Surface chemistry of alanine on Ni{111}

The adsorption of L-alanine on Ni{111} has been studied as a 10 model of enantioselective heterogeneous catalysts. Synchrotron-based X-ray 11 photoelectron spectroscopy and near-edge X-ray absorption fine structure 12 (NEXAFS) spectroscopy were used to determine the chemical state, bond 13 coordination, and out-of-plane orientation of the molecule on the surface. 14 Alanine adsorbs in anionic and zwitterionic forms between 250 and ≈320 K. 15 NEXAFS spectra exhibit a strong angular dependence of the π* resonance 16 associated with the carboxylate group, which is compatible with two distinct 17 orientations with respect to the surface corresponding to the bidentate and 18 tridentate binding modes. Desorption and decomposition begin together at 19 ≈300 K, with decomposition occurring in a multistep process up to ≈450 K. Comparison with previous studies of amino acid 20 adsorption on metal surfaces shows that this is among the lowest decomposition temperatures found so far and lower than typical 21 temperatures used for hydrogenation reactions where modified Ni catalysts are used.

Quantitative structure of an acetate dye molecule analogue at the TiO2- acetic acid interface

The positions of atoms in and around acetate molecules at the rutile TiO2(110) interface with 0.1 M acetic acid have been determined with a precision of ±0.05 Å. Acetate is used as a surrogate for the carboxylate groups typically employed to anchor monocarboxylate dye molecules to TiO2 in dye-sensitised solar cells (DSSC). Structural analysis reveals small domains of ordered (2 x 1) acetate molecules, with substrate atoms closer to their bulk terminated positions compared to the clean UHV surface. Acetate is found in a bidentate bridge position, binding through both oxygen atoms to two five-fold titanium atoms such that the molecular plane is along the [001] azimuth. Density functional theory calculations provide adsorption geometries in excellent agreement with experiment. The availability of these structural data will improve the accuracy of charge transport models for DSSC.