The detection of nitroaromatic explosives is of great importance owing to their strong explosive power and harmfulness in terms of the environment, homeland security and public safety. Herein, rare earth-doped carbon dots with multifunctional features were firstly prepared by simply keeping the mixture of terbium(iii) nitrate pentahydrate and citric acid at 190 °C for 30 min. The as-prepared terbium doped carbon dots (Tb-CDs), through a rapid and simple direct carbonization route, have a size of about 3 nm, and exhibit excitation wavelength dependent emission of blue fluorescence, are stable, and can be applied for the selective and colorimetric detection of 2,4,6-trinitrophenol (TNP) in the range of 500 nM-100 μM with a limit of detection of 200 nM based on the inner filtering effect (IFE) of the excitation and emission bands of Tb-CDs by TNP and the electron transfer (ET) from Tb-CDs to TNP, giving a precise and highly reproducible result for detecting complex water samples.

Fluorescent carbon dots (CDs) have been increasingly used in fluorescence detection and imaging based on their tunable fluorescence (FL) and resistance to photobleaching. However, the fast and reliable design of fluorescent CDs with specific optical properties involves a number of factors, such as the concentration of precursors, reaction time, and solvents. Therefore, it is usually considered difficult to design CDs with favorable optical properties. Herein, we report an extreme gradient boosting (XGBoost) model for guiding the fabrication of CDs with high FL intensity and tunable emission from p-benzoquinone (PBQ) and ethylenediamine (EDA) in different solvents at room temperature. Among a variety of studied machine learning models, XGBoost shows the best performance in the field of material synthesis, with a prediction coefficient of determination (R 2) higher than 0.96. The XGBoost model can effectively predict the optical properties of CDs, including the maximum FL intensity and emission centers. Guided by the XGBoost model, various green or blue fluorescent CDs with adjustable emission centers and solubility properties are designed and fabricated accurately. These CDs are successfully applied for Fe3+ detection, sustained drug release, whole-cell imaging, and poly­(vinyl alcohol) (PVA) film preparation. These results suggest the great potential of the combination of machine learning and CD synthesis as an effective strategy to help researchers realize accurate selection of reasonable CDs with individual customized properties to achieve different goals.

Cu(i)-CQDs with zigzag-shaped edges were prepared and used for a highly efficient catalysis of the Huisgen 1,3-dipolar cycloaddition that was made possible owing to their rapid release of Cu(i).

This work developed a multi-layer deep convolution neural network (DCNN) model for predicting the optical properties of carbon dots (CDs), including spectral properties and fluorescence color under ultraviolet irradiation.

The vibration of a cell membrane plays a key role in the regulation of cell shape and the behavior of cells. However, most existing approaches for the measurement of cell vibration require either exogenous modification or sophisticated techniques, and the main challenge lies in developing methods that can monitor membrane vibration of living cells directly. Herein, a noninvasive strategy based on ultrasmall quartz nanopipettes is introduced. With a tip size of less than 100 nm, nanopipettes can be spatially controlled for precision targeting of a specific location on the membrane of single living cells. Surprisingly, by employing a constant voltage, stable cyclic oscillations are observed from the continuous current versus time traces. The time‐domain current can be decomposed into two basic waves: the high‐frequency one indicates the local membrane vibration driven by the electro‐osmotic flow from the nanopipette, whereas the low‐frequency one indicates the natural frequency of the whole cell. This provides a simple but reliable method to test local and global membrane vibration of single living cells simultaneously with little damage, which provides a tool for the quantification of drugs, disease, or mutations of the cell structure.

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In this work, we design sticky, furry and fluorescent “wool-balls” based on p-benzoquinone/ethylenediamine polymer nanoclusters, which provide a convenient, fast labeling strategy for the imaging of cell surface sialic acids.