In recent years, major advances in nanotechnology have inspired some of the most innovative breakthroughs in various fields, including the development of nanomechanical resonators, such as high-precision sensing and quantum network applications.
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Now, a team of researchers at TU Delft have designed one of the most advanced and precise nanomechanical resonators drawing inspiration from both the natural and virtual world. Inspired by spiderwebs and guided by machine learning, the team set about creating a web-shaped device that would exhibit vibration modes that are isolated from ambient thermal environments.
One of the most sought after characteristics for a mechanical resonator is noise isolation from thermal environments, namely at room temperature conditions where thermomechanical noise can dominate.
Dr. Richard Norte, TU Delft
Inspired by Nature
Spiderwebs are constructed of unique and complex geometries, making them one of the most well-known and intriguing structures in nature. Despite being found almost anywhere and everywhere, researchers from various fields, such as materials science, physics and biology, are still discovering new and novel features regarding the mechanics of spiderwebs.
One of the things known about spiderwebs is that they are exceptional, robust isolated vibrational sensors. Spiders are able to sense their entangled prey via the web’s design. They detect vibrations that emanate from within the web, not environmental disturbances around it.
To aid their work and set about developing the right kind of nanomechanical resonator, the team employed machine learning to guide the optimization of the process using the Bayesian Optimization algorithm.
In the context of designing the spiderweb nanomechanical resonator, Bayesian optimization is expected to not only explore the design space to find new vibrational modes that induce soft clamping with a compact design, but also use them to reach high quality factors in the low frequency regime for a given resonator size.
Dr. Richard Norte, TU Delft
Bayesian Evolution
While spiderwebs are the product of millions of years of extremely sophisticated evolution, the Bayesian optimization model expedited the process and allowed the researchers to quickly make their calculations so they could streamline the design process for their ultra-sensitive device.
The resulting design model was a simplified web-like structure composed of radial and lateral beams with junctions between them. The computer simulations also revealed that the nanomechanical resonator could function at room temperature under ambient conditions with high vibrational energy.
The results also showed that the simple design functioned well with extremely low levels of environmental disturbance leaking into the resonator. This led to the team fabricating an ultrathin device that demonstrated outstanding performance capabilities.
The team was also astonished by the fact there was minimal energy loss outside of the device as the vibrations remained mostly confined to the spiderweb nanomechanical resonator.
The functionality of the TU Delft team’s nanomechanical resonator could have significant implications for the field of quantum computing, especially as quantum devices generally have to be stored at sub-zero temperatures (as close to absolute zero as possible) as they are super sensitive to ambient conditions at room temperature.
However, the expense and techniques required to store and operate quantum devices mean their costs can prove to be obstructive. Therefore, the development of a strategy that could usher in the next generation of nanomechanical resonators could help shape the future of quantum computing.
The researchers also state that the design strategy could be applied to an extensive range of geometries and design problems involving low-throughput simulations or experiments. They anticipate that future developments in machine learning and optimization together with novel fabrication techniques could usher in an unprecedented advancement of nanotechnology within the next decade.
References and Further Reading
Shin, D., and Cupertino, A., et al., (2021) Spiderweb Nanomechanical Resonators via Bayesian Optimization: Inspired by Nature and Guided by Machine Learning. Advanced Materials, [online] p.2106248. Available at: https://doi.org/10.1002/adma.202106248
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