High-performance graphene-based supercapacitors made by a scalable blade-coating approach

Graphene oxide (GO) sheets can form liquid crystals (LCs) in their aqueous dispersions that are more viscous with a stronger LC feature. In this work we combine the viscous LC-GO solution with the blade-coating technique to make GO films, for constructing graphene-based supercapacitors in a scalable way. Reduced GO (rGO) films are prepared by wet chemical methods, using either hydrazine (HZ) or hydroiodic acid (HI). Solid-state supercapacitors with rGO films as electrodes and highly conductive carbon nanotube films as current collectors are fabricated and the capacitive properties of different rGO films are compared. It is found that the HZ-rGO film is superior to the HI-rGO film in achieving high capacitance, owing to the 3D structure of graphene sheets in the electrode. Compared to gelled electrolyte, the use of liquid electrolyte (H2SO4) can further increase the capacitance to 265 F per gram (corresponding to 52 mF per cm2) of the HZ-rGO film.

Atomic layer-by-layer Co3O4/graphene composite for high performance lithium-ion batteries

An "atomic layer-by-layer" structure of Co3O4/graphene is developed as an anode material for lithium-ion batteries. Due to the atomic thickness of both the Co3O4 nanosheets and the graphene, the composite exhibits an ultrahigh specific capacity of 1134.4 mAh g-1 and an ultralong life up to 2000 cycles at 2.25 C, far beyond the performances of previously reported Co3O4/C composites.

Dual yolk-shell structure of carbon and silica-coated silicon for high-performance lithium-ion batteries

Silicon batteries have attracted much attention in recent years due to their high theoretical capacity, although a rapid capacity fade is normally observed, attributed mainly to volume expansion during lithiation. Here, we report for the first time successful synthesis of Si/void/SiO2/void/C nanostructures. The synthesis strategy only involves selective etching of SiO2 in Si/SiO2/C structures with hydrofluoric acid solution. Compared with reported results, such novel structures include a hard SiO2-coated layer, a conductive carbon-coated layer, and two internal void spaces. In the structures, the carbon can enhance conductivity, the SiO2 layer has mechanically strong qualities, and the two internal void spaces can confine and accommodate volume expansion of silicon during lithiation. Therefore, these specially designed dual yolk-shell structures exhibit a stable and high capacity of 956 mA h g−1 after 430 cycles with capacity retention of 83%, while the capacity of Si/C core-shell structures rapidly decreases in the first ten cycles under the same experimental conditions. The novel dual yolk-shell structures developed for Si can also be extended to other battery materials that undergo large volume changes.

A novel ionic diffusion strategy to fabricate high-performance anode-supported solid oxide fuel cells (SOFCs) with proton-conducting Y-doped BaZrO3 films

A stable Y-doped BaZrO3 electrolyte film, which showed a good performance in proton-conducting SOFCs, was successfully fabricated using a novel ionic diffusion strategy.

Process makes perfect: High-performance design creates healthy environments for high-performance learning

Considering the staggering benefits of high-performance schools, it seems an obvious choice to “go green.” High-performance schools offer an exceptionally cost-effective means to enhance student learning, using on average 33 percent less energy than conventionally designed schools, and provide substantial health gains, including reduced respiratory problems and absenteeism. According to the 2006 study, Greening America's Schools, Costs and Benefits, co-sponsored by the American Institute of Architects (AIA) and Capital E, a green building consulting firm, high-performance lighting is a key element of healthy learning environments, contributing to improved test scores, reduced off-task behavior, and higher achievement among students. Few argue this point more convincingly than architect Heinz Rudolf, of Portland-Oregon-based Boora Architects, who has designed sustainable schools for more than 80 school districts in Oregon, Washington, Colorado, and Wyoming, and has pioneered the high-performance school movement. Boora's recently completed project, the Baker Prairie Middle School in Canby, Oregon is one of the most sustainable K-12 facilities in the state, and illustrates Rudolf's progressive and research-intensive approach to school design.

HFinFET: A Scalable, High Performance, Low Leakage Hybrid n-Channel FET

In this letter, we propose the design and simulation study of a novel transistor, called HFinFET, which is a hybrid of an HEMT and a FinFET, to obtain excellent performance and good OFF-state control. Followed by the description of the design, 3-D device simulation has been performed to predict the characteristics of the device. The device has been benchmarked against published state of the art HEMT as well as planar and nonplanar Si n-MOSFET data of comparable gate length using standard benchmarking techniques.

High performance VLSI architecture design for H.264 CAVLC decoder

H.264 video standard achieves high quality video along with high data compression when compared to other existing video standards. H.264 uses context-based adaptive variable length coding (CAVLC) to code residual data in Baseline profile. In this paper we describe a novel architecture for CAVLC decoder including coeff-token decoder, level decoder total-zeros decoder and run-before decoder UMC library in 0.13 mu CMOS technology is used to synthesize the proposed design. The proposed design reduces chip area and improves critical path performance of CAVLC decoder in comparison with [1]. Macroblock level (including luma and chroma) pipeline processing for CAVLC is implemented with an average of 141 cycles (including pipeline buffering) per macroblock at 250MHz clock frequency. To compare our results with [1] clock frequency is constrained to 125MHz. The area required for the proposed architecture is 17586 gates, which is 22.1% improvement in comparison to [1]. We obtain a throughput of 1.73 * 10(6) macroblocks/second, which is 28% higher than that reported in [1]. The proposed design meets the processing requirement of 1080HD [5] video at 30frames/seconds.

Design and realization of high-performance wave-pipelined 8×8 b multiplier in CMOS technology

Wave pipelining is a design technique for increasing the throughput of a digital circuit or system without introducing pipelining registers between adjacent combinational logic blocks in the circuit/system. However, this requires balancing of the delays along all the paths from the input to the output which comes the way of its implementation. Static CMOS is inherently susceptible to delay variation with input data, and hence, receives a low priority for wave pipelined digital design. On the other hand, ECL and CML, which are amenable to wave pipelining, lack the compactness and low power attributes of CMOS. In this paper we attempt to exploit wave pipelining in CMOS technology. We use a single generic building block in Normal Process Complementary Pass Transistor Logic (NPCPL), modeled after CPL, to achieve equal delay along all the propagation paths in the logic structure. An 8×8 b multiplier is designed using this logic in a 0.8 ?m technology. The carry-save multiplier architecture is modified suitably to support wave pipelining, viz., the logic depth of all the paths are made identical. The 1 mm×0.6 mm multiplier core supports a throughput of 400 MHz and dissipates a total power of 0.6 W. We develop simple enhancements to the NPCPL building blocks that allow the multiplier to sustain throughputs in excess of 600 MHz. The methodology can be extended to introduce wave pipelining in other circuits as well

A high performance scheme for EEG compression using a multichannel model

The amount of data contained in electroencephalogram (EEG) recordings is quite massive and this places constraints on bandwidth and storage. The requirement of online transmission of data needs a scheme that allows higher performance with lower computation. Single channel algorithms, when applied on multichannel EEG data fail to meet this requirement. While there have been many methods proposed for multichannel ECG compression, not much work appears to have been done in the area of multichannel EEG. compression. In this paper, we present an EEG compression algorithm based on a multichannel model, which gives higher performance compared to other algorithms. Simulations have been performed on both normal and pathological EEG data and it is observed that a high compression ratio with very large SNR is obtained in both cases. The reconstructed signals are found to match the original signals very closely, thus confirming that diagnostic information is being preserved during transmission.

Fabrication and evaluation of 450 F electrochemical redox supercapacitors using inexpensive and high-performance, polyaniline coated, stainless-steel electrodes

Redox supercapacitors using polyaniline (PANI) coated. stainless-steel (SS) electrodes have been assembled and characterized. PANI has been deposited on SS substrate by a potentiodynamic method from an acidic electrolyte which contains aniline monomer. By employing stacks of electrodes, each with a geometrical area of 24 cm(2), in acidic perchlorate electrolyte, a capacitance value of about 450 F has been obtained over a long cycle-life. Characterization studies have been carried out by galvanostatic charge-discharge cycling of the capacitors singly, as well as in series and parallel configurations. Various electrical parameters have been evaluated. Use of the capacitors in parallel with a battery for pulse-power loads. and also working of a toy fan connected to the charged capacitors have been demonstrated. A specific capacitance value of about 1300 F g(-1) of PANI has been obtained at a discharge power of about 0.5 kW kg(-1). This value is several times higher than those reported in the literature for PANI and is, perhaps, the highest value known for a capacitor material. The inexpensive SS substrate and the high-capacitance PANI are favorable factors for commercial exploitation. (C) 2002 Elsevier Science B.V. All rights reserved.

Potentiodynamically deposited polyaniline on stainless steel - Inexpensive, high-performance electrodes for electrochemical supercapacitors

Polyaniline (PANI) has been studied as an active material for electrochemical capacitors. Polymerization of aniline to PANI has been carried out potentiodynamically on a stainless steel (SS) substrate, instead of Pt-based substrates generally employed for this application. The PANI/SS electrodes have been evaluated by assembling symmetrical capacitors in NaClO(4) + HClO(4) mixed electrolyte and subjecting them to galvanostatic charge/discharge cycles between 0 and 0.75 V. The effect of substrate has been assessed by comparing the capacitance of PANI/SS and PANI/Pt electrodes. The capacitance of PANI/SS electrode is higher than that of PANI/Pt electrode by several times. The effect of sweep rate of potentiodynamic deposition of PANI/SS on capacitance has been investigated. At a power density of 0.5 kW kg(-1), a capacitance value of 815 F g(-1) of PANI is obtained for the deposition sweep rate of 200 mV s(-1). Increase in thickness of PANI on the SS substrate results in an increase in capacitance of PANI. This value of capacitance is the highest ever reported for any electrochemical capacitor material. Thus, in addition to a favorable economic aspect involved in using SS instead of Pt or Pt-based substrate, the advantage of higher capacitance of PANI has also been achieved. (C) 2002 The Electrochemical Society.

A Neuro-Adaptive Approach for Robust Control of High Performance Aircrafts with Parameter Inaccuracies

For high performance aircrafts, the flight control system needs to be quite effective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addition, the control system must also be sufficiently robust to cater to possible parameter variations. The primary aim of this paper is to enhance the robustness of the controller for a HPA using neuro-adaptive control design. Here the architecture employs a network of Gaussian Radial basis functions to adaptively compensate for the ignored system dynamics. A stable weight mechanism is determined using Lyapunov theory. The network construction and performance of the resulting controller are illustrated through simulations with a low-fidelity six –DOF model of F16 that is available in open literature.

Robustness Study of a Dynamic Inversion Control Law for a High Performance Aircraft

In the design of °ight control system modeling uncertainties in the form of param-eter variations is one of the major problems. It is even more critical for high performance aircrafts,since such aircrafts are purposefully designed unstable to enhance their performance (especially ma-neuverability). Hence the °ight control system needs to be quite e®ective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addi-tion, the control system must also be su±ciently robust to cater for possible parameter variations and inaccuracies . The primary aim of this paper is to carry out a robustness study of a dynamic inversion based nonlinear control design for a high performance aircraft, which has been developed recently [1].

Command Tracking in High Performance Aircrafts: A New Dynamic Inversion Design

This paper proposes a new straight forward technique based on dynamic inversion, which is applied for tracking the pilot commands in high performance aircrafts.Pilot commands assumed in longitudinal mode are normal acceleration and total velocity(while roll angle and lateral acceleration are maintained at zero). In lateral mode, roll rate and total velocity are used as pilot commands (while climb rate and lateral acceleration are maintained at zero). Ensuring zero lateral acceleration leads to a better turn co-ordination. A six degree-of-freedom model of F-16 aircraft is used for both control design as well as simulation studies. Promising results are obtained which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response and reduced control magnitude. Another advantage of this approach is that it leads to a significant reduction of tuning parameters in the control design process.

Model-following Neuro-adaptive approach for robust control of high performance aircrafts

Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.