First total synthesis of (±)-myltayl-4(12)-ene and single-crystal X-ray structure of exo-12-normyltaylan-4-yl 4-nitrobenzoate

The total synthesis of the unusual sesquiterpene (+/-)-myltayl-4(12)-ene 3 starting from the readily available cyclogeraniol 5 and the single-crystal X-ray structure of the 4-nitrobenzoate 12 of the noralcohol 11 are described.

Matrix method for eigenvalue assignment: The single input case

The eigenvalue assignment/pole placement procedure has found application in a wide variety of control problems. The associated literature is rather extensive with a number of techniques discussed to that end. In this paper a method for assigning eigenvalues to a Linear Time Invariant (LTI) single input system is proposed. The algorithm determines a matrix, which has eigenvalues at the desired locations. It is obtained from the knowledge of the open-loop system and the desired eigenvalues. Solution of the matrix equation, involving unknown controller gains, open-loop system matrices and desired eigenvalues, results in the state feedback controller. The proposed algorithm requires the closed-loop eigenvalues to be different from those of the open-loop case. This apparent constraint is easily overcome by a negligible shift in the values. Two examples are considered to verify the proposed algorithm. The first one pertains to the in-plane libration of a Tethered Satellite System (TSS) while the second is concerned with control of the short period dynamics of a flexible airplane. Finally, the method is extended to determine the Controllability Grammian, corresponding to the specified closed-loop eigenvalues, without computing the controller gains.

Probing Single and Bilayer Graphene Field Effect Transistors By Raman Spectroscopy

This article is a review of our work related to Raman studies of single layer and bilayer graphenes as a function Fermi level shift achieved by electrochemically top gating a field effect transistor. Combining the transport and in situ Raman studies of the field effect devices, a quantitative understanding is obtained of the phonon renormalization due to doping of graphene. Results are discussed in the light of time dependent perturbation theory, with electron phonon coupling parameter as an input from the density functional theory. It is seen that phonons near and Gamma and K points of the Brillouin zone are renormalized very differently by doping. Further, Gamma-phonon renormalization is different in bilayer graphene as compared to single layer, originating from their different electronic band structures near the zone boundary K-point. Thus Raman spectroscopy is not only a powerful probe to characterize the number of layers and their quality in a graphene sample, but also to quantitatively evaluate electron phonon coupling required to understand the performance of graphene devices.

Linear electro‐optic dispersion in (‐)‐2‐(α‐methylbenzylamino)‐5‐nitropyridine single crystals

The variation of the linear electro-optic effect in (-)-2-(alpha-methylbenzylamino)-5-nitropyridine with the wavelength of the incident light at room temperature has been measured. The reduced half-wave voltages have been found to have the values 2.1, 2.8, and 6.0 kV at 488, 514.5, and 632.8 nm respectively and the corresponding values of the linear electro-optic coefficient have been evaluated.;The interpretation of the results in terms of the structures of the molecule and the crystal is discussed. The thermal variation of the birefringence has also been investigated and the coefficient for the temperature variation of the refractive index difference is found to have the value (d Delta n/dT)=9.3X10(-5) K-1.

Matrix method for eigenvalue assignment: The single input case

The eigenvalue assignment/pole placement procedure has found application in a wide variety of control problems. The associated literature is rather extensive with a number of techniques discussed to that end. In this paper a method for assigning eigenvalues to a Linear Time Invariant (LTI) single input system is proposed. The algorithm determines a matrix, which has eigenvalues at the desired locations. It is obtained from the knowledge of the open-loop system and the desired eigenvalues. Solution of the matrix equation, involving unknown controller gains, open-loop system matrices and desired eigenvalues, results in the state feedback controller. The proposed algorithm requires the closed-loop eigenvalues to be different from those of the open-loop case. This apparent constraint is easily overcome by a negligible shift in the values. Two examples are considered to verify the proposed algorithm. The first one pertains to the in-plane libration of a Tethered Satellite System (TSS) while the second is concerned with control of the short period dynamics of a flexible airplane. Finally, the method is extended to determine the Controllability Grammian, corresponding to the specified closed-loop eigenvalues, without computing the controller gains.

Precipitation in small systems-I. stochastic analysis

Precipitation in small droplets involving emulsions, microemulsions or vesicles is important for Producing multicomponent ceramics and nanoparticles. Because of the random nature of nucleation and the small number of particles in a droplet, the use of a deterministic population balance equation for predicting the number density of particles may lead to erroneous results even for evaluating the mean behavior of such systems. A comparison between the predictions made through stochastic simulation and deterministic population balance involving small droplets has been made for two simple systems, one involving crystallization and the other a single-component precipitation. The two approaches have been found to yield quite different results under a variety of conditions. Contrary to expectation, the smallness of the population alone does not cause these deviations. Thus, if fluctuation in supersaturation is negligible, the population balance and simulation predictions concur. However, for large fluctuations in supersaturation, the predictions differ significantly, indicating the need to take the stochastic nature of the phenomenon into account. This paper describes the stochastic treatment of populations, which involves a sequence of so-called product density equations and forms an appropriate framework for handling small systems.

Pressure-induced band gap reduction, orientational ordering and reversible amorphization in single crystals of C70: Photoluminescence and Raman studies

Photoluminescence and Raman scattering experiments have been carried out on single crystals of C70 up to 31 GPa to investigate the effect of pressure on the optical band gap, vibrational modes and stability of the molecule. The photoluminescence band shifts to lower energies and the pressure dependence of the band maxima yields the hydrostatic deformation potential to be 2.15 eV. The slope changes in the pressure dependence of peak positions and linewidths of the Raman modes associated with the intramolecular vibrations at 1 GPa mark the known face-centred cubic-->rhombohedral orientational ordering transition. The reversible amorphization in C70 at P > 20 GPa has been compared with the irreversible amorphization in C60 at P > 22 GPa in terms of carbon-carbon distance between the neighbouring molecules at the threshold transition pressures, in conjunction with the interplay between the intermolecular and intramolecular interactions.

Effect of substitution of Y on the structural, magnetic, and thermal properties of hexagonal DyMnO3 single crystals

We investigate the structural, magnetic, and specific heat behavior of the hexagonal manganite Dy0.5Y0.5MnO3 in order to understand the effect of dilution of Dy magnetism with nonmagnetic yttrium. In this compound, the triangular Mn lattice orders antiferromagnetic at T-N(Mn) approximate to 68 K observed experimentally in the derivative of magnetic susceptibility as well as in specific heat. In addition, a low-temperature peak at T-N(Dy) similar to 3 K is observed in specific heat which is attributed to rare earth order. The T-N(Mn) increases by 9 K compared to that of hexagonal (h) DyMnO3 while T-N(Dy) is unchanged. A change in slope of thermal evolution of lattice parameters is observed to occur at temperature close to T-N(Mn). This hints at strong magnetoelastic coupling in this geometric multiferroic. In magnetization measurements, steplike features are observed when the magnetic field is applied along the c axis which shift to higher fields with temperature and vanish completely above 40 K. The presence of different magnetic phases at low temperature and strong magnetoelastic effects can lead to such field-induced transitions which resemble metamagnetic transitions. This indicates the possibility of strong field-induced effects in dielectric properties of this material, which is unexplored to date.

Multiple UAV Coalitions for a Search and Prosecute Mission

Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.

Structural characterization of gel-grown neodymium copper oxalate single crystals

Sparingly soluble neodymium copper oxalate (NCO) single crystals were grown by gel method, by the diffusion of a mixture of neodymium nitrate and cupric nitrate into the set gel containing oxalic acid. Tabular crystal, revealing well-defined dissolution figures has been recorded. X-ray diffraction studies of the powdered sample reveal that NCO is crystalline. Infrared absorption spectrum confirmed the formation of oxalato complex with water of crystallization, while energy dispersive X-ray analysis established the presence of neodymium dominant over copper in the sample. X-ray photoelectron spectroscopic studies established the presence of Nd and Cu in oxide states besides (C2O4)(2-) oxalate group. The intensities of Nd (3d(5/2)) and Cu (2p(3/2)) peaks measured in terms of maximum photoelectron count rates also revealed the presence of Nd in predominance. The inductively coupled plasma analysis supports the EDAX and XPS data by the estimation of neodymium percentage by weight to that of copper present in the NCO sample. On the basis of these findings, an empirical structure for NCO has been proposed. The implications are discussed.

Robust/Optimal Temperature Profile Control of a High-Speed Aerospace Vehicle Using Neural Networks

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the �Single Network Adaptive Critic (SNAC)� is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Constructions of 2D-Metallamacrocycles Using Half-Sandwich Ru-2(II) Precursors: Synthesis, Molecular Structures, and Self-Selection for a Single Linkage Isomer

Coordination-driven self-assembly of oxalato-bridged half-sandwich p-cymene ruthenium complex Ru-2(mu-eta(4)-C2O4)(MeOH)(2)(eta(6)-p-cymene)(2)] (O3SCF3)(2) (1a) with several ditopic donors (L-a-L-d) in methanol affords a series of bi- and tetranuclear metallamacrocycles (2a and 3-5). Similarly, the combination of 2,5-dihydroxy-1,4-benzoquinonato (dhbq)-bridged binuclear complex Ru-2(mu-eta(4)-C6H2O4)(MeOH)(2)(eta(6)-p-cymene)(2)](O3SCF3)(2) (1b) with a flexible bidentate amide linker (L-a) in 1:1 molar ratio gave the corresponding tetranuclear complex 2b. All the macrocycles were isolated as their triflate salts in high yields and were fully characterized by various spectroscopic techniques. Finally, the molecular structures of all the assemblies were determined unambiguously by single-crystal X-diffraction analysis. Interestingly, the combination of acceptor 1a or 1b with an unsymmetrical linear ditopic donor L-a results in a self-sorted linkage isomeric (head-to-tail) macrocycle (2a or 2b) despite the possibility of formation of two different isomeric macrocycles (head-to-head or head-to-tail) due to different connectivity of the donor. Molecular structures of the complexes 2a and 2b showed tetranuclear rectangular geometry with dimensions of 5.51 angstrom x 13.29 angstrom for 2a and 7.91 angstrom x 13.46 angstrom for 2b. In both cases, two binuclear Ru-2(II) building blocks are connected by a mu-N-(4-pyridyl)isonicotinamide donor in a head-to-tail fashion. Surprisingly, the macrocycle 2a loses one counteranion and cocrystallizes with monodeprotonated 1,3,5-trihydroxybenzene via strong intermolecular pi-pi stacking and hydrogen bonding. The tweezer complex 3 showed strong fluorescence in solution, and it showed fluorescence sensing toward nitroaromatic compounds. A fluorescence study demonstrated a marked quenching of the initial fluorescence intensity of the macrocycle 3 upon gradual addition of trinitrotoluene and exhibits significant fluorescence quenching response only for nitroaromatic compounds compared to various other aromatic compounds tested.

Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

Effect of thermal annealing on the dielectric properties of KTiOPO4 single crystals

Dielectric properties of potassium titanyl phosphate have been investigated as a function of thickness and frequency, as well as annealing treatment under various atmospheres. The low frequency dielectric constant of KTP crystals is shown to depend upon the sample thickness, and this feature is attributed to the existence of surface layers. The frequency-dependent dielectric response of KTP exhibits a non-Debye type relaxation, with a distribution of relaxation times. The dielectric behavior of KTP samples annealed in various atmospheres shows that the low frequency dielectric constant is influenced by the contribution from the space charge layers. Prolonged annealing of the samples leads to a surface degradation, resulting in the formation of a surface layer of lower dielectric constant. This surface degradation is least when annealed in the presence of dry oxygen. From the analysis of the dielectric data using complex electric modulus, alpha(m) has been evaluated for the virgin and annealed samples. (C) 1996 American Institute of Physics.