Liquid-drop model for the surface energy of nanoparticles

Based on the liquid-drop model, we have evaluated the Tolman length and surface energy of nanoparticles for different elements and compared with other theoretical models as well as the available simulated data. The predictions of the model show good agreement with the simulated results. Like the cohesive energy and melting temperature, the size-dependency of surface energy is also shape-dependent. (c) 2012 Elsevier B.V. All rights reserved.

Carrier concentration dependence of donor activation energy in n-type GaN epilayers grown on Si (111) by plasma-assisted MBE

The n-type GaN layers were grown by plasma-assisted MBE and either intentionally doped with Si or unintentionally doped. The optical characteristics of a donor level in Si-doped, GaN were studied in terms of photoluminescence (PL) spectroscopy as a function of electron concentration. Temperature dependent PL measurements allowed us to estimate the activation energy of a Si-related donor from temperature-induced decay of PL intensity. PL peak positions, full width at half maximum of PL and activation energies are found to be proportional to the cube root of carrier density. The involvement of donor levels is supported by the temperature-dependent electron concentration measurements. (C) 2012 Elsevier Ltd. All rights reserved.

Realization of thermally durable close-packed 2D gold nanoparticle arrays using self-assembly and plasma etching

Realization of thermally and chemically durable, ordered gold nanostructures using bottom-up self-assembly techniques are essential for applications in a wide range of areas including catalysis, energy generation, and sensing. Herein, we describe a modular process for realizing uniform arrays of gold nanoparticles, with interparticle spacings of 2 nm and above, by using RF plasma etching to remove ligands from self-assembled arrays of ligand-coated gold nanoparticles. Both nanoscale imaging and macroscale spectroscopic characterization techniques were used to determine the optimal conditions for plasma etching, namely RF power, operating pressure, duration of treatment, and type of gas. We then studied the effect of nanoparticle size, interparticle spacing, and type of substrate on the thermal durability of plasma-treated and untreated nanoparticle arrays. Plasma-treated arrays showed enhanced chemical and thermal durability, on account of the removal of ligands. To illustrate the application potential of the developed process, robust SERS (surface-enhanced Raman scattering) substrates were formed using plasma-treated arrays of silver-coated gold nanoparticles that had a silicon wafer or photopaper as the underlying support. The measured value of the average SERS enhancement factor (2 x 10(5)) was quantitatively reproducible on both silicon and paper substrates. The silicon substrates gave quantitatively reproducible results even after thermal annealing. The paper-based SERS substrate was also used to swab and detect probe molecules deposited on a solid surface.

Criticality guided energy aware speculation for speculative multithreaded processors

Unending quest for performance improvement coupled with the advancements in integrated circuit technology have led to the development of new architectural paradigm. Speculative multithreaded architecture (SpMT) philosophy relies on aggressive speculative execution for improved performance. However, aggressive speculative execution comes with a mixed flavor of improving performance, when successful, and adversely affecting the energy consumption (and performance) because of useless computation in the event of mis-speculation. Dynamic instruction criticality information can be usefully applied to control and guide such an aggressive speculative execution. In this paper, we present a model of micro-execution for SpMT architecture that we have developed to determine the dynamic instruction criticality. We have also developed two novel techniques utilizing the criticality information namely delaying the non-critical loads and the criticality based thread-prediction for reducing useless computations and energy consumption. Experimental results showing break-up of critical instructions and effectiveness of proposed techniques in reducing energy consumption are presented in the context of multiscalar processor that implements SpMT architecture. Our experiments show 17.7% and 11.6% reduction in dynamic energy for criticality based thread prediction and criticality based delayed load scheme respectively while the improvement in dynamic energy delay product is 13.9% and 5.5%, respectively. (c) 2012 Published by Elsevier B.V.