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

TL;DR
This paper introduces an autonomous experimentation platform that uses machine learning to discover principles for controlling spontaneous emission in reconfigurable semiconductor metasurfaces, achieving significant emission directivity improvements.
Contribution
The study presents a self-driving lab that uncovers the governing equations for steering spontaneous emission, integrating advanced AI techniques to optimize and understand nanophotonic structures.
Findings
Discovered key factors like spatial gradient and curvature in refractive index for emission control.
Achieved a four-fold increase in emission directivity within 300 experiments.
Identified that positive gratings and lenses can effectively steer emission across all angles.
Abstract
We developed an autonomous experimentation platform to accelerate interpretable scientific discovery in ultrafast nanophotonics, targeting a novel method to steer spontaneous emission from reconfigurable semiconductor metasurfaces. Controlling spontaneous emission is crucial for clean-energy solutions in illumination, thermal radiation engineering, and remote sensing. 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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
