As the global economy evolves, modernization and urbanization accelerate and various global problems followed. Research in many fields, such as environment, climate and healthcare, is facing increasing challenges. These problems are too complex to be systematically solved by a single discipline. In recent years, artificial intelligence (AI) technology has developed rapidly, as the core discipline of scientific research, when AI technology is applied into chemistry research, great potential will be shown in breaking disciplinary boundaries, promoting multidisciplinary integration and solving various global problems. This paper systematically reviews a number of literatures in the field of AI in the past decade, introduces some AI systems or models that have been applied to various application scenarios in the field of chemistry, such as AlphaFold, SynthReader, dZiner, and AlphaFlow, from reading, deeply learning and analyzing literature, designing synthesis routes, to conducting experiments independently. It predicts and discusses the mechanism of breaking down disciplinary barriers by building an interdisciplinary real-time fusion platform and dynamic knowledge graph, as well as the future path of AI assisted chemical research—"AI+Chem" and other disciplines. It also analyzes and looks forward to the possible development direction of AI and its challenges. At present, whether it is AI+Chem or AI+Chem+multidisciplinary research is still in its infancy, preliminary research has shown that AI technology is very likely to be a powerful tool to break down disciplinary barriers and connect knowledge islands, and also provides great possibilities for solving complex global problems, and the play of tools and problem solving still need to be explored by all scientific researchers.

The practical application of carbon dots (CDs) in room-temperature phosphorescence (RTP) is fundamentally constrained by the inherent trade-off between phosphorescence lifetime and quantum yield within conventional single-confinement systems. Herein, we report a multiscale-coupled triple-confinement paradigm that integrates molecular-level covalent locking (C=N bonds), nanoscale silica encapsulation, and matrix-level boron oxide rigidification. This synergistic design decouples the competing requirements of enhanced intersystem crossing (ISC) and suppressed nonradiative decay, enabling nonlinear performance amplification with a synergy index S = 2.4 (> 1). The optimized CD@SiO₂@B₂O₃ composite exhibits an exceptional phosphorescence lifetime of 1119.8 ms and a quantum yield of 25.98%, corresponding to 3.8-fold and 1.7-fold enhancements relative to single-confinement CD@B₂O₃ (291.4 ms and 15.35%), respectively. Systematic mechanistic investigations confirm that C=N bonds reduce the singlet-triplet energy gap (ΔE_ST) by 0.14 eV to facilitate ISC, whereas the hybrid matrix suppresses nonradiative decay rate by 77.2% (from 2.90 to 0.66 s⁻¹). This strategy is readily extendable to other systems and exhibits excellent universality. Furthermore, leveraging phosphorescence resonance energy transfer (PRET) with trace amounts (1 wt.%) of fluorescent dyes enables multicolor RTP tunability while preserving hundreds-millisecond lifetimes, overcoming the emission color restriction of traditional RTP CDs. These merits enable applications including time-gated information encryption with second-level temporal resolution, high-contrast fingerprint visualization on multicolor substrates, and warm-white light-emitting diodes (LEDs) free of commercial phosphors. This work establishes a universal design principle for multiscale-coupled confinement, providing a robust platform for next-generation high-performance RTP materials.