Speaker
Description
Nonlinear mode coupling in micro- and nanoelectromechanical systems (MEMS and NEMS) has been studied extensively because these platforms combine compact size, batch-fabrication compatibility, high reliability, and low power consumption with rich dynamical behavior. In particular, coupled resonators can exhibit energy exchange between interacting modes or neighboring resonators through linear and nonlinear coupling mechanisms. Previous works have established important phenomena such as veering, crossover, internal resonance, chaos, and Hopf bifurcation, significantly advancing the physical understanding of nonlinear interactions in N/MEMS resonators. However, most of these studies have focused on observing, characterizing, or mitigating such phenomena, rather than exploiting them as controllable functional mechanisms to engineer the resurgence time. As a result, a key gap remains in the systematic engineering of dynamic energy transfer and redistribution between coupled modes/ resonators, particularly for applications in communication and computation, where controlled signal flow, recurrence, and energy routing are essential.
In this talk, we address this gap by investigating how nonlinear interactions govern dynamic energy transfer in two nanomechanical systems: intermodal coupling within a single nanobeam and inter-resonator coupling in an engineered array of coupled nanomechanical resonators. We first analyze the nonlinear dynamics of a clamped-clamped Euler-Bernoulli nanobeam, taking into account built-in axial tension, geometric nonlinearity arising from mid-plane stretching, and amplitude-dependent nonlinear damping. Built-in tension is incorporated by means of a tension-dependent shift in the modal frequencies, whereas nonlinearity is described by a cubic modal-coupling term derived from mid-plane stretching. In addition, a phenomenological nonlinear damping term is included to capture amplitude-dependent dissipation. Within this framework, we show that the interplay of these mechanisms gives rise to controlled energy sharing among the fundamental, third-, and fifth-order modes. Importantly, this energy-sharing process depends strongly on the activation force and exhibits a characteristic time-dependent onset, revealing a tunable temporal responce. This behavior is particularly relevant for computational functionality, as the onset and redistribution of modal energy may be harnessed for nonlinear switching and neuromorphic-inspired operations.
We then extend the analysis to a system of nine coupled resonators in order to examine how energy transfer evolves in a larger, designed architecture. In this case, we focus on the dynamics of energy exchange between the first two out-of-plane fundamental modes and show that the transfer dynamics depend sensitively on the resonator design parameters. To capture these effects, we employ a nonlinear model containing both quadratic and cubic nonlinearity, enabling a broader description of energy redistribution and recurrence in coupled nanomechanical resonators. Our results show that the inclusion of quadratic nonlinearities modifies the recurrence time by altering both the available coupling pathways and the amplitude-dependent frequency shifts. These findings demonstrate that recurrence and energy-flow pathways are not fixed properties of the system but can be engineered through the nonlinear interaction landscape and device design.
The first part of the work identifies how nonlinear dissipation, modal coupling, and forcing conditions determine the onset and timescale of intermodal energy transfer in a single device. The second part shows how nonlinear potential in coupled arrays can reshape redistribution and recurrence dynamics at the multi-resonator level. We show that dynamic energy transfer in nonlinear coupled nanomechanical systems is not merely a secondary consequence of mode interaction, but a controllable physical resource. This makes it a promising mechanism for future communication and computation technologies, including signal routing, logic functionality, information processing, and neuromorphic architectures.
We acknowledge the support from the project PIONEER, funded by Horizon Europe under Grant Agreement No. 101211881.
References
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