Efficient chiral hydrogel template based on supramolecular self-assembly driven by chiral carbon dots for circularly polarized luminescence.

Since the chiral emission of excited states is observed on carbon dots (CDs), exploration towards the design and synthesis of chiral CDs nanomaterials with circularly polarized luminescence (CPL) properties has been at a brisk pace. In this regard, the "host and guest" co-assembly strategy based on the combination of CDs and chiral templates has been of unique interest recently for its convenient operation, multicolor tunable CPL, and wide application of prepared CDs-composited materials in optoelectronic devices and information encryption. However, the existing chiral templates that match perfectly with chiral CDs exhibiting optical activity both in ground and excited states are rather scarce.

Machine-Learning-Driven G-Quartet-Based Circularly Polarized Luminescence Materials.

Circularly polarized luminescence (CPL) materials have garnered significant interest due to their potential applications in chiral functional devices. Synthesizing CPL materials with a high dissymmetry factor (g ) remains a significant challenge. Inspired by efficient machine learning (ML) applications in scientific research, this work demonstrates ML-based techniques for the first time to guide the synthesis of G-quartet-based CPL gels with high g values and multiple chiral regulation strategies.