ABSTRACT
We present a new scheme for sensing biomolecules by combining an enzyme hydrogel with a photonic crystal hydrogel layer that responds to ionic strength and pH changes. We demonstrate this unique combination by successfully detecting acetylcholine (ACh) and acetylcholinesterase (AChE) inhibitors. Specifically, the sandwich assembly is composed of layers of photonic crystals and a polyacrylamide hydrogel functionalized with AChE. The photonic crystal film has a red color and turns dark purple within 2-6 minutes of the enzymatic reaction upon analyte addition. This 3D photonic crystal sensor responds to acetylcholine in the 1 nM to 10 µM concentration range (which includes the relevant range of ACh concentrations in human body fluids). Michaelis-Menten kinetics of the enzyme were determined which correlated well with literature data demonstrating the uninhibited reactivity of the immobilized enzyme. Furthermore, the presence of the acetylcholinesterase inhibitor neostigmine at concentrations as low as 1 fM was demonstrated, which is even below the necessary detection limit for clinical diagnostics. We suggest that this novel concept will find its application in clinical diagnostics, for pesticide and nerve agent detection.
ABSTRACT
Reduced graphene oxide (rGO) was investigated as a material for use in chemiresistive gas sensors. The carbon nanomaterial was transferred onto a silicon wafer with interdigital gold electrodes. Spin coating turned out to be the most reliable transfer technique, resulting in consistent rGO layers of reproducible quality. Fast changes in the electrical resistance at a low operating temperature of 85 °C could be detected for the gases NO(2), CH(4) and H(2). Especially upon adsorption of NO(2) the high signal changes allowed a minimum detection of 0.3 ppm (S/N = 3). To overcome the poor selectivity, rGO was chemically functionalized with octadecylamine, or modified by doping with metal nanoparticles such as Pd and Pt, and also metal oxides such as MnO(2), and TiO(2). The different response patterns for six different materials allowed the discrimination of all of the test gases by pattern recognition based on principal component analysis.
