Engineering FeOOH/Fe 2 O 3 @Carbon Interfaces With Biomass-Derived Carbon Nanodot/Iron Colloids for Efficient Redox-Modulated Dopamine Voltammetric Detection.
Meseret Ethiopia GuyeRichard Appiah-NtiamoahMintesinot Dessalegn DabaroHern KimPublished in: Chemistry, an Asian journal (2024)
The Fe 2+ /Fe 3+ redox couple is effective for voltammetric detection of trace dopamine (DA). However, achieving adequate concentrations with high electroactive surface area (ECSA), DA affinity, and fast interfacial charge transfer is challenging. Consequently, most reported Fe-based sensors have a high nanomolar range detection limit (LOD). Herein, we address these limitations by manipulating the phase and morphology of FeOOH/Fe 2 O 3 heterojunctions anchored on sp 2 -carbon. FeOOH/Fe 2 O 3 is synthesized by variable temperature aging of unique Fe 5 H 9 O 15 /Fe 2 O 3 @sp 2 -carbon colloidal nanoparticles, which form via chelation between biomass-derived carbon nanodots (CNDs) and Fe 2+ ions. At 27 °C and 120 °C, Fe 5 H 9 O 15 /Fe 2 O 3 @sp 2 -carbon transforms into β-FeOOH/Fe 2 O 3 nanoparticles and α-FeOOH/Fe 2 O 3 nanosheet, respectively. The β-FeOOH/Fe 2 O 3 interface exhibits higher e g orbital electron occupancy than α-FeOOH/Fe 2 O 3 , thereby facilitating oxygen adsorption and the generation of Fe 2+ /Fe 3+ sites near the polarization potential of DA. This facilitates interfacial electron transfer between Fe 3+ and DA. Moreover, its nanoparticle morphology enhances ECSA and DA adsorption compared to α-FeOOH/Fe 2 O 3 nanosheets. With a LOD of ~3.11 nM, β-FeOOH/Fe 2 O 3 surpasses the lower threshold in humans (~10 nM) and matches noble-metal sensors. Furthermore, it exhibits selective detection of DA over 10 biochemicals in urine. Therefore, the β-FeOOH/Fe 2 O 3 @sp 2 -C platform holds promise as a low-cost, easy-to-synthesize, and practical voltammetric DA monitor.
Keyphrases
- aqueous solution
- metal organic framework
- electron transfer
- low cost
- visible light
- loop mediated isothermal amplification
- label free
- photodynamic therapy
- metabolic syndrome
- reduced graphene oxide
- machine learning
- quantum dots
- molecular dynamics simulations
- climate change
- gold nanoparticles
- mass spectrometry
- molecularly imprinted
- sensitive detection