  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
