A bifurcation-based coupled linear-bistable system for microscale mass sensing

Harne, Ryan L.; Wang, K.W.

doi:10.1016/j.jsv.2013.12.017

Cited by 71 publications

(36 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These structures exhibit rich dynamical phenomena, have exquisite sensitivity near instabilities and allow for efficient control of deformed configuration using external fields. Collectively, these aspects give rise to a myriad of functional advantages in applications such as switches 1,2 , sensors 3,4 and non-volatile memories 5 . The most common and widely used bistable element is a curved beam, shown in Fig.…”

mentioning

confidence: 99%

Experimental dynamic trapping of electrostatically actuated bistable micro-beams

Medina

Gilat

Ilić

et al. 2016

Applied Physics Letters

View full text Add to dashboard Cite

We demonstrate dynamic snap-through from a primary to a secondary statically inaccessible stable configuration in single crystal silicon, curved, doubly clamped micromechanical beam structures. Nanoscale motion of the fabricated bistable micromechanical devices was transduced using a high speed camera. Our experimental and theoretical results collectively show, that the transition between the two stable states was solely achieved by a tailored time dependent electrostatic actuation. Fast imaging of micromechanical motion allowed for direct visualization of dynamic trapping at the statically inaccessible state. These results further suggest that our direct dynamic actuation transcends prevalent limitations in controlling geometrically non-linear microstructures, and may have applications extending to multi-stable, topologically optimized micromechanical logic and non-volatile memory architectures.

show abstract

mentioning

confidence: 99%

Experimental dynamic trapping of electrostatically actuated bistable micro-beams

Medina

Gilat

Ilić

et al. 2016

Applied Physics Letters

View full text Add to dashboard Cite

show abstract

“…Since the excitation conditions are selected by the user or designer of the sensor, these critical mass sensing factors may be directly adjusted for the specific application of interest. These insights were not obtainable through the investigations of the past study by Harne and Wang (2014) and suggest further comprehensive explorations may uncover additional critical abilities and sensitivities of the passive mass measurement strategy that may lead to the development of valuable design guidelines.…”

Section: System Operation Studiesmentioning

confidence: 91%

Passive measurement of progressive mass change via bifurcation sensing with a multistable micromechanical system

Harne

Wang

2014

Journal of Intelligent Material Systems and Structures

View full text Add to dashboard Cite

Mass sensing using the onset and crossing of a dynamic bifurcation of a micromechanical system has been shown to reduce the mass threshold which may be detected and exhibited improved robustness to damping and noise compared to traditional tracking of resonant frequency shift. Previous investigations demonstrated that mass measurement over time via actively controlled strategies or explored passively operated threshold-type methods to indicate a predetermined mass was adsorbed. Recently, an alternative idea integrating aspect of frequency shift-and bifurcation-based mass sensors and methods was proposed, providing initial illustration of a noteworthy ability to passively quantify progressive mass adsorption due to sequentially activated bifurcations. To advance the state of the art, this research provides a thorough investigation of this new sensing concept in terms of its dynamic characteristics and devises guidelines for effective, reliable operations. The conceptual foundation of the sensing method and an experimentally validated sensor model are reviewed. The results of numerous simulated operational trials and parametric investigations are detailed to reach important conclusions on sensor operations and versatility, and to uncover the influences of key operational conditions upon detection metrics. Finally, suitable microscale sensor architectures and fabrications are described to exemplify the flexibility of successfully realizing the mass sensing strategy.

show abstract

“…Recently, great attention has been devoted to the development of robust and sensitive microscale bifurcation-based sensors due to the ease of activating strongly nonlinear behaviors on such a length scale, including the pitchfork [38][39][40] and saddle-node bifurcations [41][42][43][44]. By leveraging unmistakable and sudden variations in sensor behavior due to subtle perturbations to the system which induce the bifurcation, the bifurcation-based sensing methods yield significantly enhanced resolution and sensitivity compared to conventional, linear dynamics-based detection methods.…”

Section: Introductionmentioning

confidence: 99%

Predicting Non-Stationary and Stochastic Activation of Saddle-Node Bifurcation

Kim

Harne

Wang

2016

Journal of Computational and Nonlinear Dynamics

View full text Add to dashboard Cite

Accurately predicting the onset of large behavioral deviations associated with saddle-node bifurcations is imperative in a broad range of sciences and for a wide variety of purposes, including ecological assessment, signal amplification, and microscale mass sensing. In many such practices, noise and non-stationarity are unavoidable and ever-present influences. As a result, it is critical to simultaneously account for these two factors toward the estimation of parameters that may induce sudden bifurcations. Here, a new analytical formulation is presented to accurately determine the probable time at which a system undergoes an escape event as governing parameters are swept toward a saddle-node bifurcation point in the presence of noise. The double-well Duffing oscillator serves as the archetype system of interest since it possesses a dynamic saddle-node bifurcation. The stochastic normal form of the saddle-node bifurcation is derived from the governing equation of this oscillator to formulate the probability distribution of escape events. Non-stationarity is accounted for using a time-dependent bifurcation parameter in the stochastic normal form. Then, the mean escape time is approximated from the probability density function (PDF) to yield a straightforward means to estimate the point of bifurcation. Experiments conducted using a double-well Duffing analog circuit verifies that the analytical approximations provide faithful estimation of the critical parameters that lead to the non-stationary and noise-activated saddle-node bifurcation.

show abstract

A bifurcation-based coupled linear-bistable system for microscale mass sensing

Cited by 71 publications

References 43 publications

Experimental dynamic trapping of electrostatically actuated bistable micro-beams

Experimental dynamic trapping of electrostatically actuated bistable micro-beams

Passive measurement of progressive mass change via bifurcation sensing with a multistable micromechanical system

Predicting Non-Stationary and Stochastic Activation of Saddle-Node Bifurcation

Contact Info

Product

Resources

About