Thermal Drift Correction for Laboratory Nano Computed Tomography via Outlier Elimination and Feature Point Adjustment

Thermal drift of nano-computed tomography (CT) adversely affects the accurate reconstruction of objects. However, feature-based reference scan correction methods are sometimes unstable for images with similar texture and low contrast. In this study, based on the geometric position of features and the structural similarity (SSIM) of projections, a rough-to-refined rigid alignment method is proposed to align the projection. Using the proposed method, the thermal drift artifacts in reconstructed slices are reduced. Firstly, the initial features are obtained by speeded up robust features (SURF). Then, the outliers are roughly eliminated by the geometric position of global features. The features are refined by the SSIM between the main and reference projections. Subsequently, the SSIM between the neighborhood images of features are used to relocate the features. Finally, the new features are used to align the projections. The two-dimensional (2D) transmission imaging experiments reveal that the proposed method provides more accurate and robust results than the random sample consensus (RANSAC) and locality preserving matching (LPM) methods. For three-dimensional (3D) imaging correction, the proposed method is compared with the commonly used enhanced correlation coefficient (ECC) method and single-step discrete Fourier transform (DFT) algorithm. The results reveal that proposed method can retain the details more faithfully.

All polarization-maintaining Er:fiber-based optical frequency comb for frequency comparison of optical clocks

In this research, we demonstrate an optical frequency comb (OFC) based on a turnkey mode-locked laser with a figure-9 structure and polarization-maintaining fibers for frequency comparison between optical clocks with wavelengths of 698 nm, 729 nm, 1068 nm and 1156 nm. We adopt a multi-branch approach in order to produce high power OFC signals at these specific wavelengths, enabling the signal-to-noise ratio of the beatnotes between the OFC and the clock lasers beyond 30 dB at a resolution bandwidth of 300 kHz. This approach makes the supercontinuum spectra generating process much easier in comparison to a single branch OFC; however, more out-of-loop fibers degrade the long term frequency instability due to thermal drift. To minimize the thermal drift effect, we set the fiber lengths of different branches to be similar, and we stabilize the temperature as well. The out-of-loop frequency instability of the OFC due to the incoherence of the multi-branch is about 5.5×10-19 @ 4000 s, while the in-loop frequency instability of f ceo and that of f beat are 7.5×10-18 @1 s and 8.5×10-18 @1 s, respectively. The turnkey OFC meets the requirement of frequency comparison between the best optical clocks.

Thermal Performance of a Capacitive Comb-Drive MEMS Accelerometer: Measurements vs. Simulation

In this work, we analysed the difference between the measurement and simulation results of thermal drift of a custom designed capacitive MEMS accelerometer. It was manufactured in X-FAB XMB10 technology together with a dedicated readout circuit in X-FAB XP018 technology. It turned out that the temperature sensitivity of the sensor’s output is nonlinear and particularly strong in the negative Celsius temperature range. It was found that the temperature drift is mainly caused by the MEMS sensor and the influence of the readout circuit is minimal. Moreover, the measurements showed that this temperature dependence is the same regardless of applied acceleration. Simulation of the accelerometer’s model allowed us to estimate the contribution of post-manufacturing mismatch on the thermal drift; for our sensor, the mismatch-induced drift accounted for about 6% of total thermal drift. It is argued that the remaining 94% of the drift could be a result of the presence of residual stress in the structure after fabrication.

Characterization and Comparison of Biodegradable Printed Capacitive Humidity Sensors

Flexible and biodegradable sensors are advantageous for their versatility in a range of areas from smart packaging to agriculture. In this work, we characterize and compare the performance of interdigitated electrode (IDE) humidity sensors printed on different biodegradable substrates. In these IDE capacitive devices, the substrate acts as the sensing layer. The dielectric constant of the substrate increases as the material absorbs water from the atmosphere. Consequently, the capacitance across the electrodes is a function of environmental relative humidity. Here, the performance of polylactide (PLA), glossy paper, and potato starch as a sensing layer is compared to that of nonbiodegradable polyethylene terephthalate (PET). The capacitance across inkjet-printed silver electrodes is measured in environmental conditions ranging from 15 to 90% relative humidity. The sensitivity, response time, hysteresis, and temperature dependency are compared for the sensors. The relationship between humidity and capacitance across the sensors can be modeled by exponential growth with an R2 value of 0.99, with paper and starch sensors having the highest overall sensitivity. The PET and PLA sensors have response and recovery times under 5 min and limited hysteresis. However, the paper and starch sensors have response and recovery times closer to 20 min, with significant hysteresis around 100%. The PET and starch sensors are temperature independent, while the PLA and paper sensors display thermal drift that increases with temperature.

Thermal Noise Decoupling of Micro-Newton Thrust Measured in a Torsion Balance

The space gravitational wave detection and drag free control requires the micro-thruster to have ultra-low thrust noise within 0.1 mHz–0.1 Hz, which brings a great challenge to calibration on the ground because it is impossible to shield any spurious couplings due to the asymmetry of torsion balance. Most thrusters dissipate heat during the test, making the rotation axis tilt and components undergo thermal drift, which is hysteretic and asymmetric for micro-Newton thrust measurement. With reference to LISA’s research and coming up with ideas inspired from proportional-integral-derivative (PID) control and multi-timescale (MTS), this paper proposes to expand the state space of temperature to be applied on the thrust prediction based on fine tree regression (FTR) and to subtract the thermal noise filtered by transfer function fitted with z-domain vector fitting (ZDVF). The results show that thrust variation of diurnal asymmetry in temperature is decoupled from 24 μN/Hz1/2 to 4.9 μN/Hz1/2 at 0.11 mHz. Additionally, 1 μN square wave modulation of electrostatic force is extracted from the ambiguous thermal drift background of positive temperature coefficient (PTC) heater. The PID-FTR validation is performed with experimental data in thermal noise decoupling, which can guide the design of thermal control and be extended to other physical quantities for noise decoupling.

Implantable Blood Pressure Sensors with Analogic Thermal Drift Compensation

Implantable pressure sensors represent an important part of the research activity in laboratories. Unfortunately, their use is limited by cost, autonomy and temperature-related drifts. The cost of use depends on several parameters, particularly their low battery life and the need for miniaturization to be able to implant the animals and monitor them over a time that is long enough to be physiologically relevant. This paper studied the possibility of reducing the thermal drift of implantable sensors. To quantify and compensate for the thermal drift, we developed the equivalent model of the piezoresistive probe by using the Cadence software. Our model takes into account the temperature (34–39 °C) as well as the pressure (0–300 mmHg). We were thus able to identify the source of the drift and thanks to our model, we were able to compensate for it thanks to the compensation circuits added to the conditioning circuits of the sensor. The maximum relative drift of the sensor is (0.1 mV/°C)/3.6 mV (2.7%), a drift of the conditioning circuit is (0.98 mV/°C)/916 mV (0.1%) and the whole is (13.4 mV/°C)/420 mV (32%). The compensated sensor shows a relative maximum drift of (0.371 mV/°C)/405 mV (0.09%). The output voltage remains stable over the measurement temperature range.

Lightweight Thermal Compensation Technique for MEMS Capacitive Accelerometer Oriented to Quasi-Static Measurements

The application of MEMS capacitive accelerometers isimited by its thermal dependence, and each accelerometer must be individually calibrated to improve its performance. In this work, aight calibration method based on theoretical studies is proposed to obtain two characteristic parameters of the sensor’s operation: the temperature drift of bias and the temperature drift of scale factor. This method requiresess data to obtain the characteristic parameters, allowing a faster calibration. Furthermore, using an equation with fewer parameters reduces the computational cost of compensation. After studying six accelerometers, modelIS3DSH, their characteristic parameters are obtained in a temperature range between 15 ∘C and 55 ∘C. It is observed that the Temperature Drift of Bias (TDB) is the parameter with the greatest influence on thermal drift, reaching 1.3 mg/∘C. The Temperature Drift of Scale Factor (TDSF) is always negative and ranges between 0 and −400 ppm/∘C. With these parameters, the thermal drifts are compensated in tests with 20 ∘C of thermal variation. An average improvement of 47% was observed. In the axes where the thermal drift was greater than 1 mg/∘C, the improvement was greater than 80%. Other sensor behaviors have also been analyzed, such as temporal drift (up to 1 mg/h for three hours) and self-heating (2–3 ∘C in the first hours with the corresponding drift). Thermal compensation has been found to reduce the effect of theatter in the first hours after power-up of the sensor by 43%.