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Developing Multi-Channel Sensor Arrays for Detection and Discrimination of Important Biological Compounds and Environmental Pollutants

Koushkestani, Marjan | 2025

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 58659 (03)
  4. University: Sharif University of Technology
  5. Department: Chemistry
  6. Advisor(s): Hormozinezhad, Mohammad Reza
  7. Abstract:
  8. In the first part of this research, a dual-channel sensor array was designed based on colorimetric and fluorescence responses for the quantification and classification of azinphos-methyl (AZ), oxydimethon-methyl (OX), and thiometon (TM) and acetamiprid (AC). The sensing mechanisms that lead to the generation of colorimetric and fluorescence responses are the aggregation of gold nanoparticles and the inner filter effect phenomenon, respectively. Due to different structures of the target analytes, they interact with gold nanoparticles in different ways and as a result, each of the analytes led to the different degrees of aggregation of gold nanoparticles. In the next step, luminescent components (carbon dots, quantum dots, and fluorescein isothiocyanate) were added, which resulted in unique fluorescence responses due to the spectral overlap of the fluorophores with gold nanoparticles before and after the aggregation. The principal component analysis (PCA) technique along with linear discriminant analysis (LDA) and partial least squares regression (PLS-R) were used for classification and quantification of pesticides, respectively. Linear responses of pesticides were obtained in the concentration range of 10-800, 25-1000, 10-700 and 25-600 ng mL-1 and with detection limits of 7.88, 23.92, 5.80 and 15.24 ng mL-1 for AZ, OX, TM and AC, respectively. The results obtained from the analysis of pesticides and their mixtures in lettuce, cucumber and river water samples ensured the practical application of the sensor array in complex samples
  9. Keywords:
  10. Ratiometric Fluorescence ; Pesticide ; Gold Nanoparticle ; Neuro Transmitter ; Dopamine ; Linear Discriminant Analysis ; Principal Component Analysis (PCA) ; Partial Least Squares (PLS)Regression ; Colorimetric Sensor Array ; Serotonin ; Dual-Channel Sensor Array

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