Qi Xiao, Wen Xu, Xiumei Yin, Na Zhou, Xinyao Dong, Ge Zhu, Xixian Luo, Yinglin Song, Bin Dong
Photon upconversion (UC), while promising for infrared photonics, is fundamentally constrained by limited spectral response range, low efficiency, and slow response speeds. Here, we present a machine learning-guided single-photon UC strategy based on cascade pumping that implements a "LEGO-inspired photon stacking" mechanism, in which intermediate state of lanthanide ions (Ln3+) becomes a "virtual ground state" for direct single-photon pumping to target energy levels. As a proof-of-concept, the NaYS2:Ho3+ UC emissions are selectively enhanced by 2-3 orders of magnitude via precise population control. This mechanism extends efficient UC response to ~2100 nm and reduces response time from 30 ms to 54 μs. The approach generalizes to other Ln3+ (Tm3+/Pr3+/Er3+), and energy-transfer optimization in Ho3+-sensitized systems yields near-pure RGB emission. We further demonstrate the high-sensitivity and rapid-response UC narrowband photodetection, enabling low-threshold CO2 sensing with a sensitivity of 6.4×10-4 ppm-1. Our work offers strategy for developing single-photon UC and infrared photodetection technologies.