Building and Characterizing Graphene Nanomechanical Resonator Networks
Loading...
Date
2024-01-09
Authors
Carter, Brittany
Journal Title
Journal ISSN
Volume Title
Publisher
University of Oregon
Abstract
Networks of nanoelectromechanical (NEMS) resonators are useful analogs for a variety of many- body systems and enable impactful applications in sensing, phononics, and mechanical information processing. Two main challenges are currently limiting progress toward realizing practical NEMS networks. The first is building a platform of interconnected resonators that is scalable in both size and tunability. The second is spatially quantifying the mechanical parameters of each resonator in the network and their coupling. In this work, we address these two main challenges with a novel scalable platform to build the network and a compatible method to characterize mechanical parameters. Together, this work fills in a vital gap for the experimental realization of programmable NEMS networks.We first present a novel platform of suspended graphene resonators that hosts strong coupling and is scalable in 2D. In this platform, we suspended graphene over pillar arrays, in which large areas of suspended graphene act as drumhead resonators and shared membrane between adjacent resonators allows for direct coupling through strain. We demonstrate the versatility advantages of our graphene-based resonator network by providing evidence of strong coupling through two different tuning methods. We demonstrate the 2D scalability potential of this platform with evidence of coupling between three resonators. Finally, we show noteworthy coupling dynamics of inter-resonator higher order mode coupling that is enabled by our versatile platform.
We then demonstrate a scalable optical technique to spatially characterize graphene NEMS network. In this technique, we read out the fixed-frequency collective response as a single vector. Using just two response vectors, we solve for the site-specific elasticity, mass, damping, and coupling parameters of network clusters. Compared to multiple regression, our algebraic fully characterizes the network parameters without requiring a priori parameter estimates or iterative computation. We apply this technique to single-resonator and coupled-pair clusters and find excellent agreement with expected parameter values and spectral response. Our approach offers a direct means to accurately characterize both classical and quantum resonator systems.
Description
Keywords
Coupled, Graphene, NEMS, Networks, Resonator