Disorder suppression and precise conductance quantization in constrictions of PbTe quantum wells

Conductance quantization was measured in submicron constrictions of PbTe, patterned into narrow,12 nm wide quantum wells deposited between Pb$_{0.92}$Eu$_{0.08}$Te barriers. Because the quantum confinement imposed by the barriers is much stronger than the lateral one, the one-dimensional electron energy level structure is very similar to that usually met in constrictions of AlGaAs/GaAs heterostructures. However, in contrast to any other system studied so far, we observe precise conductance quantization in $2e^2/h$ units, {\it despite of significant amount of charged defects in the vicinity of the constriction}. We show that such extraordinary results is a consequence of the paraelectric properties of PbTe, namely, the suppression of long-range tails of the Coulomb potentials due to the huge dielectric constant.Comment: 7 pages, 6 figures, submitted to Phys. Rev.

Temperature reconstruction of infrared images with motion deblurring

Infrared images of an uncooled microbolometer camera can show significant blurring effects while recording a moving object. The electrical signal in the pixel of a microbolometer detector decays exponentially; hence, the moving object is mapped to more pixels resulting in a blurred image. Not only the contrast is corrupted by the motion, but also the temperature of the object seems to be significantly lower. In this paper, it is shown how such images can be deblurred and the true temperature with a good approximation restored. Since the detection mechanism of a microbolometer camera is different from complementary metal–oxide–semiconductor (CMOS) or charge-coupled device (CCD) cameras, also the point-spread function (PSF) needed for the deblurring restoration is different. It is shown how the exponential coefficient of the PSF can be calculated if the motion speed and the camera resolution are known, or otherwise how it can be estimated from the image itself. Experimental examples are presented for motion deblurring used to restore images with linear or rotational motion

Thermal resistance field estimations from IR thermography using multiscale Bayesian inference

The main goal of this paper is the estimation of thermal resistive fields in multilayer samples using the classical front face flash method as excitation and InfRared Thermography (IRT) as a monitoring sensor. The complete inverse processing of a multilayer analytical model can be difficult due to a lack of sensitivity to certain parameters (layer thickness, depth of thermal resistance, etc.) or processing time. For these reasons, our present strategy proposes a Bayesian inference approach. Using the analytical quadrupole method, a reference model can be calculated for a set of parameters. Then, the Bayesian probabilistic method is used to determine the maximum likelihood probability between the measured data and the reference model. To keep the processing method robust and fast, an automatic selection of the calculation range is proposed. Finally, in the case of a bilayer sample, both the thickness and resistive 3D layers are estimated in less than 2 min for a space and time matrix of 50,000 pixels by 4000 time steps with a reasonable relative error of less than 5%

Thermal (IR) and Other NDT Techniques for Improved Material Inspection

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