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Main Authors: Fort, Ethan, Mousa, Mohamed, Nouh, Mostafa
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2511.00647
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author Fort, Ethan
Mousa, Mohamed
Nouh, Mostafa
author_facet Fort, Ethan
Mousa, Mohamed
Nouh, Mostafa
contents Recent advances in metamaterials and fabrication techniques have revived interest in mechanical computing. Contrary to techniques relying on static deformations of buckling beams or origami-based lattices, the integration of wave scattering and mechanical memory presents a promising path toward efficient, low-latency elastoacoustic computing. This work introduces a novel class of multifunctional mechanical computing circuits that leverage the rich dynamics of phononic and locally resonant materials. These circuits incorporate memory-integrated components, realized here via metamaterial cells infused with shape memory alloys which recall stored elastic profiles and trigger specific actions upon thermal activation. A critical advantage of this realization is its synergistic interaction with incident vibroacoustic loads and the inherited high speed of waves, giving it a notable performance edge over recent adaptations of mechanically intelligent systems that employ innately slower mechanisms such as elastomeric shape changes and snap-through bistabilities. Through a proof-of-concept physical implementation, the efficacy and reconfigurability of the wave-based gates are demonstrated via output probes and measured wavefields. Furthermore, the modular design of the fundamental gates can be used as building blocks to construct complex combinational logic circuits, paving the way for sequential logic in wave-based analog computing systems.
format Preprint
id arxiv_https___arxiv_org_abs_2511_00647
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Thermoelastic wave-based logic for mechanically cognitive materials
Fort, Ethan
Mousa, Mohamed
Nouh, Mostafa
Applied Physics
Soft Condensed Matter
Recent advances in metamaterials and fabrication techniques have revived interest in mechanical computing. Contrary to techniques relying on static deformations of buckling beams or origami-based lattices, the integration of wave scattering and mechanical memory presents a promising path toward efficient, low-latency elastoacoustic computing. This work introduces a novel class of multifunctional mechanical computing circuits that leverage the rich dynamics of phononic and locally resonant materials. These circuits incorporate memory-integrated components, realized here via metamaterial cells infused with shape memory alloys which recall stored elastic profiles and trigger specific actions upon thermal activation. A critical advantage of this realization is its synergistic interaction with incident vibroacoustic loads and the inherited high speed of waves, giving it a notable performance edge over recent adaptations of mechanically intelligent systems that employ innately slower mechanisms such as elastomeric shape changes and snap-through bistabilities. Through a proof-of-concept physical implementation, the efficacy and reconfigurability of the wave-based gates are demonstrated via output probes and measured wavefields. Furthermore, the modular design of the fundamental gates can be used as building blocks to construct complex combinational logic circuits, paving the way for sequential logic in wave-based analog computing systems.
title Thermoelastic wave-based logic for mechanically cognitive materials
topic Applied Physics
Soft Condensed Matter
url https://arxiv.org/abs/2511.00647