Architectures for Silicon Nanoelectronics and Beyond

Although nanoelectronics won't replace CMOS for some time, research is needed now to develop the architectures, methods, and tools to maximally leverage nanoscale devices and terascale capacity. Addressing the complementary architectural and system issues involved requires greater collaboration at all levels. The effective use of nanotechnology calls for total system solutions     

Preparation,characterization and in vitro drug release properties of polytrimethylene carbonate/polyadipic anhydride blend microspheres

Polyadipic anhydride (PAA), an aliphatic polyanhydride, and polytrimethylene carbonate (PTMC), an aliphatic polycarbonate, were synthesized via ring opening polymerization of oxepan‐2,7‐dione and melt‐condensation of trimethylene carbonate (1,3 dioxan‐2‐one), respectively. PTMC–PAA blend microspheres containing different ratios of buprenorphine HCl (2, 5, and 10%) were prepared by an oil‐in‐oil emulsion solvent removal method. Microspheres with different ratios of PTMC–PAA (85/15, 70/30, and 55/45) containing 5% buprenorphine HCl were prepared. Microspheres were spherical with visible cracks and pores on the surface. The average particle size of microspheres was around 200 μm for all microspheres. Drug loading efficiency of PTMC–PAA microspheres (85/15, 70/30, and 55/45) was 97.2, 95.2, and 70.2%, respectively. With the increase in the PTMC ratio, the melting point and the enthalpy of melting were both decreased. The mechanism for drug release from PTMC–PAA blend microspheres were generally a combination of drug diffusion through polymers and biodegradation of the polymers. In first three days, the release from microspheres followed zero order kinetics and was dependent on the PAA content. After three days the drug release from microspheres followed first order kinetics. In conclusion it was demonstrated that buprenorphine HCl release from microspheres could be successfully controlled by using different ratios of PTMC–PAA blends. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2377–2383, 2006     

Speeding up learning automata based multi agent systems using the concepts of stigmergy and entropy

Learning automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms and are able to control the stochastic games. In this paper, the concepts of stigmergy and entropy are imported into learning automata based multi-agent systems with the purpose of providing a simple framework for interaction and coordination in multi-agent systems and speeding up the learning process. The multi-agent system considered in this paper is designed to find optimal policies in Markov games. We consider several dummy agents that walk around in the states of the environment, make local learning automaton active, and bring information so that the involved learning automaton can update their local state. The entropy of the probability vector for the learning automata of the next state is used to determine reward or penalty for the actions of learning automata. The experimental results have shown that in terms of the speed of reaching the optimal policy, the proposed algorithm has better learning performance than other learning algorithms.     

Factored Edge-Valued Binary Decision Diagrams

Factored Edge-Valued Binary Decision Diagrams form an extension to Edge-Valued Binary Decision Diagrams. By associating both an additive and a multiplicative weight with the edges, FEVBDDs can be used to represent a wider range of functions concisely. As a result, the computational complexity for certain operations can be significantly reduced compared to EVBDDs. Additionally, the introduction of multiplicative edge weights allows us to directly represent the so-called complement edges which are used in OBDDs, thus providing a one to one mapping of all OBDDs to FEVBDDs. Applications such as integer linear programming and logic verification that have been proposed for EVBDDs also benefit from the extension. We also present a complete matrix package based on FEVBDDs and apply the package to the problem of solving the Chapman-Kolmogorov equations.     

Multiscale analysis of viscoelastic laminated composite plates using generalized differential quadrature

In this paper, a laminated composite plate is analyzed using a multiscale method. At first, material properties of a lamina are obtained using an analytical micromechanical approach called simplified unit cell method (SUCM), and then in structural level, the generalized differential quadrature method (GDQM) is used to analyze a laminated composite plate. By means of the Boltzmann superposition principle, the viscoelastic behavior of the matrix is obtained. The Prony series is considered to define the compliance of matrix. To verify the results, graphiteT300/epoxy5208 composite material is analyzed and the results are compared with existing experimental data. The multiscale algorithm includes obtaining overall properties of the composite by SUCM; then, these properties are used to define the bending stiffness. Governing equations of motion of laminated composite plate are solved via GDQM and Newton–Raphson method. Variations of stresses and displacements versus time and volume fraction of the fibers are shown for laminated composite plates with different boundary conditions.     

A modified thermodynamic insight to deliquescence of a void‐containing nanocrystal confirmed by MD simulation

Existence of voids in crystalline structures can affect their physical and chemical properties considerably. When the size of the crystal reaches to nanoscale, experimental determination of its void fraction is difficult. In this work, a molecular dynamics approach is introduced to find equilibrium void fractions of a simple cubic (CsCl) and fcc (KCl) nanocrystals by determination of their deliquescence relative humidity (DRH) for different sizes and void fractions and extrapolation of the results to the bulk limit. To confirm the simulation results, the size dependency of DRH to the nanoparticle size was studied thermodynamically by inclusion of size‐dependent density of water nanodroplet which leads to a simple homographic equation. This method proposes the equilibrium void percents of CsCl and KCl nanoparticles to be 10 and 15%, respectively, which are obtained by extrapolation of the results to the bulk limit. The success of obtained Möbius function was also confirmed by fitting it to experimental data for deliquescence of NaCl nanoparticles which implies the importance of considering density of water nanodroplet as a size dependent quantity. Also, using the mentioned thermodynamic approach, void dependency of deliquescence for the nanoparticles was found to be as a quasi‐linear trend which is compatible with the simulation results. It is noticeable that the approach used this work for determination of equilibrium void fraction is only valid if the utilized force fields are accurate. © 2016 American Institute of Chemical Engineers AIChE J, 62: 4066–4077, 2016     

Analytical wide-band modeling of high frequency resistance in integrated spiral inductors

For integrated spiral inductor synthesis, designers and design automation tools require efficient modeling techniques during the initial design space exploration process. In this paper, we introduce an analytical frequency-dependent resistance model for integrated spiral inductors. Based on our resistance formulation, we have developed a systematic technique for creating wide-band circuit models for accurate time domain simulation. The analytical resistance model provides a fast alternative to field solver-based approaches with typical errors of less than 2.6 percent while surpassing the accuracy of several other analytical modeling techniques by an order of magnitude. Furthermore, the wide-band circuit generation technique captures the frequency-dependent resistance of the inductor with typical errors of less than 3.2 percent.     

Parasitic-aware analytical modeling of integrated CMOS inductively degenerated narrow-band low noise amplifiers

In this paper, we present an analytical modeling methodology for fully integrated inductively-degenerated CMOS narrow-band cascode Low Noise Amplifiers (LNA) that captures short channel transistor effects to enable rapid design space exploration in current and future process technologies. The modeling methodology captures the impact of parasitics on passive components, ESD-protection structures, and devices to accurately predict both impedance matching and noise figure. Our modeling is suitable for numerical optimization and fully automated synthesis for LNAs. The results indicate that the methodology models ESD-protected LNA circuits with 47.9% better accuracy in noise figure when compared with several current analytical modeling techniques with four orders of magnitude improvement in simulation time over circuit-level simulation. Given its speed and accuracy, the analytical modeling methodology is well-suited for design space exploration.