Liquid metal enabled pump

Small-scale pumps will be the heartbeat of many future micro/nanoscale platforms. However, the integration of small-scale pumps is presently hampered by limited flow rate with respect to the input power, and their rather complicated fabrication processes. These issues arise as many conventional pumping effects require intricate moving elements. Here, we demonstrate a system that we call the liquid metal enabled pump, for driving a range of liquids without mechanical moving parts, upon the application of modest electric field. This pump incorporates a droplet of liquid metal, which induces liquid flow at high flow rates, yet with exceptionally low power consumption by electrowetting/deelectrowetting at the metal surface. We present theory explaining this pumping mechanism and show that the operation is fundamentally different from other existing pumps. The presented liquid metal enabled pump is both efficient and simple, and thus has the potential to fundamentally advance the field of microfluidics.

Smart Inter-Phase Switching of Residential Loads in Low Voltage Distribution Feeders

In order to dynamically reduce voltage unbalance along a low voltage distribution feeder, a smart residential load transfer system is discussed. In this scheme, residential loads can be transferred from one phase to another to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch and a controller. The master controller, installed at the transformer, observes the power consumption in each house and will determine which house(s) should be transferred from an initially connected phase to another in order to keep the voltage unbalance minimum. The performance of the smart load transfer scheme is demonstrated by simulations.

Optimal distributed generation placement in radial distribution systems

Distributed generation (DG) resources are commonly used in the electric systems to obtain minimum line losses, as one of the benefits of DG, in radial distribution systems. Studies have shown the importance of appropriate selection of location and size of DGs. This paper proposes an analytical method for solving optimal distributed generation placement (ODGP) problem to minimize line losses in radial distribution systems using loss sensitivity factor (LSF) based on bus-injection to branch-current (BIBC) matrix. The proposed method is formulated and tested on 12 and 34 bus radial distribution systems. The classical grid search algorithm based on successive load flows is employed to validate the results. The main advantages of the proposed method as compared with the other conventional methods are the robustness and no need to calculate and invert large admittance or Jacobian matrices. Therefore, the simulation time and the amount of computer memory, required for processing data especially for the large systems, decreases.

Motor controller simulation and embedded implementation for a blood pump

This study was a step forward in modeling, simulation and microcontroller implementation of a high performance control algorithm for the motor of a blood pump. The rotor angle is sensed using three Hall effect sensors and an algorithm is developed to obtain better angular resolution from the three signals for better discrete-time updates of the controller. The performance of the system was evaluated in terms of actual and reference speeds, stator currents and power consumption over a range of reference speeds up to 4000 revolutions per minute. The use of fewer low cost Hall effect sensors compared to expensive high resolution sensors could reduce the cost of blood pumps for total artificial hearts.

Recent progress in fluorescent blue light-emitting materials

Organic light emitting diodes (OLEDs), as an emerging technology for display and solid state lighting application, have many advantages including self-emission, lightweight, flexibility, low driving voltage, low power consumption, and low production cost. With the advancement of light emitting materials development and device architecture optimization, mobile phones and televisions based on OLED technology are already in the market. However, to obtain efficient, stable and pure blue emission than producing lower-energy colors is still one of the important subjects of these challenges. Full color and pure white light can be achieved only having stable blue emitting materials. To address this issue, significant effort has been devoted to develop novel blue light emitting materials in the past decade aiming at further improving device efficiency, color quality of emission light, and device lifetime. This review focuses on recent efforts of synthesis and device performance of small molecules, oligomers and polymers for blue emission of organic electroluminescent devices.

Engineering thin film semiconductor gas sensors to increase sensitivity and decrease operation temperature

Thin film nanostructured gas sensors typically operate at temperatures above 400°C, but lower temperature operation is highly desirable, especially for remote area field sensing as this reduces significantly power consumption. We have investigated a range of sensor materials based on both pure and doped tungsten oxide (mainly focusing on Fe-doping), deposited using both thermal evaporation and electron-beam evaporation, and using a variety of post-deposition annealing. The films show excellent sensitivity at operating temperatures as low as 150°C for detection of NO2. There is a definite relationship between the sensitivity and the crystallinity and nanostructure obtained through the deposition and heat treatment processes, as well as variations in the conductivity caused both by doping and heat treatmetn. The ultimate goal of this work is to control the sensing properties, including selectivity to specific gases through the engineering of the electronic properties and the nanostructure of the films.

Real-time price based home energy management scheduler

With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.

Surface engineering of reduced graphene oxide for controllable ambipolar flash memories

Tunable charge-trapping behaviors including unipolar charge trapping of one type of charge carrier and ambipolar trapping of both electrons and holes in a complementary manner is highly desirable for low power consumption multibit flash memory design. Here, we adopt a strategy of tuning the Fermi level of reduced graphene oxide (rGO) through self-assembled monolayer (SAM) functionalization and form p-type and n-type doped rGO with a wide range of manipulation on work function. The functionalized rGO can act as charge-trapping layer in ambipolar flash memories, and a dramatic transition of charging behavior from unipolar trapping of electrons to ambipolar trapping and eventually to unipolar trapping of holes was achieved. Adjustable hole/electron injection barriers induce controllable Vth shift in the memory transistor after programming operation. Finally, we transfer the ambipolar memory on flexible substrates and study their charge-trapping properties at various bending cycles. The SAM-functionalized rGO can be a promising candidate for next-generation nonvolatile memories.

Measurement of actual efficacy of compact fluorescent lamps (CFLs)

The use of compact fluorescent lamps (CFLs) in domestic residences has increased rapidly due to their higher energy efficiency and longer life expectancy when compared with traditional incandescent light bulbs. Through measurement of illuminance, actual power and apparent power, the actual efficacy and associated power factor of CFLs are studied in this paper. It is found that for an individual CFL, although its power consumption and lighting output (i.e. luminous flux) may be higher or lower than the stated values provided by the lighting manufacturers, the actual efficacy would most likely be equal to or better than the efficacy calculated from the given rated power and lumen from the manufacturers. The typical power factor for CFLs was 0.63.

Modelling milling train performance

This paper describes recent updates to a milling train extraction model used to assess and predict the performance of a milling train. An extension was made to the milling unit model for the bagasse mills to replace the imbibition coefficient with crushing factor and mixing efficiency. New empirical relationships for reabsorption factor, imbibition coefficient, crushing factor, mixing efficiency and purity ratio were developed. The new empirical relationships were tested against factory measurements and previous model predictions. The updated model has been implemented in the SysCAD process modelling software. New additions to the model implementation include: a shredder model to assess or predict cane preparation, mill and shredder drives for power consumption and an updated imbibition control system to add allow water to be added to intermediate mills.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

Non-linear regression model for spatial variation in precipitation chemistry for South India

Chemical composition of rainwater changes from sea to inland under the influence of several major factors - topographic location of area, its distance from sea, annual rainfall. A model is developed here to quantify the variation in precipitation chemistry under the influence of inland distance and rainfall amount. Various sites in India categorized as 'urban', 'suburban' and 'rural' have been considered for model development. pH, HCO3, NO3 and Mg do not change much from coast to inland while, SO4 and Ca change is subjected to local emissions. Cl and Na originate solely from sea salinity and are the chemistry parameters in the model. Non-linear multiple regressions performed for the various categories revealed that both rainfall amount and precipitation chemistry obeyed a power law reduction with distance from sea. Cl and Na decrease rapidly for the first 100 km distance from sea, then decrease marginally for the next 100 km, and later stabilize. Regression parameters estimated for different cases were found to be consistent (R-2 similar to 0.8). Variation in one of the parameters accounted for urbanization. Model was validated using data points from the southern peninsular region of the country. Estimates are found to be within 99.9% confidence interval. Finally, this relationship between the three parameters - rainfall amount, coastline distance, and concentration (in terms of Cl and Na) was validated with experiments conducted in a small experimental watershed in the south-west India. Chemistry estimated using the model was in good correlation with observed values with a relative error of similar to 5%. Monthly variation in the chemistry is predicted from a downscaling model and then compared with the observed data. Hence, the model developed for rain chemistry is useful in estimating the concentrations at different spatio-temporal scales and is especially applicable for south-west region of India. (C) 2008 Elsevier Ltd. All rights reserved.

A low cost demagnetizer with controllable cycle and adjustable level

Demagnetization to zero remanent value or to a predetermined value is of interest to magnet manufacturers and material users. Conventional methods of demagnetization using a varying alternating demagnetizing field, under a damped oscillatory or conveyor system, result in either high cost for demagnetization or large power dissipation. A simple technique using thyristors is presented for demagnetizing the material. Power consumption is mainly in the first two half-cycles of applied voltage. Hence power dissipation is very much reduced. An optimum value calculation for a thyristor triggering angle for demagnetizing high coercive materials is also presented.

Middleware for Mobile Sensing Applications in Urban Environments

Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.

Integrated CMOS Gas Sensors

We present a low power gas sensor system on CMOS platform consisting of micromachined polysilicon microheater, temperature controller circuit, resistance readout circuit and SnO2 transducer film. The design criteria for different building blocks of the system is elaborated The microheaters are optimized for temperature uniformity as well as static and dynamic response. The electrical equivalent model for the microheater is derived by extracting thermal and mechanical poles through extensive laser doppler vibrometer measurements. The temperature controller and readout circuit are realized on 130nm CMOS technology The temperature controller re-uses the heater as a temperature sensor and controls the duty cycle of the waveform driving the gate of the power MOSFET which supplies heater current. The readout circuit, with subthreshold operation of the MOSFETs, is based oil resistance to time period conversion followed by frequency to digital converter Subthreshold operatin of MOSFETs coupled with sub-ranging technique, achieves ultra low power consumption with more than five orders of magnitude dynamic range RF sputtered SnO2 film is optimized for its microstructure to achive high sensitivity to sense LPG gas.