d-Glucose Adsorption on the TiO2 Anatase (100) Surface: A Direct Comparison Between Cluster-Based and Periodic Approaches

Abstract

Titanium dioxide (TiO2) has been extensively studied as a suitable material for a wide range of fields including catalysis and sensing. For example, TiO2-based nanoparticles are active in the catalytic conversion of glucose into value-added chemicals, while the good biocompatibility of titania allows for its application in innovative biosensing devices for glucose detection. A key process for efficient and selective biosensors and catalysts is the interaction and binding mode between the analyte and the sensor/catalyst surface. The relevant features regard both the molecular recognition event and its effects on the nanoparticle electronic structure. In this work, we address both these features by combining two first-principles methods based on periodic boundary conditions and cluster approaches (CAs). While the former allows for the investigation of extended materials and surfaces, CAs focus only on a local region of the surface but allow for using hybrid functionals with low computational cost, leading to a highly accurate description of electronic properties. Moreover, the CA is suitable for the study of reaction mechanisms and charged systems, which can be cumbersome with PBC. Here, a direct and detailed comparison of the two computational methodologies is applied for the investigation of d-glucose on the TiO2 (100) anatase surface. As an alternative to the commonly used PBC calculations, the CA is successfully exploited to characterize the formation of surface and subsurface oxygen vacancies and to determine their decisive role in d-glucose adsorption. The results of such direct comparison allow for the selection of an efficient, finite-size structural model that is suitable for future investigations of biosensor electrocatalytic processes and biomass conversion catalysis.</p>Titanium dioxide (TiO2) has been extensively studied as a suitable material for a wide range of fields including catalysis and sensing. For example, TiO2-based nanoparticles are active in the catalytic conversion of glucose into value-added chemicals, while the good biocompatibility of titania allows for its application in innovative biosensing devices for glucose detection. A key process for efficient and selective biosensors and catalysts is the interaction and binding mode between the analyte and the sensor/catalyst surface. The relevant features regard both the molecular recognition event and its effects on the nanoparticle electronic structure. In this work, we address both these features by combining two first-principles methods based on periodic boundary conditions and cluster approaches (CAs). While the former allows for the investigation of extended materials and surfaces, CAs focus only on a local region of the surface but allow for using hybrid functionals with low computational cost, leading to a highly accurate description of electronic properties. Moreover, the CA is suitable for the study of reaction mechanisms and charged systems, which can be cumbersome with PBC. Here, a direct and detailed comparison of the two computational methodologies is applied for the investigation of d-glucose on the TiO2 (100) anatase surface. As an alternative to the commonly used PBC calculations, the CA is successfully exploited to characterize the formation of surface and subsurface oxygen vacancies and to determine their decisive role in d-glucose adsorption. The results of such direct comparison allow for the selection of an efficient, finite-size structural model that is suitable for future investigations of biosensor electrocatalytic processes and biomass conversion catalysis.</p>