Rapid and efficient detection of acetone using C₂₀-based nanostructures: A novel non-invasive strategy for diabetes assay through DFT/TD-DFT calculations

The urgent demand for non-invasive, rapid diabetes detection has inspired this study, which investigates C₂₀ fullerene and its doped derivatives (BeC₁₉, MgC₁₉, and CaC₁₉) as nanostructured sensors for acetone (Ac), a biomarker in exhaled breath. Computational analysis using density functional theory (DFT) and time-dependent DFT (TD-DFT) reveals CaC19 as the most promising candidate, with the highest dipole moment (29.65 D), a substantial UV–visible redshift (580 nm), and rapid recovery time (4.4 × 10⁻¹¹ s). This sensor demonstrates superior sensitivity and efficiency for detecting acetone via visible colorimetric changes, offering a fast and reusable solution for real-time diabetes monitoring. These findings highlight Ca-doped C₂₀ fullerene as a promising candidate for non-invasive, rapid diabetes monitoring.