Quantum spin models with exact dimer ground states

Inspired by the exact solution of the Majumdar-Ghosh model, a family of one-dimensional, translationally invariant spin Hamiltonians is constructed. The exchange coupling in these models is antiferromagnetic, and decreases linearly with the separation between the spins. The coupling becomes identically zero beyond a certain distance. It is rigorously proved that the dimer configuration is an exact, superstable ground-state configuration of all the members of the family on a periodic chain. The ground state is twofold degenerate, and there exists an energy gap above the ground state. The Majumdar-Ghosh Hamiltonian with a twofold degenerate dimer ground state is just the first member of the family. The scheme of construction is generalized to two and three dimensions, and illustrated with the help of some concrete examples. The first member in two dimensions is the Shastry-Sutherland model. Many of these models have exponentially degenerate, exact dimer ground states.

Study of the dynamics of protein folding through minimalistic models

Starting with the Levinthal paradox, a brief introduction to the protein folding problem is presented. The existing theories of protein folding, including the folding funnel scenario, are discussed. After briefly discussing different simulation studies of model proteins, we discuss our recent work on the dynamics of folding of the model HP-36 (the chicken villin headpiece) protein by using a simplified hydropathy scale. Special attention has been paid to the statics and dynamics of contact formation among the hydrophobic residues. The results obtained from this simple model appear to be surprisingly similar to several features observed in the folding of real proteins. The account concludes with a discussion of future problems.

Ternary copper(II) complexes of thiosemicarbazones and heterocyclic bases showing N3OS coordination as models for the type-2 centers of copper monooxygenases

Six ternary copper(II) complexes of general formulation [CuLB] (1-6), where L is dianionic ONS-donor thiosemicarbazones derived from the condensation of salicylaldehyde with thiosemicarbazides and B is NN-donor heterocyclic bases like 2,2'-bipyridine, 1,10-phenanthroline and 2,9-dimethyl-1,10-phenanthroline, are prepared from a reaction of copper(II) acetate hydrate with the heterocyclic base (B) and the thiosemicarbazone (H2L) in MeOH, and structurally characterized by X-ray diffraction technique. Crystal structures of the complexes display a distorted square-pyramidal (4 + 1) coordination geometry having the ONS-donor thiosemicarbazone bonded at the basal plane. The chelating heterocyclic bases exhibit axial-equatorial mode of bonding. The complexes are one-electron paramagnetic and they show axial X-band EPR spectra in DMF-toluene glass at 77 K giving g(parallel to)(A(parallel to)) and g(perpendicular to) values of similar to2.2 (175 x 10(-4) cm(-1)) and similar to2.0 indicating a {d(x2-y2)}(1) ground state. The complexes show a d-d band near 570 nm and a charge transfer band near 400 nm in DMF. The complexes are redox active and exhibit a quasireversible Cu(II)-Cu(I) couple in DMF-0.1 M tetrabutylammonium perchlorate near 0.1 V vs. SCE. They are catalytically active in the oxidation of ascorbic acid in presence of dioxygen. The complexes with a CuN3OS coordination model the ascorbate oxidation property of dopamine beta-hydroxylase and peptidylglycine a-hydroxylating monooxygeanase. (C) 2003 Elsevier Science B.V. All rights reserved.

A Novel VSI- and CSI-Fed Dual Stator Induction Motor Drive Topology for Medium-Voltage Drive Applications

A new configuration is proposed for high-power induction motor drives. The induction machine is provided with two three-phase stator windings with their axes in line. One winding is designed for higher voltage and is meant to handle the main (active) power. The second winding is designed for lower voltage and is meant to carry the excitation (reactive) power. The excitation winding is powered by an insulated-gate-bipolar-transistor-based voltage source inverter with an output filter. The power winding is fed by a load-commutated current source inverter. The commutation of thyristors in the load-commutated inverter (LCI) is achieved by injecting the required leading reactive power from the excitation inverter. The MMF harmonics due to the LCI current are also cancelled out by injecting a suitable compensating component from the excitation inverter, so that the electromagnetic torque of the machine is smooth. Results from a prototype drive are presented to demonstrate the concept.

A Seven-Level Inverter Topology for Induction Motor Drive Using Two-Level Inverters and Floating Capacitor Fed H-Bridges

A multilevel inverter topology for seven-level space vector generation is proposed in this paper. In this topology, the seven-level structure is realized using two conventional two-level inverters and six capacitor-fed H-bridge cells. It needs only two isolated dc-voltage sources of voltage rating V(dc)/2 where V(dc) is the dc voltage magnitude required by the conventional neutral point clamped (NPC) seven-level topology. The proposed topology is capable of maintaining the H-bridge capacitor voltages at the required level of V(dc)/6 under all operating conditions, covering the entire linear modulation and overmodulation regions, by making use of the switching state redundancies. In the event of any switch failure in H-bridges, this inverter can operate in three-level mode, a feature that enhances the reliability of the drive system. The two-level inverters, which operate at a higher voltage level of V(dc)/2, switch less compared to the H-bridges, which operate at a lower voltage level of V(dc)/6, resulting in switching loss reduction. The experimental verification of the proposed topology is carried out for the entire modulation range, under steady state as well as transient conditions.

Voltage and Temperature Scalable Standard Cell Leakage Models Based on Stacks for Statistical Leakage Characterization

With extensive use of dynamic voltage scaling (DVS) there is increasing need for voltage scalable models. Similarly, leakage being very sensitive to temperature motivates the need for a temperature scalable model as well. We characterize standard cell libraries for statistical leakage analysis based on models for transistor stacks. Modeling stacks has the advantage of using a single model across many gates there by reducing the number of models that need to be characterized. Our experiments on 15 different gates show that we needed only 23 models to predict the leakage across 126 input vector combinations. We investigate the use of neural networks for the combined PVT model, for the stacks, which can capture the effect of inter die, intra gate variations, supply voltage(0.6-1.2 V) and temperature (0 - 100degC) on leakage. Results show that neural network based stack models can predict the PDF of leakage current across supply voltage and temperature accurately with the average error in mean being less than 2% and that in standard deviation being less than 5% across a range of voltage, temperature.

Voltage and Temperature Scalable Gate Delay and Slew Models Including Intra-Gate Variations

We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

Voltage and Temperature Scalable Gate Delay and Slew Models Including Intra-Gate Variations

We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

A comparative study of ordinary kriging and support vector machine models for the spatial variability of rock depth in Bangalore

In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 sq.km. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, ordinary kriging and Support Vector Machine (SVM) models have been developed. In ordinary kriging, the knowledge of the semivariogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of Bangalore, where field measurements are not available. A cross validation (Q1 and Q2) analysis is also done for the developed ordinary kriging model. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing e-insensitive loss function has been used to predict the reduced level of rock from a large set of data. A comparison between ordinary kriging and SVM model demonstrates that the SVM is superior to ordinary kriging in predicting rock depth.

Topology Optimization of Micromachined Structures with the Manufacturing Constraints of KOH Etching of (110) Silicon

The focus of this paper is on designing useful compliant micro-mechanisms of high-aspect-ratio which can be microfabricated by the cost-effective wet etching of (110) orientation silicon (Si) wafers. Wet etching of (110) Si imposes constraints on the geometry of the realized mechanisms because it allows only etch-through in the form of slots parallel to the wafer's flat with a certain minimum length. In this paper, we incorporate this constraint in the topology optimization and obtain compliant designs that meet the specifications on the desired motion for given input forces. Using this design technique and wet etching, we show that we can realize high-aspect-ratio compliant micro-mechanisms. For a (110) Si wafer of 250 µm thickness, the minimum length of the etch opening to get a slot is found to be 866 µm. The minimum achievable width of the slot is limited by the resolution of the lithography process and this can be a very small value. This is studied by conducting trials with different mask layouts on a (110) Si wafer. These constraints are taken care of by using a suitable design parameterization rather than by imposing the constraints explicitly. Topology optimization, as is well known, gives designs using only the essential design specifications. In this work, we show that our technique also gives manufacturable mechanism designs along with lithography mask layouts. Some designs obtained are transferred to lithography masks and mechanisms are fabricated on (110) Si wafers.