Richard A. Norte

L. Norder, S. Yin, M. J. de Jong et al.

The Starshot Breakthrough Initiative aims to send one-gram microchip probes to Alpha Centauri within 20 years, using gram-scale lightsails propelled by laser-based radiation pressure, reaching velocities nearing a fifth of light speed. This mission requires lightsail materials that challenge the fundamentals of nanotechnology, requiring innovations in optics, material science and structural engineering. Unlike the microchip payload, which must be minimized in every dimension, such lightsails need meter-scale dimensions with nanoscale thickness and billions of nanoscale holes to enhance reflectivity and reduce mass. Our study employs neural topology optimization, revealing a novel pentagonal lattice-based photonic crystal (PhC) reflector. The optimized designs shorten acceleration times, therefore lowering launch costs significantly. Crucially, these designs also enable lightsail material fabrication with orders-of-magnitude reduction in costs. We have fabricated a 60 x 60 mm$^2$, 200nm thick, single-layer reflector perforated with over a billion nanoscale features; the highest aspect-ratio nanophotonic element to date. We achieve this with nearly 9,000 times cost reduction per m$^2$. Starshot lightsails will have several stringent requirements but will ultimately be driven by costs to build at scale. Here we highlight challenges and possible solutions in developing lightsail materials - showcasing the potential of scaling nanophotonics for cost-effective next-generation space exploration.

Dongil Shin, Andrea Cupertino, Matthijs H. J. de Jong et al.

From ultra-sensitive detectors of fundamental forces to quantum networks and sensors, mechanical resonators are enabling next-generation technologies to operate in room temperature environments. Currently, silicon nitride nanoresonators stand as a leading microchip platform in these advances by allowing for mechanical resonators whose motion is remarkably isolated from ambient thermal noise. However, to date, human intuition has remained the driving force behind design processes. Here, inspired by nature and guided by machine learning, a spiderweb nanomechanical resonator is developed that exhibits vibration modes which are isolated from ambient thermal environments via a novel "torsional soft-clamping" mechanism discovered by the data-driven optimization algorithm. This bio-inspired resonator is then fabricated; experimentally confirming a new paradigm in mechanics with quality factors above 1 billion in room temperature environments. In contrast to other state-of-the-art resonators, this milestone is achieved with a compact design which does not require sub-micron lithographic features or complex phononic bandgaps, making it significantly easier and cheaper to manufacture at large scales. Here we demonstrate the ability of machine learning to work in tandem with human intuition to augment creative possibilities and uncover new strategies in computing and nanotechnology.