Detecting the body odor volatilomes (BOVs) represents a crucial step in comprehending its implications for human social interactions and healthcare. This work explores a novel mucin-based receptor functionalized graphene-based sensor material for BOVs detection through atomistic simulations. The density functional theory (DFT) investigation involves calculating the binding features of analyte-substrate interactions, including binding energy and charge transfer. These electronic properties characterize the sensing mechanisms and yield synergistically sensor signal response in the end, which could be estimated by the work function change before and after BOVs adsorption. This research enhances the fundamental understanding of the analyte-receptor interactions and potentially facilitates the selection and optimization of the receptors in pursuit of high responsiveness and excellent discrimination capabilities.
Li Chen obtained his Bachelor degree in mechanical engineering at Sichuan University in 2018. In the same year, he joined TU Dresden for the Diplom degree in power engineering. During his study, he worked as SHK and WHK in the topic of heat transport in polymers and electronic properties of 2D-materials for gas adsorption, using Molecular dynamics (MD) and density functional theory (DFT) simulations. In 2023, he joined Prof. Cuniberti’s chair as a PHD student under supervision of Dr. Gutierrez and Dr. Dianat with the topic of odor molecules sensing by receptor-functionalized graphene.
Detecting the body odor volatilomes (BOVs) represents a crucial step in comprehending its implications for human social interactions and healthcare. This work explores a novel mucin-based receptor functionalized graphene-based sensor material for BOVs detection through atomistic simulations. The density functional theory (DFT) investigation involves calculating the binding features of analyte-substrate interactions, including binding energy and charge transfer. These electronic properties characterize the sensing mechanisms and yield synergistically sensor signal response in the end, which could be estimated by the work function change before and after BOVs adsorption. This research enhances the fundamental understanding of the analyte-receptor interactions and potentially facilitates the selection and optimization of the receptors in pursuit of high responsiveness and excellent discrimination capabilities.
Li Chen obtained his Bachelor degree in mechanical engineering at Sichuan University in 2018. In the same year, he joined TU Dresden for the Diplom degree in power engineering. During his study, he worked as SHK and WHK in the topic of heat transport in polymers and electronic properties of 2D-materials for gas adsorption, using Molecular dynamics (MD) and density functional theory (DFT) simulations. In 2023, he joined Prof. Cuniberti’s chair as a PHD student under supervision of Dr. Gutierrez and Dr. Dianat with the topic of odor molecules sensing by receptor-functionalized graphene.
