Dynamics of Diblock Copolymers in Dilute Solutions

We consider the dynamics of freely translating and rotating diblock (A-B), Gaussian copolymers, in dilute solutions. Using the multiple scattering technique, we have computed the diffusion and the friction coefficients D_AB and Zeta_AB, and the change Eta_AB in the viscosity of the solution as functions of x = N_A/N and t = l_B/l_A, where N_A, N are the number of segments of the A block and of the whole copolymer, respectively, and l_A, l_B are the Kuhn lengths of the A and B blocks. Specific regimes that maximize the efficiency of separation of copolymers with distinct "t" values, have been identified.Comment: 20 pages Revtex, 7 eps figures, needs epsf.tex and amssymb.sty, submitted to Macromolecule

A novel power optimized hybrid renewable energy system using neural computing and bee algorithm

With rapid depletion of non-renewable energy resources or the fossil fuels like coal, petroleum etc., there has been a significant shift in innovations towards exploiting and tapping of energy from renewable energy resources like sun, bio gas, wind etc., E Off late, there has been an increased research towards combined or hybrid integrated energy generation systems based on renewable resources like sun-wind, sun-biogas etc., These hybrid systems effectively address the past demerits observed in standalone systems which could provide substantial power only during specific periods and seasons. For example, solar power would be much reduced during the night time. Hence hybrid systems effectively counteract this issue as the lack of stability in one system is well compensated by the other. This research paper proposes an optimized hybrid PV-wind power generation system with optimization towards maximization of power generated from the system with the help of neural architecture and bee colony algorithm. The proposed system has been implemented and tested for a wide range of solar irradiances and wind velocities and maximum and stable power generation has been observed when compared to existing techniques

A novel power optimized hybrid renewable energy system using neural computing and bee algorithm

With rapid depletion of non-renewable energy resources or the fossil fuels like coal, petroleum etc., there has been a significant shift in innovations towards exploiting and tapping of energy from renewable energy resources like sun, bio gas, wind etc., E Off late, there has been an increased research towards combined or hybrid integrated energy generation systems based on renewable resources like sun-wind, sun-biogas etc., These hybrid systems effectively address the past demerits observed in standalone systems which could provide substantial power only during specific periods and seasons. For example, solar power would be much reduced during the night time. Hence hybrid systems effectively counteract this issue as the lack of stability in one system is well compensated by the other. This research paper proposes an optimized hybrid PV-wind power generation system with optimization towards maximization of power generated from the system with the help of neural architecture and bee colony algorithm. The proposed system has been implemented and tested for a wide range of solar irradiances and wind velocities and maximum and stable power generation has been observed when compared to existing techniques

Polymers pushing Polymers: Polymer Mixtures in Thermodynamic Equilibrium with a Pore

We investigate polymer partitioning from polymer mixtures into nanometer size cavities by formulating an equation of state for a binary polymer mixture assuming that only one (smaller) of the two polymer components can penetrate the cavity. Deriving the partitioning equilibrium equations and solving them numerically allows us to introduce the concept of "polymers-pushing-polymers" for the action of non-penetrating polymers on the partitioning of the penetrating polymers. Polymer partitioning into a pore even within a very simple model of a binary polymer mixture is shown to depend in a complicated way on the composition of the polymer mixture and/or the pore-penetration penalty. This can lead to enhanced as well as diminished partitioning, due to two separate energy scales that we analyse in detail.Comment: 10 pages, 6 figure

Electronic structure of strongly correlated d-wave superconductors

We study the electronic structure of a strongly correlated d-wave superconducting state. Combining a renormalized mean field theory with direct calculation of matrix elements, we obtain explicit analytical results for the nodal Fermi velocity, v_F, the Fermi wave vector, k_F, and the momentum distribution, n_k, as a function of hole doping in a Gutzwiller projected d-wave superconductor. We calculate the energy dispersion, E_k, and spectral weight of the Gutzwiller-Bogoliubov quasiparticles, and find that the spectral weight associated with the quasiparticle excitation at the antinodal point shows a non monotonic behavior as a function of doping. Results are compared to angle resolved photoemission spectroscopy (ARPES) of the high temperature superconductors.Comment: final version, comparison to experiments added, 4+ pages, 4 figure

A study on Vertigo – Evaluation of Bedside Tests and Aetiopathology.

Vertigo is defined as the ‘hallucination’ of movement, either of self (subjective) or the environment (objective). Usually the patient uses various terms (eg.) Bouncing, Oscillating, Staggering, Swimming, Twisting Rolling, Spinning, Rocking, Lightheadness, Imbalance, Floating, Fainting, Falling. For the most part they are benign but always there is the possibility that they signal the presence of an important neurological disorder. Diagnosis of the underlying disease demands that the complaint of vertigo be analyzed correctly, the nature of the disturbance of function being determined first and then its anatomic localization. A careful history and physical examination usually affords the basis for separating true vertigo from the dizziness of the anxious patient and from the other types of pseudo vertigo This study evaluates the vertigo patients based on history, examination and relevant investigations to establish the etiology for the vertigo. Benign paroxysmal positional vertigo (BPPV) was the commonest cause of vertigo in this study. 31 to 40 years had the highest incidence of vertigo in this study. Migranous vertigo was the common central cause of vertigo. Head thrust test was the most reliable bedside test. Dick Halpick’s and calorie test positive only in peripheral vertigo. All the bedside tests used in this study were very much significant for vertigo with the ‘P’ value of <0.001

Determining the underlying Fermi surface of strongly correlated superconductors

The notion of a Fermi surface (FS) is one of the most ingenious concepts developed by solid state physicists during the past century. It plays a central role in our understanding of interacting electron systems. Extraordinary efforts have been undertaken, both by experiment and by theory, to reveal the FS of the high temperature superconductors (HTSC), the most prominent strongly correlated superconductors. Here, we discuss some of the prevalent methods used to determine the FS and show that they lead generally to erroneous results close to half filling and at low temperatures, due to the large superconducting gap (pseudogap) below (above) the superconducting transition temperature. Our findings provide a perspective on the interplay between strong correlations and superconductivity and highlight the importance of strong coupling theories for the characterization as well as the determination of the underlying FS in ARPES experiments