Optical waveguides and switches based on periodic arrays of carbon nanotubes

This document presents the modeling and characterization of novel optical devices based on periodic arrays of multiwalled carbon nanotubes. Vertically aligned carbon nanotubes can be grown in the arrangement of two-dimensional arrays of precisely determined dimensions. Having their dimensions comparable to the wavelength of light makes carbon nanotubes good candidates for utilization in nano-scale optical devices. We report that highly dense periodic arrays of multiwalled carbon nanotubes can be utilized as sub-wavelength structures for establishing advanced optical materials, such as metamaterials and photonic crystals. We demonstrate that when carbon nanotubes are grown close together at spacing of the order of few hundred nanometers, they display artificial optical properties towards the incident light, acting as metamaterials. By utilizing these properties we have established micro-scaled plasmonic high pass filter which operates in the optical domain. Highly dense arrays of multiwalled also offer a periodic dielectric constant to the incident light and display interesting photonic band gaps, which are frequency domains within which on wave propagation can take place. We have utilized these band gaps displayed by a periodic nanotube array, having 400 nm spacing, to construct photonic crystals based optical waveguides and switches. © 2011 IEEE.

Problems in estimating the response functions of natural climatic recording systems [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): High-resolution proxy records of climate, such as varves, ice cores, and tree-rings, provide the opportunity for reconstructing climate on a year-by-year basis. In order to do so it is necessary to approximate the complex nonlinear response function of the natural recording system using linear statistical models. Three problems with this approach were discussed, and possible solutions were suggested. Examples were given from a reconstruction of Santa Barbara precipitation based on tree-ring records from Santa Barbara County.

Periodic autoregressive moving average models for the analysis of streamflow [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Streamflow values show definite seasonal patterns in their month-to-month correlation structure. The structure also seems to vary as a function of the type of stream (coastal versus mountain or humid versus arid region). The standard autoregressive moving average (ARMA) time series model is incapable of reproducing this correlation structure. ... A periodic ARMA time series model is one in which an ARMA model is fitted to each month or season but the parameters of the model are constrained to be periodic according to a Fourier series. This constraint greatly reduces the number of parameters but still leaves the flexibility for matching the seasonally varying correlograms.