Direct Readout of Homo- vs Heterochiral Ligand Shell of Quantum Dots.

The chiroptical activity of various semiconductor inorganic nanocrystalline materials has typically been tested using circular dichroism or circularly polarized luminescence. Herein, we report on a high-throughput screening method for identifying and differentiating chiroptically active quantum-sized ZnO crystals using Raman spectroscopy combined with principal component analysis. ZnO quantum dots (QDs) coated by structurally diverse homo- and heterochiral aminoalcoholate ligands (cis- and trans-1-amino-2-indanolate, 2-amino-1-phenylethanolate, and diphenyl-2-pyrrolidinemethanolate) were prepared using the one-pot self-supporting organometallic procedure and then extensively studied toward the identification of specific Raman fingerprints and spectral variations. The direct comparison between the spectra demonstrates that it is very difficult to make definite recognition and identification between QDs coated with enantiomers based only on the differences in the respective Raman bands' position shifts and their intensities. However, the applied approach involving the principal component analysis performed on the Raman spectra allows the simultaneous differentiation and identification of the studied QDs. The first and second principal components explain 98, 97, 97, and 87% of the variability among the studied families of QDs and demonstrate the possibility of using the presented method as a qualitative assay. Thus, the reported multivariate approach paves the way for simultaneous differentiation and identification of chirotopically active semiconductor nanocrystals.

SERS Signature of SARS-CoV-2 in Saliva and Nasopharyngeal Swabs: Towards Perspective COVID-19 Point-of-Care Diagnostics.

In this study, the intrinsic surface-enhanced Raman spectroscopy (SERS)-based approach coupled with chemometric analysis was adopted to establish the biochemical fingerprint of SARS-CoV-2 infected human fluids: saliva and nasopharyngeal swabs. The numerical methods, partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC), facilitated the spectroscopic identification of the viral-specific molecules, molecular changes, and distinct physiological signatures of pathetically altered fluids. Next, we developed the reliable classification model for fast identification and differentiation of negative CoV(-) and positive CoV(+) groups. The PLS-DA calibration model was described by a great statistical value-RMSEC and RMSECV below 0.3 and R2cal at the level of ~0.7 for both type of body fluids. The calculated diagnostic parameters for SVMC and PLS-DA at the stage of preparation of calibration model and classification of external samples simulating real diagnostic conditions evinced high accuracy, sensitivity, and specificity for saliva specimens. Here, we outlined the significant role of neopterin as the biomarker in the prediction of COVID-19 infection from nasopharyngeal swab. We also observed the increased content of nucleic acids of DNA/RNA and proteins such as ferritin as well as specific immunoglobulins. The developed SERS for SARS-CoV-2 approach allows: (i) fast, simple and non-invasive collection of analyzed specimens; (ii) fast response with the time of analysis below 15 min, and (iii) sensitive and reliable SERS-based screening of COVID-19 disease.

Flexible PET/ITO/Ag SERS Platform for Label-Free Detection of Pesticides.

We show a new type of elastic surface-enhanced Raman spectroscopy (SERS) platform made of poly(ethylene terephthalate) (PET) covered with a layer of indium tin oxide (ITO). This composite is subjected to dielectric barrier discharge (DBD) that develops the active surface of the PET/ITO foil. To enhance the Raman signal, a modified composite was covered with a thin layer of silver using the physical vapor deposition (PVD) technique. The SERS platform was used for measurements of para-mercaptobenzoic acid (p-MBA) and popular pesticides, i.e., Thiram and Carbaryl. The detection and identification of pesticides on the surface of fruits and vegetables is a crucial issue due to extensive use of those chemical substances for plant fungicide and insecticide protection. Therefore, the developed PET/ITO/Ag SERS platform was dedicated to quantitative analysis of selected pesticides, i.e., Thiram and Carbaryl from fruits. The presented SERS platform exhibits excellent enhancement and reproducibility of the Raman signal, which enables the trace analysis of these pesticides in the range up to their maximum residues limit. Based on the constructed calibration curves, the pesticide concentrations from the skin of apples was estimated as 2.5 µg/mL and 0.012 µg/mL for Thiram and Carbaryl, respectively. Additionally, the PET/ITO/Ag SERS platform satisfies other spectroscopic properties required for trace pesticide analysis e.g., ease, cost-effective method of preparation, and specially designed physical properties, especially flexibility and transparency, that broaden the sampling versatility to irregular surfaces.