Chemical sensing based on Carbon Quantum Dots for food additives analysis

Abstract

Fluorescent chemical sensing platforms have been applied to detect different types of analytes, including food additives. Among its advantages, the production with low cost and high sensitivity in quality control stands out, following the maximum limits recommended by competent organizations. These sensors become more viable when they are based on 0D nanostructured materials known as Carbon Quantum Dots (CQDs). In the literature, there are still few works that incorporate CQDs in a solid phase, to develop a field analysis sensor with high sensitivity and selectivity. Given this scenario, this thesis results from innovative research in the area of chemical sensors, whose general objective is to develop sensing platforms and a device for analyzing food safety in industrialized products. The first work consisted of the synthesis and characterization of CQDs obtained from a natural carbon source (seeds of the plant Caelsalpinia pulcherrima), with subsequent application of chemometric methods of multivariate analysis to identify five food additives in canned olives. The nanoparticles obtained were labeled as FM-CDs and the results showed a high sensitivity of the proposed strategy, which detected concentrations as low as 252 ng mL-1 of sodium benzoate. In addition, we obtained a classification with 100% accuracy, based on the algorithm Linear Discriminant Analysis (LDA). With the first work completed, the next step was to obtain new CQDs, with a higher quantum yield (QY) to be applied in a field analysis sensor. Thus, CQDs were synthesized by the hydrothermal route from citric acid, boric acid and branched polyethyleneimine, which were named B,N-Cdot. The results showed that these nanoparticles with QY equal to 44.3% were able to detect nitrite ions with high selectivity. The next step consisted of impregnating the B,N-Cdot in polyvinyl alcohol (PVA) polymer matrix to develop a nitrite ion field analysis sensor. The nanocomposite was used together with the PhotoMetrix application and was able to quantify the analyte. Therefore, this thesis presents results that prove the great potential of CQDs in the field of chemical sensing and in the development of simple devices that enable quality control in the food industry.