Plasmonic Mediated Atomically Engineered 2D Aluminium Quasicrystals for Dopamine Biosensing

TL;DR

This paper introduces a novel plasmonic 2D aluminium quasicrystal sensor utilizing SSPM for sensitive, label-free dopamine detection, offering a rapid and scalable method for medical diagnostics of neurodegenerative diseases.

Contribution

It presents a new SSPM-based sensing technique combined with 2D aluminium quasicrystals for effective dopamine detection, integrating experimental and DFT simulation analyses.

Findings

Detects dopamine at 1100 ppb with high sensitivity

Demonstrates the effectiveness of SSPM in biosensing

Provides a scalable, rapid diagnostic approach

Abstract

Dopamine levels are linked to neurological illnesses like Parkinson's and Alzheimer's. Thus, reliable and sensitive detection of dopamine is crucial for early diagnosis and surveillance of neurodegenerative diseases. Non-noble-metal-based nanomaterials are ideal for light-mediated sensing of organic molecules. Among these, 2D quasicrystal structures consisting of five elements, namely Al70Co10Fe5Ni10Cu5, provide active sites due to their high surface-to-volume ratio, making them excellent for organic chemical sensing. Here, we propose a simple, label-free, spatial self-phase-modulation (SSPM)-based sensing method in liquid form. SSPM-based time evolution of the diffraction pattern for varied mixing levels of a 1100 ppb dopamine solution shows a shift in the active 2D Al QC solution. The 1100 ppb solution shows a distinct value, indicating a change in the nonlinear refractive index. Time-evolution analysis is used to calculate sensitivities to changes in the nonlinear refractive index and time constant. The SPR-activated 2D Al QC nanostructure is used to demonstrate dopamine sensing and to perform qualitative and quantitative evaluations. The SSPM-based sensing has been further compared with other optical-based sensing methods such as Raman spectroscopy, UV-Vis spectroscopy, and FTIR spectroscopy. The experimental observations are also explained using DFT-based simulations. The current SSPM method can be used for rapid, large-scale medical diagnostics.