Vertical graphene gas- and bio-sensors via catalyst-free, reactive plasma reforming of natural honey

A rapid reforming of natural honey exposed to reactive low-temperature Ar + H2 plasmas produced high-quality, ultra-thin vertical graphenes, without any metal catalyst or external heating. This transformation is only possible in the plasma and fails in similar thermal processes. The process is energy-efficient, environmentally benign, and is much cheaper than common synthesis methods based on purified hydrocarbon precursors. The graphenes retain the essential minerals of natural honey, feature reactive open edges and reliable gas- and bio-sensing performance.

Partial rectification of the plasmon-induced electrical tunnel current in discontinuous thin gold film at optical frequency

The effect of plasmonoscillations, induced by pulsed laserirradiation, on the DC tunnel current between islands in a discontinuous thin goldfilm is studied. The tunnel current is found to be strongly enhanced by partial rectification of the plasmon-induced AC tunnel currents flowing between adjacent gold islands. The DC tunnel current enhancement is found to increase approximately linearly with the laser intensity and the applied DC bias voltage. The experimental data can be well described by an electron tunnelling model which takes the plasmon-induced AC voltage into account. Thermal heating seems not to contribute to the tunnel current enhancement.

Highly NO2 sensitive caesium doped graphene oxide conductometric sensors

Here we report on the synthesis of caesium doped graphene oxide (GO-Cs) and its application to the development of a novel NO2 gas sensor. The GO, synthesized by oxidation of graphite through chemical treatment, was doped with Cs by thermal solid-state reaction. The samples, dispersed in DI water by sonication, have been drop-casted on standard interdigitated Pt electrodes. The response of both pristine and Cs doped GO to NO2 at room temperature is studied by varying the gas concentration. The developed GO-Cs sensor shows a higher response to NO2 than the pristine GO based sensor due to the oxygen functional groups. The detection limit measured with GO-Cs sensor is ≈90 ppb.

Investigation on bioactivity of titanium dioxide thin films fabricated by electron cyclotron resonance plasma aided pulsed laser deposition

Titanium dioxide thin films with a rutile crystallinite size around 20 nm were fabricated by pulsed laser deposition (PLD) aided with an electron cyclotron resonance (ECR) plasma. With annealing treatment, the crystal size of the rutile crystallinite increased to 100 nm. The apatite-forming ability of the films as deposited and after annealing was investigated in a kind of simulated body fluid with ion concentrations nearly equal to those of human blood plasma. The results indicate that ECR aided PLD is an effective way both to fabricate bioactive titanium dioxide thin films and to optimize the bioactivity of titanium dioxide, with both crystal size and defects of the film taken into account.

Enhancement of optical absorption in thin-film solar cells through the excitation of higher-order nanoparticle plasmon modes

Recent research in the rapidly emerging field of plasmonics has shown the potential to significantly enhance light trapping inside thin-film solar cells by using metallic nanoparticles. In this article it is demonstrated the plasmon enhancement of optical absorption in amorphous silicon solar cells by using silver nanoparticles. Based on the analysis of the higher-order surface plasmon modes, it is shown how spectral positions of the surface plasmons affect the plasmonic enhancement of thin-film solar cells. By using the predictive 3D modeling, we investigate the effect of the higher-order modes on that enhancement. Finally, we suggest how to maximize the light trapping and optical absorption in the thin-film cell by optimizing the nanoparticle array parameters, which in turn can be used to fine tune the corresponding surface plasmon modes.

Surface plasmon enhancement of optical absorption in thin-film silicon solar cells

Strong electromagnetic field enhancement that occurs under conditions of the surface plasmon excitation in metallic nanoparticles deposited on a semiconductor surface is a very efficient and promising tool for increasing the optical absorption within semiconductor solar cells and, hence, their photocurrent response. The enhancement of the optical absorption in thin-film silicon solar cells via the excitation of localized surface plasmons in spherical silver nanoparticles is investigated. Using the effective medium model, the effect of the nanoparticle size and the surface coverage on that enhancement is analyzed. The optimum configuration and the nanoparticle parameters leading to the maximum enhancement in the optical absorption and the photocurrent response in a single p-n junction silicon cell are obtained. The effect of coupling between the silicon layer and the surface plasmon fields on the efficiency of the above enhancement is quantified as well.

Excitation of surface plasmon-polariton waves at a semiconductor-metal interface

The excitation of surface plasmon-polariton waves propagating across an external magnetic field (Voigt geometry) in a semiconductor-metal structure by means of the attenuated total reflection method is investigated. The phase matching conditions for the surface waves excitation in the Kretchmann configuration are derived and analyzed. The effect of different nonlinearities on the excitation of the surface waves is studied as well.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

Thermal effect of plasmon oscillations on the tunnel current in gold nanoisland thin film at low laser intensity

The effect of plasmon oscillations on the DC tunnel current in a gold nanoisland thin film (GNITF) is investigated using low intensity P~1W/cm2 continuous wave lasers. While DC voltages (1–150 V) were applied to the GNITF, it was irradiated with lasers at different wavelengths (k¼473, 532, and 633 nm). Because of plasmon oscillations, the tunnel current increased. It is found that the tunnel current enhancement is mainly due to the thermal effect of plasmon oscillations rather than other plasmonic effects. The results are highly relevant to applications of plasmonic effects in opto-electronic devices.

Studying upper-limb kinematic using inertial sensors embedded in smartphones

Background: In recent years, there have been investigations concerning upper-limbs kinematics by various devices. The latest generation of smartphones often includes inertial sensors with subunits which can detect inertial kinematics. The use of smartphones is presented as a convenient and portable analysis method for studying kinematics in terms of angular mobility and linear acceleration Objective: The aim of this study was to study humerus kinematics through six physical properties that correspond to angular mobility and acceleration in the three axes of space, obtained by a smartphone. Methods: This cross-sectional study recruited healthy young adult subjects. Descriptive and anthropometric independent variables related to age, gender, weight, size, and BMI were included. Six physical properties were included corresponding to two dependent variables for each of three special axes: mobility angle (degrees) and lineal acceleration (meters/seconds2), which were obtained thought the inertial measurement sensor embedded in the iPhone4 smartphone equipped with three two elements for the detection of kinematic variables: a gyroscope and an accelerometer. Apple uses an LIS302DL accelerometer in the iPhone4. The application used to obtain kinematic data was xSensor Pro, Crossbow Technology, Inc., available at the Apple AppStore. The iPhone4 has storage capacity of 20MB. The data-sampling rate was set to 32 Hz, and the data for each analytical task was transmitted as email for analysis and postprocessing The iPhone4 was placed in the right half of the body of each subject located in the middle third of the humerus slightly posterior snugly secured by a neoprene fixation belt. Tasks were explained concisely and clearly. The beginning and the end were decided by a verbal order by the researcher. Participants were placed standing, starting from neutral position, performing the following analytical tasks: 180º right shoulder abduction (eight repetitions) and, after a break of about 3 minutes, 180º right shoulder flexion (eight repetitions). Both tasks were performed with the elbow extended, wrist in neutral position and the palmar area of the hand toward the midline at the beginning and end of the movement. Results: A total of 11 subjects (8 men, 3 woman) were measured, whose mean of age was 24.7 years (SD = 4.22 years) and their average BMI was 22.64 Kg/m2 (SD = 2.29 Kg/m2). The mean of angular mobility collected by the smartphone was bigger in pitch axis for flexion (= 157.28°, SD= 12.35°) and abduction (= 151.71°, SD= 9.70°). With regard to acceleration, the highest peak mean value was shown in the Y motion axis during flexion (= 19.5°/s2, SD = 0.8°/s2) and abduction (= 19.4°/s2, SD = 0.8°/s2). Also, descriptive graphics of analytical tasks performed were obtained. Conclusions: This study shows how humerus contributes to upper-limb motion and it identified movement patterns. Therefore, it supports smartphone as a useful device to analyze upper-limb kinematics. Thanks to this study it´s possible to develop a simple application that facilitates the evaluation of the patient.

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.

A motor controller using field oriented control and Hall effect rotor position sensors : simulation and implementation

A field oriented control (FOC) algorithm is simulated and implemented for use with a permanent magnet synchronous motor (PMSM). Rotor position is sensed using Hall effect switches on the stator because other hardware position sensors attached to the rotor may not be desirable or cost effective for certain applications. This places a limit on the resolution of position sensing – only a few Hall effect switches can be placed. In this simulation, three sensors are used and the position information is obtained at higher resolution by estimating it from the rotor dynamics, as shown in literature previously. This study compares the performance of the method with an incremental encoder using simulations. The FOC algorithm is implemented using Digital Motor Control (DMC) and IQ Texas Instruments libraries from a Simulink toolbox called Embedded Coder, and downloaded into a TI microcontroller (TMS320F28335) known as the Piccolo via Code Composer Studio (CCS).

Surface plasmon-enhanced zeolite catalysis under light irradiation and its correlation with molecular polarity of reactants

Enhanced catalytic performance of zeoltes via the plasmonic effect of gold nanoparticles has been discovered to be closely correlated with the molecular polarity of reactants. The intensified polarised electrostatic field of Na+ in NaY plays a critical role in stretching the C=O bond of aldehydes to improve the reaction rate.

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.