Micro-Electro-Mechanical Sensors and Actuators

我的研究领域是机电系统动力学。微机电系统（MEMS）制造技术的最近可用性允许该领域将活跃的研究和创新领域联合收割机与低成本制造结合。我将利用这个机会介绍新颖的传感器、执行器和微型发电机（MPG），它们的性能优于宏观发电机，并增加了新的功能。为此，我提出了一个研究计划，以促进基础知识和设备开发如下： 1)微型执行器： 我们将研究分析（使用非线性动力学工具）和实验（使用，干涉测量和模拟控制）的静电，电磁和混合MEMS致动器的动态，以了解和稳定大轨道运动，并在其响应中定位分叉。这项基础研究将部署在开发手持式静电MEMS原子力显微镜（AFM）。AFM将结合联合收割机技术，我们已经开发和验证的低电压驱动，全电动亚纳米位置检测，和反馈控制，以稳定长行程静电执行器。 2)微型传感器： 我们将使用我们的研究结果的位置和行为的静电MEMS在附近的不稳定性（分叉）开发分叉为基础的传感器。这些传感器利用分叉将小刺激放大为大检测信号，从而提高灵敏度但不提高成本。我们开发了一类新的分叉传感器：二元传感器，检测分析物的浓度是否高于或低于安全阈值。我们的静态二元传感器能够检测5 ppm的乙醇蒸汽，比商业同等产品好一个数量级。二元传感器也比商业等同物更强大（更简单）。我们将开发设计所需的基础知识，并将演示动态二元气体和化学（水下）传感器。利用动态放大将使动态二进制传感器的灵敏度比静态二进制传感器提高1-2个数量级。 3)MPG： 我们将把冲击振荡器和无弹簧采集器架构的使用从电磁MPG扩展到静电MPG，并开发宽带和低频静电MPG。为了实现这一目标，我们将扩展我们的MPGs动力学的基本分析，从电磁静电转导。由于静电MPG随着其尺寸的缩小而变得更有效，因此我们将使用它们来设计静电MEMS MPG，从而获得低振幅运动。最后，我们将结合联合收割机在传感器和MPG方面的专业知识，开发被动疲劳传感器，该传感器使用低振幅MPG作为积分传感器，以测量施加到结构上的总应变能或人体消耗的动能。

My research area is the dynamics of electromechanical systems. The recent availability of Micro-Electro-Mechanical Systems (MEMS) fabrication technology has allowed this field to combine an active research and innovation area to low-cost fabrication. I will exploit this opportunity to introduce novel sensors, actuators, and micro-power generators (MPGs) that outperform their macro counterparts and add new functionality. Towards that end, I propose a research program to advance fundamental knowledge and device development as follows: 1) Micro Actuators: We will investigate analytically (using nonlinear dynamics tools) and experimentally (using, interferometric measurements and analog control) the dynamics of electrostatic, electromagnetic, and hybrid MEMS actuators to understand and stabilize large orbit motions and locate bifurcations in their response. This fundamental research will be deployed to develop hand-held electrostatic MEMS Atomic Force Microscopes (AFM). The AFM will combine technology we have developed and proven for low-voltage actuation, all-electric sub-nano-meter position detection, and feedback control to stabilize long-stroke electrostatic actuators. 2) Micro Sensors: We will use our findings on locations and behavior of electrostatic MEMS in the vicinity of instabilities (bifurcations) to develop bifurcation-based sensors. These sensors exploit an bifurcations to amplify a small stimulus into a large detection signal, thereby improving sensitivity but not cost. We developed a new class of bifurcation sensors: binary sensors that detects whether the concentration of as analyte is above or below a safety threshold. Our static binary sensors demonstrated ability to detect 5ppm of ethanol vapor, one order-of-magnitude better than the commercial equivalent. Binary sensors are also more robust (simpler) than the commercial equivalents. We will develop the fundamental knowledge necessary to design and we will demonstrate dynamic binary gas and chemical (under water) sensors. Exploiting dynamic amplification will improve the sensitivity of dynamic binary sensors by 1-2 orders-of-magnitude over static binary senors. 3) MPGs: We will extend the use of impact oscillators and springless harvester architecture from electromagnetic to electrostatic MPGs and develop wideband and low-frequency electrostatic MPGs. Towards that goal, we will extend our fundamental analysis of MPGs dynamics from electromagnetic to electrostatic transduction. Because electrostatic MPGs become more efficient as their size scales down, we will use them to design electrostatic MEMS MPGs, thereby harvesting low-amplitude motions. Finally, we will combine our expertise in sensors and MPGs to develop passive fatigue sensors that use low-amplitude MPGs as an integrating sensor to measure the total strain energy applied to a structure or kinetic energy spent by a human.