School of Mechanical Engineering Seminar
Monday, December 24, 2018 at 14.00
Wolfson Building of Mechanical Engineering, Room 206

Frequency Based Micro Sensors

Naftaly Krakover

 Ph.D. student of Prof. Slava Krylov

Micro- and nanoelectromechanical systems (MEMS/NEMS)-based sensors are indispensable components in a large variety of products as diverse as consumer electronics, industrial, automotive and defense systems. Simplicity, manufacturability and integrability all contribute to an increasingly widespread use of these small-size low-cost devices. In the realm of high-end sensors, one of the promising and intensively researched approaches for performance improvement is based on the monitoring of the spectral characteristics of the devices. Resonant frequencies of the vibrating structure are extremely sensitive to the external stimuli such as acceleration or pressure and can be measured with high accuracy.

In this work, two different frequency-based sensing approaches ae introduced and their feasibility is demonstrated theoretically and experimentally. The first is a resonant displacement/acceleration sensor, which exploits electrostatic frequency tuning. The device incorporates a vibrating beam located in a close proximity to a quasi-statically deflecting body and interacting with it through the electrostatic field.  Perturbations of the field induced by the body’s deflection affect the effective stiffness of the beam and its natural frequency.  Sensitivity is enhanced by tailoring the nonlinear coupling force using fringing electrostatic fields. The feasibility of the suggested sensing scenario was demonstrated using the deflection measurement of a single crystal silicon micro scale pressurized membrane. The sensitivity of ≈ 30 Hz/kPa, which is equivalent to the displacement sensitivity of ≈ 4 Hz/nm, was registered in the experiments.

The second approach is related to the vibration-based structural health monitoring, especially in the low frequency range. One of the main challenges encountered by the MEMS vibration sensors developers is a large mismatch between typical frequencies of macro and micro scale structures.  Our approach is based on a purely mechanical realization of the superheterodyne principle, which allows conversion of low frequency input signals into high frequency response. The device benefits from the inertial coupling between the translational and tilting vibrational modes of a proof mass attached to an oscillating substrate. The translational vibration creates a time-harmonic offset between the mass and the tilting axis. The frequency mixing moment emerges as a product between the inertial force and the translational displacement. The structure is distinguished by its ability to combine both sensing and signal processing functions by the same device. Our model and experimental results collectively support the feasibility of the suggested concept. Extremely low power consumption of the device makes it especially suitable for autonomous distributed sensors networks valuable for future Internet of Things (IoT) applications.

School of Mechanical Engineering Seminar
Monday, November 12, 2018 at 14:00
Wolfson Building of Mechanical Engineering, Room 206

Heat transfer During Phase Separation of Partially Miscible Liquid-Liquid Systems in Mini-Channels

by

Idan Shem Tov

This research was carried out in the School of Mechanical Engineering under the supervision of Prof. Amos Ullmann

and Prof. Neima Brauner

The increasing power density of miniaturized equipment requires advanced cooling technologies to maintain allowable temperatures and ensure safe operation. An experimental study has been conducted to explore the possibility of enhancing the convective heat transfer in mini-channels by temperature-induced phase separation of partially miscible liquid-liquid mixtures. The convective heat transfer of three different mixtures: triethylamine-water, propylene glycol propyl ether-water and lutidine-water was tested under conditions of constant wall heat fluxes. The phase separation of the mixtures showed up to 120% cooling enhancement compared to single-phase flow, up to 25% enhancement compared to water and up to 150% enhancement compared to the standard coolant of ethylene glycol-water mixture. The best results were achieved with triethylamine-water mixture under low Re number and high heating power. The creation and migration of droplets when phase-separation takes place and the resulting local fluid mixing in the heated wall vicinity, was found to be the main mechanism leading to the HTC enhancement. The local mixing can be represented as higher effective fluid thermal conductivity (k). The effective k values, circulated via CFD simulations, are up to 2.1 larger than those of the corresponding single-phase flow values. In parallel to this research, USA group, in collaboration with our research group, showed that the effect of HTC enchantment is preserved upon downscaling to micro-channel.

School of Mechanical Engineering Seminar
Wednesday, December 03, 2018 at 14:00
Wolfson Building of Mechanical Engineering, Room 206

Simulating photothermal actuation in resonant micro bridges

 Gilad Goldenberg

 MSc Student of Dr. Yoav Linzon

This work comes from the application need of optimizing the photothermal actuation in micro bridges that change their resonance frequencies with changes in mass due to gas absorption. The micro bridges are activated using 405[nm] (blue) laser close to resonance frequency, the actual bridge frequencies are sensed with red probe laser.

The research in this work is performed using Comsol Multiphysics, modeling the polysilicon micro bridges of various lengths (20 um, 30 um and 35 um) and their oscillation using thermal actuation in periodic and aperiodic actuation.

The research main results are:

1.    The expected displacements in 1.5um wide, 0.14um thick and 20um, 30um and 35 um long polysilicon bridges in the time domain.

2.    The expected maximum displacements in 1.5um wide, 0.14um thick and 20um, 30um and 35 um long polysilicon bridges in the frequency domain.

3.    The Q factors derived from the frequency domain analysis.

4.    An analysis of the bridge heating duty cycle effect on the maximum displacement.

5.    An analysis of unsynchronized activation.

Multidimensional diffusion MRI

Author: D. Topgaard
Affiliation: Department of Chemistry, Lund University, Sweden
E-mail: daniel.topgaard@fkem1.lu.se

The use Diffusion MRI is an excellent method for detecting subtle microscopic changes of the living human brain, but often fails to assign the experimental observations to specific structural properties such as cell density, size, shape, or orientation. When attempting to solve this problem, we have chosen to disregard essentially all previous work in the field of diffusion MRI, and instead translate data acquisition and processing schemes from multidimensional solid-state NMR spectroscopy [1, 2]. Key elements of our approach are free gradient waveforms, q-vector trajectories, b-tensors, and correlations between isotropic and directional diffusion encoding. By approximating the water displacement probability as a sum of anisotropic Gaussians, the voxel composition can be reported as a diffusion tensor distribution where each component of the distribution corresponds to a distinct tissue environment. Our new methods yield estimates of the complete diffusion tensor distribution or well-defined statistical properties thereof, such as the mean and variance of isotropic diffusivities, mean-square anisotropy, and orientational order parameter, which derive from analogous parameters in solid-state NMR and can be related to the structural properties of the tissue. This presentation will give an overview of the new methods, including basic physical principles, pulse sequences, and data processing, as well as examples of applications in healthy and diseased brain.

[1] Schmidt-Rohr K, Spiess HW. Multidimensional solid-state NMR and polymers. San Diego: Academic Press; 1994.
[2] Topgaard D. Multidimensional diffusion MRI. J Magn Reson 2017;275:98-113. https://dx.doi.org/10.1016/j.jmr.2016.12.007