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March 14, 2026Nano Letters2 citations

Ultrahigh- Q Torsional Nanomechanics through Bayesian Optimization

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AHA. D. HyattAAA. R. AgrawalCPC. M. Pluchar

Key Points

  • This research aims to enhance torque sensing in nanoribbons by optimizing their mechanical properties using Bayesian methods.
  • Utilized Bayesian optimization to design nanoribbons for optimal dissipation dilution.
  • Applied techniques to centimeter-scale Si3N4 nanoribbons.
  • Assessed performance based on Q factors and torque sensitivity.
  • Achieved Q factors exceeding 100 million in the optimized designs.
  • Reported Q-frequency products over 10^13 Hz at room temperature.
  • Demonstrated thermal torque sensitivity levels around 1 × 10^-20 N·m/√Hz.

Abstract

Recently, it was discovered that torsion modes of strained nanoribbons exhibit dissipation dilution, giving a route to enhanced torque sensing and quantum optomechanics experiments. As with all strained nanomechanical resonators, an important limitation is bending loss due to mode curvature at the clamps. Here we use Bayesian optimization to design nanoribbons with optimal dissipation dilution of the fundamental torsion mode. Applied to centimeter-scale Si3N4 nanoribbons, we realize Q factors exceeding 100 million and Q-frequency products exceeding 1013 Hz at room temperature. The thermal torque sensitivity of the reported devices is at the level of 10-20Nm/Hz, and the zero point angular displacement spectral density is at the level of 10-10rad/Hz; they are moreover simple to fabricate, have high thermal conductivity, and can be heavily mass-loaded without diminishing their Q, making them attractive for diverse fundamental and applied weak force sensing tasks.

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Cite This Study

Hyatt et al. (2026) studied this question.

synapsesocial.com/papers/69b4fc0eb39f7826a300cb5chttps://doi.org/10.1021/acs.nanolett.5c06306
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