Multiplexed structured illumination super-resolution imaging with time-domain upconversion nanoparticles

Abstract: The emerging optical multiplexing within nanoscale shows super-capacity in encoding information by using the time-domain fingerprints from uniform nanoparticles. However, the optical diffraction limit compromises the decoding throughput and accuracy of the nanoparticles during wide-field imaging. This, in turn, challenges the quality of nanoparticles to afford the modulated excitation condition, and further to retain the multiplexed optical fingerprints for super-resolution multiplexing. Here we report a tailor-made time-domain super-resolution method with the lifetime-engineered upconversion nanoparticles for multiplexing. We demonstrate that the nanoparticles are bright, uniform, and stable under structured illumination, which supports a lateral resolution of 186 nm, less than 1/4th of the excitation wavelength. We further develop a deep learning algorithm to coordinate with super-resolution images for more accurate decoding compared to a numeric algorithm. We demonstrate a three-channel sub-diffraction-limit imaging-based optical multiplexing with decoding accuracies above 93% for each channel, and larger than 60% accuracies for potential seven-channel multiplexing. The improved resolution provides high throughput by resolving the particles within the optical limit, which enables higher multiplexing capacity in space. This time-domain super-resolution multiplexing opens a new horizon for handling the growing amount of information content, diseases source, and security risk in modern society