Multivariate Analysis of pH-Dependent Carbon Dots Sensitivity for Fe³⁺ Ions Detection Using UV-VIS Spectroscopy

Fluorescent carbon dots (CDs) have become a potent and adaptable nanomaterial in recent years for the sensitive and specific detection of heavy metal ions. Ferric ion (Fe³⁺) is one of the most damaging metal ions that can infiltrate the human body and the environment. In this study, blue-emitting carbon dots (CDs) were successfully synthesized from lemon juice using a hydrothermal process. The sensitivity of CDs to Fe³⁺ ions was examined using various concentrations of Fe³⁺ (0-400 µM) under different pH conditions (3, 5, 7, 9, 11, and 13) by measuring UV-Vis absorbance at 200-700 nm. The findings showed that the interaction between CDs and Fe³⁺ is significantly influenced by pH, resulting in varying absorbance enhancement responses. To get more profound insights into this pH-dependent performance, multivariate analysis techniques, including principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares regression (PLSR) were utilized. By combining these techniques with experimental data, significant correlations between pH levels, $\pi -\pi _{}^{\ast }$ and $n-\pi _{}^{\ast }$ electronic transitions of CDs, and Fe³⁺ sensing performance were identified. According to the PLSR model, pH 7 is ideal for real-world uses since it offers the optimum balance between Fe³⁺ solubility and CDs sensing capabilities, closely matching environmental and physiological conditions. This work contributes to the knowledge of CDs-based sensing mechanisms and emphasizes the value of multivariate analysis in boosting material performance for real-world applications in the biochemical and environmental domains.