Manganese(I)-Catalyzed Access to Enantioenriched Chiral Aziridine Phosphines.

Herein, we present the first catalytic asymmetric nucleophilic addition of diarylphosphines to 2H-azirines, facilitated by a chiral Mn(I) complex. This method not only provides access to novel class of derivatives of the aziridine core - a structural motif recognized for its antitumor and antibacterial properties - but also introduces a phosphine moiety alongside the generation of an NH moiety within a strained three-membered ring. The discovery of this new Mn(I) complex that both enables the reaction and induces stereoselectivity is pivotal, as it underscores the significant potential of this earth-abundant metal in advancing asymmetric catalysis.

"Turn-off" fluorescent sensor for highly sensitive and specific simultaneous recognition of 29 famous green teas based on quantum dots combined with chemometrics.

Fluorescent "turn-off" sensors based on water-soluble quantum dots (QDs) have drawn increasing attention owing to their unique properties such as high fluorescence quantum yields, chemical stability and low toxicity. In this work, a novel method based on the fluorescence "turn-off" model with water-soluble CdTe QDs as the fluorescent probes for differentiation of 29 different famous green teas is established. The fluorescence of the QDs can be quenched in different degrees in light of positions and intensities of the fluorescent peaks for the green teas.

Detection of unexpected frauds: Screening and quantification of maleic acid in cassava starch by Fourier transform near-infrared spectroscopy.

Fourier transform near-infrared (FT-NIR) spectroscopy and chemometrics were adopted for the rapid analysis of a toxic additive, maleic acid (MA), which has emerged as a new extraneous adulterant in cassava starch (CS). After developing an untargeted screening method for MA detection in CS using one-class partial least squares (OCPLS), multivariate calibration models were subsequently developed using least squares support vector machine (LS-SVM) to quantitatively analyze MA. As a result, the OCPLS model using the second-order derivative (D2) spectra detected 0.

"Turn-off" fluorescent data array sensor based on double quantum dots coupled with chemometrics for highly sensitive and selective detection of multicomponent pesticides.

As a popular detection model, the fluorescence "turn-off" sensor based on quantum dots (QDs) has already been successfully employed in the detections of many materials, especially in the researches on the interactions between pesticides. However, the previous studies are mainly focused on simple single track or the comparison based on similar concentration of drugs. In this work, a new detection method based on the fluorescence "turn-off" model with water-soluble ZnCdSe and CdSe QDs simultaneously as the fluorescent probes is established to detect various pesticides.