Qian Jin, Ye Yifan, Yang Hao, Yano Junko, Crumlin Ethan J, Goddard William A
Joint Center for Artificial Photosynthesis , California Institute of Technology , Pasadena , California 91125 , United States.
Materials and Process Simulation Center , California Institute of Technology , Pasadena , California 91125 , United States.
J Am Chem Soc. 2019 May 1;141(17):6946-6954. doi: 10.1021/jacs.8b13672. Epub 2019 Apr 18.
The interaction of water with metal surfaces is at the heart of electrocatalysis. But there remain enormous uncertainties about the atomistic interactions at the electrode-electrolyte interface (EEI). As the first step toward an understanding of the EEI, we report here the details of the initial steps of HO adsorption and complex formation on a Ag(111) surface, based on coupling quantum mechanics (QM) and ambient-pressure X-ray photoelectron spectroscopy (APXPS) experiments. We find a close and direct comparison between simulation and experiment, validated under various isotherm and isobar conditions. We identify five observable oxygen-containing species whose concentrations depend sensitively on temperature and pressure: chemisorbed O* and OH*, HO* stabilized by hydrogen bond interactions with OH* or O*, and multilayer HO*. We identify the species experimentally by their O 1s core-level shift that we calculate with QM along with the structures and free energies as a function of temperature and pressure. This leads to a chemical reaction network (CRN) that we use to predict the time evolution of their concentrations over a wide range of temperature (298-798 K) and pressure conditions (10-1 Torr), which agree well with the populations determined from APXPS. This multistep simulation CRN protocol should be useful for other heterogeneous catalytic systems.
水与金属表面的相互作用是电催化的核心。但电极 - 电解质界面(EEI)处的原子相互作用仍存在巨大的不确定性。作为理解EEI的第一步,我们在此报告基于量子力学(QM)与常压X射线光电子能谱(APXPS)实验耦合,HO在Ag(111)表面吸附及络合物形成初始步骤的详细情况。我们发现在各种等温线和等压条件下得到验证的模拟与实验之间存在紧密且直接的对比。我们识别出五种可观测的含氧物种,其浓度对温度和压力敏感:化学吸附的O和OH、通过与OH或O的氢键相互作用而稳定的HO以及多层HO。我们通过QM计算的O 1s核心能级位移以及作为温度和压力函数的结构和自由能,从实验上识别这些物种。这导致了一个化学反应网络(CRN),我们用它来预测在广泛的温度(298 - 798 K)和压力条件(10 - 1 Torr)下它们浓度随时间的演变,这与由APXPS确定的数量吻合良好。这种多步模拟CRN协议对其他多相催化系统应该是有用的。