized electromagnetic fields (Localized Surface Plasmon Resonance, LSPR) at certain wavelengths of the incident beam. In assemblies or structures where the nanoparticles are placed in close proximity, the plasmons of individual metallic NPs can be strongly coupled to each other via Coulomb interactions. By arranging the metallic NPs in a chiral (e.g. helical) geometry, it is possible to induce collective excitations, which lead to differential optical response of the structures to right-and left circularly polarized light (e.g. Circular Dichroism - CD). Earlier reports in this field include novel techniques of synthesizing metallic nanoparticles on biological helical templates made from DNA, proteins etc. In the present work, we have developed new ways of fabricating chiral complexes made of metallic NPs, which demonstrate a very strong chiro-optical response in the visible region of the electromagnetic spectrum. Using DDA (Discrete Dipole Approximation) simulations, we theoretically studied the conditions responsible for large and broadband chiro-optical response. This system may be used for various applications, for example those related to polarization control of visible light, sensing of proteins and other chiral bio-molecules, and many more.

Excitation energy transfer from a fluorophore to single-walled carbon nanotubes

We study the process of electronic excitation energy transfer from a fluorophore to the electronic energy levels of a single-walled carbon nanotube. The matrix element for the energy transfer involves the Coulombic interaction between the transition densities on the donor and the acceptor. In the Foumlrster approach, this is approximated as the interaction between the corresponding transition dipoles. For energy transfer from a dye to a nanotube, one can use the dipole approximation for the dye, but not for the nanotube. We have therefore calculated the rate using an approach that avoids the dipole approximation for the nanotube. We find that for the metallic nanotubes, the rate has an exponential dependence if the energy that is to be transferred, h is less than a threshold and a d(-5) dependence otherwise. The threshold is the minimum energy required for a transition other than the k(i,perpendicular to)=0 and l=0 transition. Our numerical evaluation of the rate of energy transfer from the dye pyrene to a (5,5) carbon nanotube, which is metallic leads to a distance of similar to 165 A degrees up to which energy transfer is appreciable. For the case of transfer to semiconducting carbon nanotubes, apart from the process of transfer to the electronic energy levels within the one electron picture, we also consider the possibility of energy transfer to the lowest possible excitonic state. Transfer to semiconducting carbon nanotubes is possible only if>=epsilon(g)-epsilon(b). The long range behavior of the rate of transfer has been found to have a d(-5) dependence if h >=epsilon(g). But, when the emission energy of the fluorophore is in the range epsilon(g)>h >=epsilon(g)-epsilon(b), the rate has an exponential dependence on the distance. For the case of transfer from pyrene to the semiconducting (6,4) carbon nanotube, energy transfer is found to be appreciable up to a distance of similar to 175 A degrees.

Robust Approach for Identification of Bad Data in State Estimation Using SLP Technique

This paper proposes a new approach for solving the state estimation problem. The approach is aimed at producing a robust estimator that rejects bad data, even if they are associated with leverage-point measurements. This is achieved by solving a sequence of Linear Programming (LP) problems. Optimization is carried via a new algorithm which is a combination of “upper bound optimization technique" and “an improved algorithm for discrete linear approximation". In this formulation of the LP problem, in addition to the constraints corresponding to the measurement set, constraints corresponding to bounds of state variables are also involved, which enables the LP problem more efficient in rejecting bad data, even if they are associated with leverage-point measurements. Results of the proposed estimator on IEEE 39-bus system and a 24-bus EHV equivalent system of the southern Indian grid are presented for illustrative purpose.

Generalized model predictive static programming and its application to 3D impact angle constrained guidance of air-to-surface missiles

A new `generalized model predictive static programming (G-MPSP)' technique is presented in this paper in the continuous time framework for rapidly solving a class of finite-horizon nonlinear optimal control problems with hard terminal constraints. A key feature of the technique is backward propagation of a small-dimensional weight matrix dynamics, using which the control history gets updated. This feature, as well as the fact that it leads to a static optimization problem, are the reasons for its high computational efficiency. It has been shown that under Euler integration, it is equivalent to the existing model predictive static programming technique, which operates on a discrete-time approximation of the problem. Performance of the proposed technique is demonstrated by solving a challenging three-dimensional impact angle constrained missile guidance problem. The problem demands that the missile must meet constraints on both azimuth and elevation angles in addition to achieving near zero miss distance, while minimizing the lateral acceleration demand throughout its flight path. Both stationary and maneuvering ground targets are considered in the simulation studies. Effectiveness of the proposed guidance has been verified by considering first order autopilot lag as well as various target maneuvers.

Optimal threshold policies for admission control in communication networks via discrete parameter stochastic approximation

The problem of admission control of packets in communication networks is studied in the continuous time queueing framework under different classes of service and delayed information feedback. We develop and use a variant of a simulation based two timescale simultaneous perturbation stochastic approximation (SPSA) algorithm for finding an optimal feedback policy within the class of threshold type policies. Even though SPSA has originally been designed for continuous parameter optimization, its variant for the discrete parameter case is seen to work well. We give a proof of the hypothesis needed to show convergence of the algorithm on our setting along with a sketch of the convergence analysis. Extensive numerical experiments with the algorithm are illustrated for different parameter specifications. In particular, we study the effect of feedback delays on the system performance.

A fully discrete C-0 interior penalty Galerkin approximation of the extended Fisher-Kolmogorov equation

A fully discrete C-0 interior penalty finite element method is proposed and analyzed for the Extended Fisher-Kolmogorov (EFK) equation u(t) + gamma Delta(2)u - Delta u + u(3) - u = 0 with appropriate initial and boundary conditions, where gamma is a positive constant. We derive a regularity estimate for the solution u of the EFK equation that is explicit in gamma and as a consequence we derive a priori error estimates that are robust in gamma. (C) 2013 Elsevier B.V. All rights reserved.

Discrete parameter simulation optimization algorithms with applications to admission control with dependent service times

We propose certain discrete parameter variants of well known simulation optimization algorithms. Two of these algorithms are based on the smoothed functional (SF) technique while two others are based on the simultaneous perturbation stochastic approximation (SPSA) method. They differ from each other in the way perturbations are obtained and also the manner in which projections and parameter updates are performed. All our algorithms use two simulations and two-timescale stochastic approximation. As an application setting, we consider the important problem of admission control of packets in communication networks under dependent service times. We consider a discrete time slotted queueing model of the system and consider two different scenarios - one where the service times have a dependence on the system state and the other where they depend on the number of arrivals in a time slot. Under our settings, the simulated objective function appears ill-behaved with multiple local minima and a unique global minimum characterized by a sharp dip in the objective function in a small region of the parameter space. We compare the performance of our algorithms on these settings and observe that the two SF algorithms show the best results overall. In fact, in many cases studied, SF algorithms converge to the global minimum.

Network flow-control using asynchronous stochastic approximation

We propose several stochastic approximation implementations for related algorithms in flow-control of communication networks. First, a discrete-time implementation of Kelly's primal flow-control algorithm is proposed. Convergence with probability 1 is shown, even in the presence of communication delays and stochastic effects seen in link congestion indications. This ensues from an analysis of the flow-control algorithm using the asynchronous stochastic approximation (ASA) framework. Two relevant enhancements are then pursued: a) an implementation of the primal algorithm using second-order information, and b) an implementation where edge-routers rectify misbehaving flows. Next, discretetime implementations of Kelly's dual algorithm and primaldual algorithm are proposed. Simulation results a) verifying the proposed algorithms and, b) comparing the stability properties are presented.

Heat transfer in rarefied couette flow on the basis of discrete ordinate method

The method of discrete ordinates, in conjunction with the modified "half-range" quadrature, is applied to the study of heat transfer in rarefied gas flows. Analytic expressions for the reduced distribution function, the macroscopic temperature profile and the heat flux are obtained in the general n-th approximation. The results for temperature profile and heat flux are in sufficiently good accord both with the results of the previous investigators and with the experimental data.

Stochastic Algorithms for Discrete Parameter Simulation Optimization

We present two efficient discrete parameter simulation optimization (DPSO) algorithms for the long-run average cost objective. One of these algorithms uses the smoothed functional approximation (SFA) procedure, while the other is based on simultaneous perturbation stochastic approximation (SPSA). The use of SFA for DPSO had not been proposed previously in the literature. Further, both algorithms adopt an interesting technique of random projections that we present here for the first time. We give a proof of convergence of our algorithms. Next, we present detailed numerical experiments on a problem of admission control with dependent service times. We consider two different settings involving parameter sets that have moderate and large sizes, respectively. On the first setting, we also show performance comparisons with the well-studied optimal computing budget allocation (OCBA) algorithm and also the equal allocation algorithm. Note to Practitioners-Even though SPSA and SFA have been devised in the literature for continuous optimization problems, our results indicate that they can be powerful techniques even when they are adapted to discrete optimization settings. OCBA is widely recognized as one of the most powerful methods for discrete optimization when the parameter sets are of small or moderate size. On a setting involving a parameter set of size 100, we observe that when the computing budget is small, both SPSA and OCBA show similar performance and are better in comparison to SFA, however, as the computing budget is increased, SPSA and SFA show better performance than OCBA. Both our algorithms also show good performance when the parameter set has a size of 10(8). SFA is seen to show the best overall performance. Unlike most other DPSO algorithms in the literature, an advantage with our algorithms is that they are easily implementable regardless of the size of the parameter sets and show good performance in both scenarios.

A constant factor approximation algorithm for boxicity of circular arc graphs

The boxicity (resp. cubicity) of a graph G(V, E) is the minimum integer k such that G can be represented as the intersection graph of axis parallel boxes (resp. cubes) in R-k. Equivalently, it is the minimum number of interval graphs (resp. unit interval graphs) on the vertex set V, such that the intersection of their edge sets is E. The problem of computing boxicity (resp. cubicity) is known to be inapproximable, even for restricted graph classes like bipartite, co-bipartite and split graphs, within an O(n(1-epsilon))-factor for any epsilon > 0 in polynomial time, unless NP = ZPP. For any well known graph class of unbounded boxicity, there is no known approximation algorithm that gives n(1-epsilon)-factor approximation algorithm for computing boxicity in polynomial time, for any epsilon > 0. In this paper, we consider the problem of approximating the boxicity (cubicity) of circular arc graphs intersection graphs of arcs of a circle. Circular arc graphs are known to have unbounded boxicity, which could be as large as Omega(n). We give a (2 + 1/k) -factor (resp. (2 + log n]/k)-factor) polynomial time approximation algorithm for computing the boxicity (resp. cubicity) of any circular arc graph, where k >= 1 is the value of the optimum solution. For normal circular arc (NCA) graphs, with an NCA model given, this can be improved to an additive two approximation algorithm. The time complexity of the algorithms to approximately compute the boxicity (resp. cubicity) is O(mn + n(2)) in both these cases, and in O(mn + kn(2)) = O(n(3)) time we also get their corresponding box (resp. cube) representations, where n is the number of vertices of the graph and m is its number of edges. Our additive two approximation algorithm directly works for any proper circular arc graph, since their NCA models can be computed in polynomial time. (C) 2014 Elsevier B.V. All rights reserved.

Analytical approximation solutions for 3-D optical waveguides: Review

The rectangular dielectric waveguide is the most commonly used structure in integrated optics, especially in semi-conductor diode lasers. Demands for new applications such as high-speed data backplanes in integrated electronics, waveguide filters, optical multiplexers and optical switches are driving technology toward better materials and processing techniques for planar waveguide structures. The infinite slab and circular waveguides that we know are not practical for use on a substrate because the slab waveguide has no lateral confinement and the circular fiber is not compatible with the planar processing technology being used to make planar structures. The rectangular waveguide is the natural structure. In this review, we have discussed several analytical methods for analyzing the mode structure of rectangular structures, beginning with a wave analysis based on the pioneering work of Marcatili. We study three basic techniques with examples to compare their performance levels. These are the analytical approach developed by Marcatili, the perturbation techniques, which improve on the analytical solutions and the effective index method with examples.