Lasing in Self-Assembled Biophotonic Network

TL;DR

This paper demonstrates that mode competition in a biophotonic laser network made from insulin protein reveals intracavity topology and can be used for sensitive sensing and encryption.

Contribution

It introduces the concept of self-assembled biophotonic networks and shows how mode competition dynamics can reconstruct network topology.

Findings

Mode competition dynamics encode network topology.

Insulin fibril network influences laser mode behavior.

Network topology can be reconstructed from laser dynamics.

Abstract

Mode competition is conventionally regarded as an unwanted phenomenon that induces instability of laser emission. Here, we experimentally demonstrate that the random dynamics behavior of mode competition provides hidden information of the intracavity topology. We introduced the concept of self-assembled biophotonics networks, where human insulin protein with network topology was sandwiched in a Fabry-Perot (FP) cavity. The optical coupling between insulin fibrils and enables strong mode competition. Thanks to the optical feedback provided by the FP cavity, the interaction between the light and insulin network was enhanced. Subtle changes in the network will cause significant changes in laser mode dynamics. By recording the transverse mode dynamics, we reconstruct a graph that reveals the optical correlation in the insulin network. Our results indicate that the graph represents an intrinsic feature and can sensitivity respond to the stimulus. The unclonable and sensitively responsive property of the biophotonic lasing network can potentially be employed in applications in sensing and information encryption.