Construction of Co,N-Coordinated Carbon Dots for Efficient Oxygen Reduction Reaction.

For the sake of the oxygen reduction reaction (ORR) catalytic performance, carbon dots (CDs) doped with metal atoms have accelerated their local electron flow for the past few years. However, the influence of CDs doped with metal atoms on binding sites and formation mechanisms is still uncertain. Herein, Co,N-doped CDs were facilely prepared by the low-temperature polymerization-solvent extraction strategy from EDTA-Co. The influence of Co doping on the catalytic performance of Co-CDs was explored, mainly in the following aspects: first, the pyridinic N atom content of Co-CDs significantly increased from 4.2 to 11.27 at% compared with the CDs, which indicates that the Co element in the precursor is advantageous in forming more pyridinic-N-active sites for boosting the ORR performance. Second, Co-CDs are uniformly distributed on the surface of carbon black (CB) to form Co-CDs@CB by the facile hydrothermal route, which can expose more active sites than the aggregation status. Third, the highest graphite N content of Co-CDs@CB was found, by limiting the current density of the catalyst towards the ORR. Composite nanomaterials formed by Co and CB are also used as air electrodes to manufacture high-performance zinc-air batteries. The battery has good cycle stability and realizes stable charges and discharges under different current densities. The outstanding catalytic activity of Co-CDs@CB is attributed to the Co,N synergistic effect induced by Co doping, which pioneer a new metal doping mechanism for gaining high-performance electrocatalysts.

Machine-Learning-Driven Synthesis of Carbon Dots with Enhanced Quantum Yields.

Knowing the correlation of reaction parameters in the preparation process of carbon dots (CDs) is essential for optimizing the synthesis strategy, exploring exotic properties, and exploiting potential applications. However, the integrated screening experimental data on the synthesis of CDs are huge and noisy. Machine learning (ML) has recently been successfully used for the screening of high-performance materials. Here, we demonstrate how ML-based techniques can offer insight into the successful prediction, optimization, and acceleration of CDs' synthesis process. A regression ML model on hydrothermal-synthesized CDs is established capable of revealing the relationship between various synthesis parameters and experimental outcomes as well as enhancing the process-related properties such as the fluorescent quantum yield (QY). CDs exhibiting a strong green emission with QY up to 39.3% are obtained through the combined ML guidance and experimental verification. The mass of precursors and the volume of alkaline catalysts are identified as the most important features in the synthesis of high-QY CDs by the trained ML model. The CDs are applied as an ultrasensitive fluorescence probe for monitoring the Fe3+ ion because of their superior optical behaviors. The probe exhibits the linear response to the Fe3+ ion with a wide concentration range (0-150 µM), and its detection limit is 0.039 µM. Our findings demonstrate the great capability of ML to guide the synthesis of high-quality CDs, accelerating the development of intelligent material.

White luminescent single-crystalline chlorinated graphene quantum dots.

A new class of white luminescent materials, white-light-emitting graphene quantum dots (WGQDs), have attracted increasing attention because of their unique features and potential applications. Herein, we designed and synthesized a novel WGQDs via a solvothermal molecular fusion strategy. The modulation of chlorine doping amount and reaction temperature gives the WGQDs a single-crystalline structure and bright white fluorescence properties. In particular, the WGQDs also exhibit novel and robust white phosphorescence performance for the first time. An optimum fluorescence quantum yield of WGQDs is 34%, which exceeds the majority of reported WGQDs and other white luminescent materials. The WGQDs display broad-spectrum absorption within almost the entire visible light region, broad full width at half maximum and extend their phosphorescence emission to the entire white long-wavelength region. This unique dual-mode optical characteristic of the WGQDs originates from the synergistic effect of low-defect and high chlorine-doping in WGQDs and enlarges their applications in white light emission devices, cell nuclei imaging, and information encryption. Our finding provides us an opportunity to design and construct more advanced multifunctional white luminescent materials based on metal-free carbon nanomaterials.