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Updated: Jun 4, 2025

Staining the Cytoplasmic Ca2+ with Fluo-4/AM in Apple Pulp
Published on: November 6, 2021
ICT-based fluorescent nanoparticles for selective cyanide ion detection and quantification in apple seeds
Upendar Reddy Gandra1,2, Rabindranath Lo3, Praveen B Managutti1,4
1Department of Chemistry, Khalifa University of Science and Technology, Abu Dhabi, P.O. Box 127788, United Arab Emirates. upreddygandra@gmail.com.
Abstract:
In this report, we successfully engineered a novel probe based on an acceptor-donor-acceptor (A-D-A) architecture featuring dicyanovinyl-substituted thieno[3,2-b]thiophene, termed DCVTT. The designed probe self-assembles into luminous nanoparticles (DCVTT NPs) upon introducing mixed aqueous solutions. These fluorescent nanostructures served as a ratiometric probe for detecting cyanide (CN-) ions in aqueous-based environments, owing to the robust Intramolecular Charge Transfer (ICT) characteristics of DCVTT. The A-D-A substituents in DCVTT significantly enhanced ICT behavior by promoting more efficient electron transfer between the donor and acceptor groups. This improved electron transfer process leads to heightened sensitivity in detection applications. In the case of cyanide (CN) sensing, this enhanced ICT behavior manifests as a strong colorimetric response, allowing for a visible color change before and after interaction with cyanide. Speculation regarding the interaction mechanism between DCVTT and CN- is proposed based on the findings of various experimental analyses. The detection limit (LOD) for DCVTT in identifying CN- is 0.83 nM, significantly lower than the CN- concentration thresholds deemed safe by the World Health Organization (WHO) and the United States Environmental Protection Agency (EPA). Time-Dependent Density Functional Theory (TD-DFT) has been utilized to theoretically analyze the optical properties of DCVTT both before and after the introduction of the CN- ions. A paper-based test strip was developed to demonstrate its practical application to enable efficient qualitative CN- detection by visual inspection. Furthermore, this sensing platform demonstrates highly accurate quantitative detection of CN- in apple seeds. No prior reports have utilized fluorescence techniques to estimate apple seeds' CN levels.

