Self-driving lab discovers principles for steering spontaneous emission beyond conventional Fourier optics
Saaketh Desai, Sadhvikas Addamane, Jeffrey Y. Tsao, Igal Brener, Remi Dingreville, Prasad P. Iyer

TL;DR
A self-driving lab uses machine learning to discover new ways to control light emission from metasurfaces beyond traditional methods.
Contribution
The study introduces a self-driving lab platform that discovers new principles for steering spontaneous emission using metasurface refractive index gradients and curvatures.
Findings
Combinations of positive gratings and lenses are as effective as negative ones for emission control.
The platform achieves up to 77% peak emission directivity within ~300 experiments.
Both spatial gradient and curvature of refractive index are key for steering spontaneous emission.
Abstract
We develop an autonomous experimentation platform to accelerate interpretable scientific discovery in ultrafast nanophotonics, targeting a novel method to steer spontaneous emission from reconfigurable semiconductor metasurfaces. Despite the potential of reconfigurable semiconductor metasurfaces with embedded sources for spatiotemporal control, achieving arbitrary far-field control remains challenging. Here, we present a self-driving lab (SDL) platform that addresses this challenge by discovering the governing equations for predicting the far-field emission profile from light-emitting metasurfaces. We discover that both the spatial gradient (grating-like) and the curvature (lens-like) of the local refractive index are key factors in steering spontaneous emission. The SDL employs a machine-learning framework comprising: (1) a variational autoencoder for generating complex spatial…
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Taxonomy
TopicsMetamaterials and Metasurfaces Applications · Plasmonic and Surface Plasmon Research · Thermal Radiation and Cooling Technologies
