Unveiling with Density Functional Theory the Optical Property Variations of Three Kinds of Graphene for Acetaminophen Sensor Design

Understanding the interactions between molecules and sensing elements is crucial to improving sensors. We present one step toward getting closer to the breach between theory and empirical sensor development. Through density functional theory (DFT) calculations, we explored the changes in some optical properties of pristine graphene (G), graphene oxide (GO), and reduced graphene oxide (rGO) interacting with one molecule of acetaminophen (APAP). The main goal is to unveil which graphene-G, GO, and rGO-works better as a substrate to detect APAP for sensor applications based on UV/vis and near-infrared absorption, refractive index changes, and plasmon resonances. For this effort, we used Quantum ESPRESSO software. We calculated each supercell's adsorption energy and recovery time containing the APAP and one graphene variant. Afterward, we calculated the optical absorption, refractive index, reflectivity, and electron energy loss spectroscopy (EELS), a technique to identify the material's plasmons. Then, we analyzed the changeovers in the optical properties mentioned for each graphene layer with and without APAP. We found that G works for UV/vis and plasmon sensors operating in blue and UV-C regions; GO has the highest performance range in UV/vis and plasmonic sensors operating in UV-C; rGO has the highest performance range in UV/vis sensors working on near-infrared and UV-C. Additionally, rGO plasmonic sensors present an "oscillation of percentage variations" from visible to UV. Our study offers a strategy for creating a map to select the best substrate to develop selective APAP optical sensors.