Highly compressible behavior of polymer mediated three-dimensional network of graphene foam

The compressive behavior of graphene foam (GF) and its polymer (polydimethyl siloxane) (PDMS) infiltrated structure are presented. While GF showed an irreversible compressibility, the GF/PDMS structure revealed a highly reversible mechanical behavior up to many cycles of compression and also possesses a six times higher compressive strength. In addition, the strain rate demonstrated a negligible effect on both the maximum achieved stress and energy absorption in the GF/PDMS structure. The mechanical responses of both GF and GF/PDMS structure are compared with carbon nanotubes based cellular structure and its composite with PDMS, where GF/PDMS presented a dominant mechanical characteristic among other carbon based micro foam structures. Therefore, the improved mechanical properties of GF/PDMS suggest its potential for dampers, cushions, packaging, etc.

Mining Unit Tests for Discovery and Migration of Math APIs

Today's programming languages are supported by powerful third-party APIs. For a given application domain, it is common to have many competing APIs that provide similar functionality. Programmer productivity therefore depends heavily on the programmer's ability to discover suitable APIs both during an initial coding phase, as well as during software maintenance. The aim of this work is to support the discovery and migration of math APIs. Math APIs are at the heart of many application domains ranging from machine learning to scientific computations. Our approach, called MATHFINDER, combines executable specifications of mathematical computations with unit tests (operational specifications) of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code comprised of API methods to compute the expression by mining unit tests of the API methods. We present a sequential version of our unit test mining algorithm and also design a more scalable data-parallel version. We perform extensive evaluation of MATHFINDER (1) for API discovery, where math algorithms are to be implemented from scratch and (2) for API migration, where client programs utilizing a math API are to be migrated to another API. We evaluated the precision and recall of MATHFINDER on a diverse collection of math expressions, culled from algorithms used in a wide range of application areas such as control systems and structural dynamics. In a user study to evaluate the productivity gains obtained by using MATHFINDER for API discovery, the programmers who used MATHFINDER finished their programming tasks twice as fast as their counterparts who used the usual techniques like web and code search, IDE code completion, and manual inspection of library documentation. For the problem of API migration, as a case study, we used MATHFINDER to migrate Weka, a popular machine learning library. Overall, our evaluation shows that MATHFINDER is easy to use, provides highly precise results across several math APIs and application domains even with a small number of unit tests per method, and scales to large collections of unit tests.

An Expeditious Asymmetric Synthesis of the Polyketide Unit Present in HIV-Inhibitory Depsipeptides Aetheramide A and B

The enantioselective synthesis of the polyketide unit present in depsipeptides aetheramide A and B, which possess potent HIV-inhibitory activity, is accomplished from a chiral furyl carbinol.

Design of an Automated Dispenser Unit

This paper presents our work on developing an automated micro positioner and a low cost disposable dispenser module having a disposable dispenser core. The dispenser core is made up of Polydimethylsiloxane (PDMS). Once the user specifies the dispensing location in the Graphical User Interface (GUI), the movement of the micropositioner is automatic. The design, fabrication and characterization results of the dispenser module are also presented. The dispensing experiments are performed with Di-Ethanol Amine as the working reagent. The minimum dispensed volume achieved is about 4 nL.

A Time-based Low Voltage Body Temperature Monitoring Unit

A neonatal temperature monitoring system operating in subthreshold regime that utilizes time mode signal processing is presented. Resistance deviations in a thermistor due to temperature variations are converted to delay variations that are subsequently quantized by a Delay measurement unit (DMU). The DMU does away with the need for any analog circuitry and is synthesizable entirely from digital logic. An FPGA implementation of the system demonstrates the viability of employing time mode signal processing, and measured results show that temperature resolution better than 0.1 degrees C can be achieved using this approach.

Highly Dense ZnO Nanowires Grown on Graphene Foam for Ultraviolet Photodetection

Growth of highly dense ZnO nanowires (ZnO NWs) is demonstrated on three-dimensional graphene foam (GF) using resistive thermal evaporation technique. Photoresponse of the as-grown hybrid structure of ZnO NWs on GF (ZnO NWs/GF) is evaluated for ultraviolet (UV) detection. Excellent photoresponse with fast response and recovery times of 9.5 and 38 s with external quantum efficiency of 2490.8% is demonstrated at low illumination power density of 1.3 mW/cm(2). In addition, due to excellent charge carrier transport, mobility of graphene reduces the recombination rate of photogenerated charge carriers, hence the lifetime of photogenerated free charge carriers enhances in the photodetectors.

Tailored mechanical behavior of magnetic particles loaded carbon nanotube foam in presence of magnetic field

The compressive behavior of carbon nanotube (CNT) foam with an entangled microstructure has become an important research area due to its excellent energy absorption capability. This report presents a tailored mechanical behavior of CNT foam under an applied magnetic field when all CNTs in the foam are coated with magnetic nanoparticles. The presence of nanoparticles not only enhanced the stiffness of the foam to four times but also revealed a nonlinear variation in both the stress and energy absorption capability with the gradual increase of the magnetic field. Magnetization of both CNT and attached nanoparticles along the magnetic field direction are shown to play a crucial role in determining the dominant deformation mechanism.

Strategy for Obtaining Bimodal Bubble Size Distribution in Water Blown Polyurethane Foams

Polyurethane foams with multimodal cell distribution exhibit superior mechanical and thermal properties. A technique for generating bimodal bubble size distribution exists in the literature, but it uses supercritical conditions. In the present work, an alternative based on milder operating conditions is proposed. It is a modification of reaction injection molding (RIM), using reactants already seeded with bubbles. The number density of the seeds determines if two nucleating events can occur. A bimodal bubble size distribution is obtained when this happens A mathematical model is used to test this hypothesis by simulating water blown free rise polyurethane foams. The effects of initial concentration of bubbles, temperature of the reactants, and the weight fraction of water are studied. The study reveals that for certain concentrations of initial number of bubbles, when initial temperature and weight fraction of water are high, it is possible to obtain a second nucleation event, leading to bimodal bubble size distribution.

Tailored nitrogen dioxide sensing response of three-dimensional graphene foam

Ultralight and macroporous three-dimensional reduced graphene oxide (rGO) foams are prepared by lyophilization (freeze-drying) technique to avoid a conventional template method. This method allows tailoring the porosity of the foams by varying the weight percentages of graphene oxide dispersions in water. Three different rGO foams of 0.2, 0.5 and 1.0 wt% are used for NO2 sensing. Sensing response from the tailored structure of rGO is found to be directly related to the density. A maximum of 20% sensing response is observed for a higher porosity of the structure, better than the known results so far on graphene foams in the literature. (C) 2015 Elsevier B.V. All rights reserved.

Traveling waves in trimer granular lattice I: Bifurcation structure of traveling waves in the unit-cell model

Present paper is the first one in the series devoted to the dynamics of traveling waves emerging in the uncompressed, tri-atomic granular crystals. This work is primarily concerned with the dynamics of one-dimensional periodic granular trimer (tri-atomic) chains in the state of acoustic vacuum. Each unit cell consists of three spherical particles of different masses subject to periodic boundary conditions. Hertzian interaction law governs the mutual interaction of these particles. Under the assumption of zero pre-compression, this interaction is modeled as purely nonlinear, which means the absence of linear force component. The dynamics of such chains is governed by the two system parameters that scale the mass ratios between the particles of the unit cell. Such a system supports two different classes of periodic solutions namely the traveling and standing waves. The primary objective of the present study is the numerical analysis of the bifurcation structure of these solutions with emphasis on the dynamics of traveling waves. In fact, understanding of the bifurcation structure of the traveling wave solutions emerging in the unit-cell granular trimer is rather important and can shed light on the more complex nonlinear wave phenomena emerging in semi-infinite trimer chains. (c) 2016 Elsevier B.V. All rights reserved.