A network of parametrically driven silicon nitride mechanical membranes
Luis Mestre, Suyash Singh, Gabriel Margiani, Letizia Catalini, Alexander Eichler, Vincent Dumont

TL;DR
This paper introduces a scalable platform using metallized silicon nitride membranes with high quality factors, tunable frequencies, and strong coupling, enabling exploration of complex nonlinear phenomena and potential analog computing applications.
Contribution
The work presents a novel system of coupled silicon nitride membranes with independent tunability and strong parametric control, advancing the development of nonlinear resonator networks.
Findings
Demonstrated individual frequency tuning via avoided crossings
Achieved strong parametric driving of membranes
Showcased tunability of coupled membrane responses
Abstract
Networks of nonlinear resonators offer a promising platform for analog computing and the emulation of complex systems. However, realizing such networks remains challenging, as it requires resonators with high quality factors, individual frequency tunability, and strong inter-resonator coupling. In this work, we present a system that meets all these criteria. Our system is based on metallized silicon nitride membranes that are coupled via their common substrate and controlled capacitively via electrodes. We demonstrate individual frequency tuning and strong parametric driving of each membrane. Notably, we tune membrane frequencies through avoided crossings and demonstrate tunability of the coupled membrane's parametric response. This platform provides a scalable and controllable setting for exploring collective phenomena, dynamical phase transitions, nonlinear topology, and analog…
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Taxonomy
TopicsAdvanced MEMS and NEMS Technologies · Modular Robots and Swarm Intelligence
