Estimation of the Young’s Modulus of Nanometer-Thick Films Using Residual Stress-Driven Bilayer Cantilevers

Precise prediction of mechanical behavior of thin films at the nanoscale requires techniques that consider size effects and fabrication-related issues. Here, we propose a test methodology to estimate the Young’s modulus of nanometer-thick films using micromachined bilayer cantilevers. The bilayer cantilevers which comprise a well-known reference layer and a tested film deflect due to the relief of the residual stresses generated during the fabrication process. The mechanical relationship between the measured residual stresses and the corresponding deflections was used to characterize the tested film. Residual stresses and deflections were related using analytical and finite element models that consider intrinsic stress gradients and the use of adherence layers. The proposed methodology was applied to low pressure chemical vapor deposited silicon nitride tested films with thicknesses ranging from 46 nm to 288 nm. The estimated Young’s modulus values varying between 213.9 GPa and 288.3 GPa were consistent with nanoindentation and alternative residual stress-driven techniques. In addition, the dependence of the results on the thickness and the intrinsic stress gradient of the materials was confirmed. The proposed methodology is simple and can be used to characterize diverse materials deposited under different fabrication conditions.

Overlooked current estimation biases arising from the Lagrangian Argo trajectory derivation method

An Argo simulation system is used to provide synthetic Lagrangian trajectories based on the Estimating the Circulation and Climate of the Ocean model, Phase II (ECCO2). In combination with ambient Eulerian velocity at the reference layer (1000 m) from the model, quantitative metrics of the Lagrangian trajectory-derived velocities are computed. The result indicates that the biases induced by the derivation algorithm are strongly linked with ocean dynamics. In low latitudes, Ekman currents and vertically sheared geostrophic currents influence both the magnitude and the direction of the derivation velocity vectors. The maximal shear-induced biases exist near the equator with the amplitudes reaching up to about 1.2 cm s-1. The angles of the shear biases are pronounced in the low latitude oceans, ranging from -8° to 8°. Specifically, the study shows an overlooked bias from the float drifting motions that mainly occurs in the western boundary current and Antarctic circumpolar current (ACC) regions. In these regions, a recently reported horizontal acceleration measured via Lagrangian floats is significantly associated with the strong eddy-jet interactions. The acceleration could induce an overestimation of Eulerian current velocity magnitudes. For the common Argo floats with a 9-day float parking period, the derivation speed biases induced by velocity acceleration would be as large as 3 cm s-1, approximately 12% of the ambient velocity. It might have implications to map the mean mid-depth ocean currents from Argo trajectories, as well as understand the dynamics of eddy-jet interactions in the ocean.

Alignment-Free Sensing Module for Absolute and Incremental Lines in Linear Positioning System Based on Tunneling-Magnetoresistance Sensors

An alignment-free sensing module for the positioning system based on tunneling magnetoresistive (TMR) sensors with an absolute-incremental-integrated scale is demonstrated. The sensors of the proposed system for both lines consist of identical layer stacks; therefore, all sensors can be fabricated in identical processes from thin film deposition to device patterning on a single substrate. Consequently, the relative position of the sensors can be predefined at the lithography stage and the alignment error between sensors caused by the manual installation is completely eliminated. Different from the existing sensing scheme for incremental lines, we proposed to utilize the magnetic tunnel junctions with a perpendicular anisotropy reference layer and an in-plane anisotropy sensing layer. The sensors are placed parallel to the scale plane with magnetization of the sensing layer in the plane, which show the capability of polarity detection for the absolute line and reveal sinusoidal output signal for the incremental line. Furthermore, due to the large signal of TMR, the working distance can be further improved compared with conventional sensors. In addition, the cost of the positioning system is expected to be lowered, since all the sensors are fabricated in the same process without extra installation. Our design may pave a new avenue for the positioning system based on a magnetic detection scheme.

A galvanic-based dissolved oxygen level monitoring sensor system in freshwater ponds

This study aims to develop low-cost and environmentally friendly material galvanic-based dissolved oxygen sensors. A Dissolved oxygen (DO) sensor has been designed and fabricated on an 85 x 205 mm galvanic-based. The sensor structure device consists of Al-Zn reference layer electrode, Ag/AgCl active electrode, 120ml KCl electrolyte solvent 0,1 M, and closed by TiO2 membrane (PTFE). The Al-Zn formation reference electrode was done by Ag layer chlorination using FeCl3, and the TiO2 membrane was formed by TiO2 paste screen printing. The test was done to measure the sensor’s performance based on the current-voltage characteristics between 1.0 and 1.8 V. The results showed that a stable diffusion current was obtained when the input voltage was 1.5 V, resulting in the best sensor performance with a sensitivity of 0.7866 μA L/mg and a stable step response time of 3 mins. This prototype sensor showed high potential for prototyping for a low-cost water quality monitoring system.

Convolutional neural networks for global human settlements mapping from Sentinel-2 satellite imagery

Spatially consistent and up-to-date maps of human settlements are crucial for addressing policies related to urbanization and sustainability, especially in the era of an increasingly urbanized world. The availability of open and free Sentinel-2 data of the Copernicus Earth Observation program offers a new opportunity for wall-to-wall mapping of human settlements at a global scale. This paper presents a deep-learning-based framework for a fully automated extraction of built-up areas at a spatial resolution of 10 m from a global composite of Sentinel-2 imagery. A multi-neuro modeling methodology building on a simple Convolution Neural Networks architecture for pixel-wise image classification of built-up areas is developed. The core features of the proposed model are the image patch of size 5 × 5 pixels adequate for describing built-up areas from Sentinel-2 imagery and the lightweight topology with a total number of 1,448,578 trainable parameters and 4 2D convolutional layers and 2 flattened layers. The deployment of the model on the global Sentinel-2 image composite provides the most detailed and complete map reporting about built-up areas for reference year 2018. The validation of the results with an independent reference dataset of building footprints covering 277 sites across the world establishes the reliability of the built-up layer produced by the proposed framework and the model robustness. The results of this study contribute to cutting-edge research in the field of automated built-up areas mapping from remote sensing data and establish a new reference layer for the analysis of the spatial distribution of human settlements across the rural–urban continuum.

Spin–orbit torque nano-oscillator with giant magnetoresistance readout

Spin-orbit torque nano-oscillators based on bilayers of ferromagnetic and nonmagnetic metals are ultra-compact current-controlled microwave signal sources. They are attractive for practical applications such as microwave assisted magnetic recording, neuromorphic computing, and chip-to-chip wireless communications. However, a major drawback of these devices is low output microwave power arising from the relatively small anisotropic magnetoresistance of the ferromagnetic layer. Here we experimentally show that the output power of a spin-orbit torque nano-oscillator can be significantly enhanced without compromising its structural simplicity. Addition of a ferromagnetic reference layer to the oscillator allows us to employ current-in-plane giant magnetoresistance to boost the output power of the device. This enhancement of the output power is a result of both large magnitude of giant magnetoresistance compared to that of anisotropic magnetoresistance and their different angular dependencies. Our results hold promise for practical applications of spin-orbit torque nano-oscillators.

Toward Quantitative and Operator-independent Quasi-static Ultrasound Elastography: An Ex Vivo Feasibility Study

It is known that the elasticity of liver reduces progressively in the case of diffuse liver disease. Currently, the diagnosis of diffuse liver disease requires a biopsy, which is an invasive procedure. In this paper, we evaluate and report a noninvasive method that can be used to quantify liver stiffness using quasi-static ultrasound elastography approach. Quasi-static elastography is popular in clinical applications where the qualitative assessment of relative tissue stiffness is enough, whereas its potential is relatively underutilized in liver imaging due to lack of local stiffness contrast in the case of diffuse liver disease. Recently, we demonstrated an approach of using a calibrated reference layer to produce quantitative modulus elastograms of the target tissue in simulations and phantom experiments. In a separate work, we reported the development of a compact handheld device to reduce inter- and intraoperator variability in freehand elastography. In this work, we have integrated the reference layer with a handheld controlled compression device and evaluate it for quantitative liver stiffness imaging application. The performance of this technique was assessed on ex vivo goat liver samples. The Young’s modulus values obtained from indentation measurements of liver samples acted as the ground truth for comparison. The results from this work demonstrate that by combining the handheld device along with reference layer, the estimated Young’s modulus value approaches the ground truth with less error compared with that obtained using freehand compression (8% vs. 15%). The results suggest that the intra- and interoperator reproducibility of the liver elasticity also improved when using the handheld device. Elastography with a handheld compression device and reference layer is a reliable and simple technique to provide a quantitative measure of elasticity.