In this work, a PdNi thin film hydrogen gas sensor with integrated Pt thin film temperature sensor was designed and fabricated using the micro-electro-mechanical system (MEMS) process. The integrated sensors consist of two resistors: the former, based on Pt film, is used as a temperature sensor, while the latter had the function of hydrogen sensing and is based on PdNi alloy film. The temperature coefficient of resistance (TCR) in both devices was measured and the output response of the PdNi film hydrogen sensor was calibrated based on the temperature acquired by the Pt temperature sensor. The SiN layer was deposited on top of Pt film to inhibit the hydrogen diffusion and reduce consequent disturbance on temperature measurement. The TCR of the PdNi film and the Pt film was about 0.00122/K and 0.00217/K, respectively. The performances of the PdNi film hydrogen sensor were investigated with hydrogen concentrations from 0.3% to 3% on different temperatures from 294.7 to 302.2 K. With the measured temperature of the Pt resistor and the TCR of the PdNi film, the impact of the temperature on the performances of the PdNi film hydrogen sensor was reduced. The output response, response time and recovery time of the PdNi film hydrogen sensors under the hydrogen concentration of 0.5%, 1.0%, 1.5% and 2.0% were measured at 313 K. The output response of the PdNi thin film hydrogen sensors increased with increasing hydrogen concentration while the response time and recovery time decreased. A cycling test between pure nitrogen and 3% hydrogen concentration was performed at 313 K and PdNi thin film hydrogen sensor demonstrated great repeatability in the cycling test.
Hyperspectral scattering is a promising technique for nondestructive quality measurement of apple fruit, and extraction of the most useful information from the hyperspectral scattering data is critical for accurate assessment of fruit firmness and soluble solids content (SSC). In this article, a hierarchical evolutionary algorithm (HEA) approach coupled with subspace decomposition and partial least squares regression is proposed to select the optimal wavelengths from hyperspectral scattering profiles of `Golden Delicious' apples for predicting fruit firmness and SSC. Six hundred apples were tested in the experiment, 400 of which were used for calibration and the remaining 200 apples for validation. Seventeen optimal wavelengths were selected for firmness prediction, which nearly spanned the entire spectral range of 500 to 1000 nm, and 16 optimal wavelengths, all of which were above 600 nm, were selected in the SSC prediction model. The model using the 17 optimal wavelengths for predicting firmness yielded better results (r = 0.857, root mean square error of prediction or RMSEP = 6.2 N) than the full spectrum model (r = 0.848, RMSEP = 6.4 N). For predicting SSC, the model using the 16 optimal wavelengths also yielded better results (r = 0.822, RMSEP = 0.78%) than the full spectrum model (r = 0.802, RMSEP = 0.83%). The HEA approach provided an effective means for optimal wavelength selection and improved the prediction of firmness and SSC in apples compared with the approach using the full spectrum.
Abstract-A novel method for generating electromagnetic field with orbital angular momentum (OAM) and correspondingly a practical design based on conical horn antenna are proposed in this paper. The OAM modes of ±m for r/ϕ field components and ±(m − 1) for x/y ones can be generated by superposing the two orthogonal polarization degenerate T E mn modes in circular waveguide through a mode-transformation section, and then radiated from the horn in the far end. The effectiveness of the proposed method is analyzed from physical mechanisms and demonstrated by both simulation and experiment for the presented new-typed OAM horn antenna.
A novel approach to tiling is described in which an array of specially designed moulded light guides is used to form a magnified image of a standard AMLCD panel. These arrays can be tessellated to form visually uniform display surfaces of essentially unlimited size.
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