Unveiling with\nDensity Functional Theory the Optical\nProperty Variations of Three Kinds of Graphene for Acetaminophen Sensor\nDesign

Understanding the interactions between molecules and\nsensing elements\nis crucial to improving sensors. We present one step toward getting\ncloser to the breach between theory and empirical sensor development.\nThrough density functional theory (DFT) calculations, we explored\nthe changes in some optical properties of pristine graphene (G), graphene\noxide (GO), and reduced graphene oxide (rGO) interacting with one\nmolecule of acetaminophen (APAP). The main goal is to unveil which\ngrapheneG, GO, and rGOworks better as a substrate\nto detect APAP for sensor applications based on UV/vis and near-infrared\nabsorption, refractive index changes, and plasmon resonances. For\nthis effort, we used Quantum ESPRESSO software. We calculated each\nsupercell’s adsorption energy and recovery time containing\nthe APAP and one graphene variant. Afterward, we calculated the optical\nabsorption, refractive index, reflectivity, and electron energy loss\nspectroscopy (EELS), a technique to identify the material’s\nplasmons. Then, we analyzed the changeovers in the optical properties\nmentioned for each graphene layer with and without APAP. We found\nthat G works for UV/vis and plasmon sensors operating in blue and\nUV–C regions; GO has the highest performance range in UV/vis\nand plasmonic sensors operating in UV–C; rGO has the highest\nperformance range in UV/vis sensors working on near-infrared and UV–C.\nAdditionally, rGO plasmonic sensors present an “oscillation\nof percentage variations” from visible to UV. Our study offers\na strategy for creating a map to select the best substrate to develop\nselective APAP optical sensors.