A soft-chemistry assisted strong metal-support interaction on a designed plasmonic core-shell photocatalyst for enhanced photocatalytic hydrogen production.

Engineering photocatalysts based on gold nanoparticles (AuNPs) has attracted great attention for the solar energy conversion due to their multiple and unique properties. However, boosting the photocatalytic performance of plasmonic materials for H2 generation has some limitations. In this study, we propose a soft-chemistry method for the preparation of a strong metal-support interaction (SMSI) to enhance the photocatalytic production of H2. The TiO2 thin overlayer covering finely dispersed AuNPs (forming an SMSI) boosts the photocatalytic generation of hydrogen, compared to AuNPs deposited at the surface of TiO2 (labelled as a classical system). The pathway of the charge carriers' dynamics regarding the system configuration is found to be different. The photogenerated electrons are collected by AuNPs in a classical system and act as an active site, while, unconventionally, they are injected back in the titania surface for an SMSI photocatalyst making the system highly efficient. Additionally, the adsorption energy of methanol, theoretically estimated using the density functional theory (DFT) methodology, is lower for the soft-chemistry SMSI photocatalyst accelerating the kinetics of photocatalytic hydrogen production. The SMSI obtained by soft-chemistry is an original concept for highly efficient photocatalytic materials, where the photon-to-energy conversion remains a major challenge.

Effect of nitrogen-doping configuration in graphene on the oxygen reduction reaction.

In this study, we investigate the oxygen reduction reaction (ORR) reactivity of nitrogen-doped graphene by using density functional theory (DFT), a computational quantum mechanical technique. Four doping configurations and five models were comprehensively studied: quaternary nitrogen (NQ), pyrrolic nitrogen (N5), two forms of pyridinic nitrogen (N6, N6nH) and three-pyridinic nitrogen (3N6). Models for possible sites during each step of ORR were set up and visualized to provide a platform to calculate the free energy of the reaction pathway to determine the suitability of each doping scenario. Associative mechanisms were displayed by all models except N5, which showed dissociative mechanism. The calculated free energy pathways demonstrate that the ranking of the reactivity for ORR by different nitrogen configurations from most reactive to least reactive is N6, NQ, N6nH, 3N6, and N5. Spin density and charge density aid in describing levels of reactivity.