Highly Efficient and Thermally Stable Second-Order Nonlinear Optical Chromophores and Electrooptic Polymers

Organic polymeric electro-optic (E-O) materials have attracted significant attention because of their potential use as fast and efficient components of integrated photonic devices (1,2). However, the practical application of these materials in optical devices is somewhat limited by the stringent material requirements imposed by the device design, fabrication processes and operating environments. Among the various material requirements, the most notable ones are large electro-optic coefficients (r(33)) and high thermal stability (3). The design of poled polymeric materials with high electro-optic activity (r(33)) involves the optimization of the percent incorporation of efficient (large beta mu) second order nonlinear optical (NLO) chromophores into the polymer matrices and the effective creation of poling-induced non-centrosymmetric structures. The factors that affect the material stability are a) the inherent thermal stability of the NLO chromophores, b) the chemical stability of the NLO chromophores during the polymer processing conditions, and c) the long-term dipolar alignment stability at high temperatures. Although considerable progress has been made in achieving these properties (4), organic polymeric materials suitable for practical E-O device applications are yet to be developed. This chapter highlights some of our approaches in the optimization of molecular and material nonlinear optical and thermal properties.

The algebra and geometry of SU(3) matrices

We give an elementary treatment of the defining representation and Lie algebra of the three-dimensional unitary unimodular group SU(3). The geometrical properties of the Lie algebra, which is an eight dimensional real Linear vector space, are developed in an SU(3) covariant manner. The f and d symbols of SU(3) lead to two ways of 'multiplying' two vectors to produce a third, and several useful geometric and algebraic identities are derived. The axis-angle parametrization of SU(3) is developed as a generalization of that for SU(2), and the specifically new features are brought out. Application to the dynamics of three-level systems is outlined.

Synthesis, crystal structure and magnetic properties of a polymeric copper(II) Schiff-base complex having binuclear units covalently linked by isonicotinate ligands

The polynuclear copper(II) complex [{Cu2L(O2CC5H4N)}. C2H5OH](x) (1), where H3L is a 1∶2 Schiff base derived from 1,3-diaminopropan-2-ol and salicylaldehyde, has been prepared and structurally characterized. The structure consists of a one-dimensional zigzag chain in which the binuclear [Cu2L](+) units are covalently linked by isonicotinate ligands to give a syndiotactic arrangement of the copper ions protruding outside the chain. In the basic unit, the copper(II) centres are bridged by an alkoxo and a carboxylato ligand, giving a Cu ... Cu distance of 3.492(3) Angstrom and a Cu-O-Cu angle of 130.9(2)degrees. While one copper centre has a square-planar geometry, the other copper is square-pyramidal with the pyridine nitrogen being the axial ligand. The visible electronic spectrum of 1 shows a broad d-d band at 615 nm. The complex shows a rhombic X-band EPR spectral pattern in the polycrystalline phase at 77 K. Magnetic susceptibility measurements in the temperature range 22 to 295 K demonstrate the antiferromagnetic behaviour of 1. A theoretical fit to the magnetic data is based on a model assuming 1 as an equimolar mixture of copper atoms belonging to an antiferromagnetically coupled one-dimensional Heisenberg chain with the other copper atoms outside the chain behaving like paramagnetic centres.

Accelerated weathering of distribution class polymeric insulators

This paper deals with the long-term accelerated weathering of 11 kV polymeric insulators for 25000 h. Polymeric insulators were continuously subjected to accelerated weathering in a specially designed multistress-aging chamber under UV radiation, temperature and electric stress. Chemical, physical and electrical changes due to degradation have been assessed using various techniques. Some of the interesting results observed indicate that there is a significant reduction in the content of low molecular weight molecules, hydrophobicity was dynamic in nature and there is a significant increase in the surface roughness and oxidation levels with respect to the duration of the weathering.

Robust Formulations for Handling Uncertainty in Kernel Matrices

We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we derive a formulation which is robust to such noise. The resulting formulation applies when the noise is Gaussian, or has finite support. The formulation in general is non-convex, but in several cases of interest it reduces to a convex program. The problem of uncertainty in kernel matrix is motivated from the real world problem of classifying proteins when the structures are provided with some uncertainty. The formulation derived here naturally incorporates such uncertainty in a principled manner leading to significant improvements over the state of the art. 1.

Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions

In this paper we consider the problem of learning an n × n kernel matrix from m(1) similarity matrices under general convex loss. Past research have extensively studied the m = 1 case and have derived several algorithms which require sophisticated techniques like ACCP, SOCP, etc. The existing algorithms do not apply if one uses arbitrary losses and often can not handle m > 1 case. We present several provably convergent iterative algorithms, where each iteration requires either an SVM or a Multiple Kernel Learning (MKL) solver for m > 1 case. One of the major contributions of the paper is to extend the well knownMirror Descent(MD) framework to handle Cartesian product of psd matrices. This novel extension leads to an algorithm, called EMKL, which solves the problem in O(m2 log n 2) iterations; in each iteration one solves an MKL involving m kernels and m eigen-decomposition of n × n matrices. By suitably defining a restriction on the objective function, a faster version of EMKL is proposed, called REKL,which avoids the eigen-decomposition. An alternative to both EMKL and REKL is also suggested which requires only an SVMsolver. Experimental results on real world protein data set involving several similarity matrices illustrate the efficacy of the proposed algorithms.

Temperature dependence of infrared and Raman modes in polymeric RbC60

Temperature dependence of the intra-molecular vibrational modes Of C-60 in the quasi-1D polymeric RbC60, across the low temperature transition at similar to50 K, has been probed through infrared (IR) and Raman spectroscopies. With the lowering of temperature, the split IR modes of RbC60 are seen to harden but below 50 K a small but definitive signature of an anomalous softening is observed. In addition, the background IR transmission shows an increase below 50 K with the opening of a well defined gap in the electronic spectrum. The implications of these results, along with those of Raman measurements, are discussed in terms of the interaction of intra-molecular phonons with electrons and spin excitations in the system. (C) 2002 Published by Elsevier Science Ltd.

A new polymeric flame retardant additive for vinyl polymers

Diethyl allyl phosphate (DEAP) monomer has been synthesized, and characterized, using H-1 NMR and direct ionization mass spectrometric (DI-MS) techniques. It was free-radically polymerized to yield the poly(diethyl allyl phosphate) (PDEAP). The direct pyrolysis-mass spectrometric (DP-MS) analysis of the PDEAP revealed that it undergoes thermal degradation to yield mainly the monomer. Utility of PDEAP as a potent flame-retardant additive in polystyrene (PS) and poly(methyl methacrylate) (PMMA) has also been established.

Synthesis and Properties of a Novel (Main-Chain)– (Side-Chain) Polymeric Peroxide

A novel (main-chain)-(side-chain) vinyl polyperoxide, poly(dipentene peroxide)(PDP), an alternating copolymer of dipentene (DP) and oxygen, has been synthesized by thermal oxidative polymerization of DP. The PDP was characterized by 1H NMR, 13C NMR, FTIR, DSC, TGA, and EI-MS studies. The overall activation energies of the degradation from Kissinger’s method were 28 and 33 kcal/mol, respectively, for the endocyclic and acyclic peroxide units. The side-chain peroxy groups were found to be thermally more stable than the main chain. Above 45°C the rate of polymerization increases sharply at a particular instant showing an “autoacceleration” with the formation of knee point. The kinetics of autoacceleration has been studied at various temperatures (45–70°C) and pressures (50–250 psi). © 2000 John Wiley&Sons, Inc. J Appl Polym Sci 79: 1549–1555, 2001

Superconductivity of embedded lead nano particles in metallic and amorphous matrices

Nanodispersed lead in metallic and amorphous matrices was synthesized by rapid solidification processing. The optimum microstructure was tailored to avoid percolation of the particles. With these embedded particles it is possible to study quantitatively the effect of size on the superconducting transition temperature by carrying out quantitative microstructural characterization and magnetic measurements. Our results suggest the role of the matrices in enhancement or depression of superconducting transition temperature of lead. The origin of this difference in behavior with respect to different matrices and sizes is discussed.

Closed form solutions for element equilibrium and flexibility matrices of eight node rectangular plate bending element using integrated force method

Closed form solutions for equilibrium and flexibility matrices of the Mindlin-Reissner theory based eight-node rectangular plate bending element (MRP8) using integrated Force Method (IFM) are presented in this paper. Though these closed form solutions of equilibrium and flexibility matrices are applicable to plate bending problems with square/rectangular boundaries, they reduce the computational time significantly and give more exact solutions. Presented closed form solutions are validated by solving large number of standard square/rectangular plate bending benchmark problems for deflections and moments and the results are compared with those of similar displacement-based eight-node quadrilateral plate bending elements available in the literature. The results are also compared with the exact solutions.

Functionalized and Postfunctionalizable Porous Polymeric Films through Evaporation-Induced Phase Separation Using Mixed Solvents

Condensation of water droplets during rapid evaporation of a polymer solution, under humid conditions, has been known to generate uniformly porous polymer films. Similar porous films are also formed when a solution of the polymer in THF containing small amounts of water, is allowed to evaporate rapidly under air flow; this suggests that water droplets may be formed during the final stages of film formation. In the presence of added surfactants, the interface of water droplets could become lined with the surfactants and consequently the internal walls of the pores generated, upon removal of the water, could become decorated with the hydrophilic head groups of the surfactant molecules. In a series of carefully designed experiments, we have examined the effect of added surfactants, both anionic and cationic, on the formation of porous PMMA films; the films were prepared by evaporating a solution of the polymer in THF containing controlled amounts of aqueous surfactant solutions. We observed that the average size of the pores decreases with increasing surfactant concentration, while it increases with increasing amounts of added water. The size of the pores and their distribution were examined using AFM and IR imaging methods. Although IR imaging possessed inadequate resolution to confirm the presence of surfactants at the pore surface, exchange of the inorganic counterion, such as the sodium-ion of SDS, with suitable ionic organic dyes permitted the unequivocal demonstration of the presence of the surfactants at the interface by the use of confocal fluorescence microscopy.

Gel Sculpture: Moldable, Load-Bearing and Self-Healing Non-Polymeric Supramolecular Gel Derived from a Simple Organic Salt

An easy access to a library of simple organic salts derived from tert-butoxycarbonyl (Boc)-protected L-amino acids and two secondary amines (dicyclohexyl- and dibenzyl amine) are synthesized following a supramolecular synthon rationale to generate a new series of low molecular weight gelators (LMWGs). Out of the 12 salts that we prepared, the nitrobenzene gel of dicyclohexylammonium Boc-glycinate (GLY.1) displayed remarkable load-bearing, moldable and self-healing properties. These remarkable properties displayed by GLY.1 and the inability to display such properties by its dibenzylammonium counterpart (GLY.2) were explained using microscopic and rheological data. Single crystal structures of eight salts displayed the presence of a 1D hydrogen-bonded network (HBN) that is believed to be important in gelation. Powder X-ray diffraction in combination with the single crystal X-ray structure of GLY.1 clearly established the presence of a 1D hydrogen-bonded network in the xerogel of the nitrobenzene gel of GLY.1. The fact that such remarkable properties arising from an easily accessible (salt formation) small molecule are due to supramolecular (non-covalent) interactions is quite intriguing and such easily synthesizable materials may be useful in stress-bearing and other applications.

Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices

In this paper we study the problem of designing SVM classifiers when the kernel matrix, K, is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the problem using the Robust Optimization methodology. This reduces the uncertain SVM problem into a deterministic conic quadratic problem which can be solved in principle by a polynomial time Interior Point (IP) algorithm. However, for large-scale classification problems, IP methods become intractable and one has to resort to first-order gradient type methods. The strategy we use here is to reformulate the robust counterpart of the uncertain SVM problem as a saddle point problem and employ a special gradient scheme which works directly on the convex-concave saddle function. The algorithm is a simplified version of a general scheme due to Juditski and Nemirovski (2011). It achieves an O(1/T-2) reduction of the initial error after T iterations. A comprehensive empirical study on both synthetic data and real-world protein structure data sets show that the proposed formulations achieve the desired robustness, and the saddle point based algorithm outperforms the IP method significantly.