Self-driving lab discovers principles for steering spontaneous emission

• URL: http://arxiv.org/abs/2407.16083v2
• Date: Wed, 24 Jul 2024 16:45:29 GMT
• Title: Self-driving lab discovers principles for steering spontaneous emission
• Authors: Saaketh Desai, Sadhvikas Addamane, Jeffery Y. Tsao, Igal Brener, Remi Dingreville, Prasad P. Iyer,
• Abstract summary: Controlling emission is crucial for clean-energy solutions in illumination, thermal radiation engineering, and remote sensing. Here, we present a self-driving lab 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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 spontaneous emission. The SDL employs a machine-learning framework comprising: (1) a variational autoencoder for generating complex spatial refractive index profiles, (2) an active learning agent for guiding experiments with real-time closed-loop feedback, and (3) a neural network-based equation learner to uncover structure-property relationships. The SDL demonstrated a four-fold enhancement in peak emission directivity (up to 77%) over a 72{\deg} field of view within ~300 experiments. Our findings reveal that combinations of positive gratings and lenses are as effective as negative lenses and gratings for all emission angles, offering a novel strategy for controlling spontaneous emission beyond conventional Fourier optics.

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