Recently, the Nanophotonics Materials and Technology team, led by Professor Bingsuo Zou from the School of Resources, Environment and Materials of GXU, in collaboration with Associate Professor Lina Yang from the School of Computer, Electronics and Information and Professor Quan Niu from South China University of Technology, has made new progress in the research of AI-guided near-infrared luminescent materials and devices. The related findings were published in the international academic journal “Nature Communications” under the title “Machine-learning guided engineering of Mo⁴⁺ activated halide near-infrared phosphors for AI-augmented medical imaging”. Professor Bingsuo Zou is the sole corresponding author, and Guangxi University is the first and exclusive corresponding institution of the paper.

Guangxi has long enjoyed the reputation of "home of non-ferrous metals", with very rich reserves of antimony, zirconium, and molybdenum ore resources. How to utilize these elements to develop novel high-value-added optoelectronic materials and devices is a current challenge. Focusing on the key scientific issue of developing highly thermally stable, efficient lead-free near-infrared (NIR) phosphors, the team co-doped Mo⁴⁺ and Sb³⁺ in a Cs₂Zr(Cl₁₋ₓBrₓ)₆ matrix, combined with machine learning prediction and optimization, and successfully obtained a broadband near-infrared emitting material centered at 920 nm. The material achieves a photoluminescence quantum yield of 92.4% and an external quantum efficiency of 65.9%. Compared with the optimal performance composition obtained via conventional orthogonal experimental design, the luminescence intensity of this material was enhanced by approximately 20%, and the NIR LED fabricated based on SM‑CZCB achieved a power conversion efficiency of 27.07% under 450 nm excitation.

This research integrates artificial intelligence throughout the entire chain of material design, device fabrication, and imaging applications, successfully achieving high-resolution visualization of vascular structures under a human tissue thickness exceeding 11 cm. This provides new ideas for AI-enhanced medical imaging research and also opens up a new path for the application of Guangxi's characteristic metal resources in the field of new materials.

This research was supported by the Guangxi Science and Technology Program, the Guangxi Natural Science Foundation, the Guangxi "Nanophotonics Materials and Technology" Talent Highland, and other projects, as well as the strong support of the Guangxi Key Laboratory of Non-ferrous Metals and Characteristic Materials Processing.