Supramolecular hydrogen-bonded chiral networks enable blue circularly polarized emission from polymeric carbon quantum dots
Materials Horizons Royal Society of Chemistry (RSC) (2026)
Abstract:
All-organic circularly polarized luminescence (CPL) emitters acting as intrinsic liquid polarizers provide a promising route to reduce optical crosstalk and enhance spatial resolution in displays by directly emitting circularly polarized light, thereby eliminating external polarizers and minimizing energy loss. Herein, we report a highly efficient, all-organic CPL-active liquid polarizer based on chiral organic binary composites (COBCs), in which camphorquinone-derived chiral inducers are integrated with polymeric carbon quantum dots (PCQDs), opening a previously unexplored pathway toward chiral organic-quantum dot composites. The composites exhibit intense blue emission with a photoluminescence quantum yield (PL QY) of 64%, and strong enantioselective CPL with luminescence dissymmetry factors (glum ≈ ±10-2). Circular dichroism spectroscopy reveals multiple Cotton effects with high absorption anisotropy (gabs = 1.2 × 10-2), while time-resolved photoluminescence and electrochemical analyses indicate that hydrogen-bonded chiral networks promote charge transfer and generate intrinsic chiral fields enabling selective CPL emission. A prototype device based on COBCs achieves a spatial resolution of 4 lp mm-1, nearly double that of achiral analogues, while effectively suppressing glare and enhancing image contrast. Our findings establish a design strategy for transforming achiral CQDs into CPL-active materials, opening pathways toward next-generation, energy-efficient photonic and display technologies.Multichannel Photoluminescence of Graphene Quantum Dots Across Femtosecond to Cryogenic Timescales
Small Wiley (2026) e14669
Abstract:
Graphene quantum dots (GQDs) exhibit complex photoluminescence (PL) originating from intrinsic sp2 carbon domains, surface functional groups, and structural defects. Yet the spectral overlap among these emissive channels hinders clear identification of their recombination pathways. Here, we investigate multichannel PL dynamics of commercial GQDs using time‐resolved and cryogenic PL spectroscopy. PL spectra reveal three distinct peaks: Peak I (443 nm) from π–π* transitions, Peak II (520 nm) from surface‐dominated contribution functional states, and Peak III (583 nm) from pyrrolic N‐related defects. Time‐correlated single‐photon counting detects only a 460 nm emission linked to graphitic N traps, indicating that Peaks I–III decay faster than the nanosecond window. Ultrafast optical Kerr‐gate measurements further resolve distinct lifetimes for hydroxyl (<5 ps), carboxyl (5–10 ps), amine (20–30 ps), and carbonyl (40–80 ps) groups. The transient evolution displays cascade relaxation from deep to shallow traps, evidenced by a progressive blue‐shift of Peak II. Cryogenic PL shows stable emission of Peak I, whereas Peak III red‐shifts and broadens with temperature, revealing strong electron–phonon coupling and deep‐level trapping. These results clarify the multichannel emission mechanisms of GQDs and provide design principles for tuning their optical properties.Inverse design of terahertz amplitude modulator using tandem deep neural networks
Applied Physics Letters AIP Publishing 128:4 (2026) 041701
Abstract:
The terahertz (THz) frequency range has emerged as a promising spectral window for broad applications, including next-generation wireless communication, high-resolution imaging, and ultrafast spectroscopy. Among the essential components in these systems, amplitude modulators with high quality (Q) factors can provide sharp, selective frequency responses, which are key requirements for scalable and high-performance THz systems. However, designing high-Q THz modulators remains challenging, as conventional full-wave simulations are time-consuming and inefficient. In this study, we propose a deep learning-based inverse design framework tailored for THz metasurfaces composed of split-ring resonators (SRRs). The framework is built on a tandem neural network architecture that couples a forward model with an inverse network to retrieve structural parameters from desired spectral responses. To enhance physical feasibility and predictive stability, we introduce an autoencoder-based spectral projection method. Our model accurately reconstructs SRR geometries across a wide range of spectral targets by learning the underlying physical relationships. Notably, we demonstrate the inverse design of Fano resonant geometries characterized by high-Q factors and sharp asymmetric resonances, which are essential features for achieving deep modulation. By extending the tandem deep learning approach to the THz domain and incorporating an autoencoder-based spectral projection, our framework provides a scalable and efficient pathway for the rapid prototyping of tunable, high-Q THz devices and lays the foundation for artificial intelligence-driven design of advanced THz photonic components.Comprehensive Analysis of Temperature-Dependent Photoluminescence in Silica-Encapsulated CsPbBr3 and CsPbI3 Perovskite Nanocrystals
Nanomaterials MDPI 16:1 (2026) 76
Abstract:
The temperature-dependent photoluminescence of CsPbBr3/SiO2 and CsPbI3/SiO2 nanocrystals was investigated to understand the thermal stability of SiO2 encapsulation. At increased temperature, intensity quenching, linewidth broadening, energy level shift, and decay dynamics were evaluated as quantified parameters. Comprehensive analysis of these parameters supports that CsPbI3/SiO2 nanocrystals show a stronger interaction with phonons compared with CsPbBr3/SiO2 nanocrystals. Despite SiO2 encapsulation, we conclude that trapping states are still present and the degree of localization can be characterized in terms of short-lived decay time and thermal activation energy.Dispersive near-infrared metalens integrated with linear polarization filtering functionality
Results in Optics Elsevier 21:Appl. Phys. Lett. 124 24 2024 (2025) 100902