Rapid, Accurate Classification of Single Emitters in Various Conditions and Environments for Blinking-Based Multiplexing.

Although single-molecule imaging is widely applied in biology and materials science, most studies are limited by their reliance on spectrally distinct fluorescent probes. We recently introduced blinking-based multiplexing (BBM), a simple approach to differentiate spectrally overlapped single emitters based solely on their intrinsic blinking dynamics. The original proof-of-concept study implemented two methods for emitter classification: an empirically derived metric and a deep learning algorithm, both of which have significant drawbacks.