Long-Lifetime and Multicolor Room-Temperature Phosphorescence of Carbon Quantum Dots Derived from Biomass: Applications on Convolutional Neural Network

Material longevity and diversity of a broad color gamut undoubtedly play a role as rigid criteria for dynamic information encryption technologies, particularly for those based on room-temperature phosphorescence (RTP). As a typical example, high-security multidimensional discriminative encryption still faces several obstacles brought about from the intrinsic limitations of carbon nitride quantum dots (CNQDs) which should be overcome, e.g. the quenching susceptibility of triplet excitons, limited tunability of colorimetric emission, and metal-doping-induced instability. To achieve tunable room-temperature phosphorescence (RTP) for advanced information encryption, biofriendly CNQDs were synthesized in this work, in terms of boron-mediated lattice defect engineering and hydrogen-bond rigidification, while dual-color RTP emissions were successfully realized with exceptional afterglow durations, lasting 7 s at 503 nm as well as 2 s at 617 nm. Based on emission mechanisms dominated by n-π* transitions, distinct phosphorescent lifetimes were detected from red and cyan-green CNQDs, within 176 and 290 ms, respectively, and then temporal determinants and Rubik’s Cube matrix transformations strategies were established following with their temporal-spectral characteristics and finally applied to convolutional neural networks (CNN). In fact, this work can be regarded as an attempt to provide a creative model for designing sustainable phosphorescent materials with programmable optical properties, devoted to promoting next-generation information encryption technologies.