Dynamically driven rutile-based acidic oxygen evolution electrocatalysts beyond stationary efficiency (DaCapo)

项目“DaCapo”将研究和测试从动态共振理论(DRT)中得出的一个基本假设，即在周期性驱动和静态操作条件下，时间平均催化性能收益的可行性。DRT假说将利用金红石模型和纳米氧化物催化剂在动态电极驱动下的电催化析氧反应(OER)，从催化活性、稳定性和效率方面进行验证和力学分析。这种方法的关键原子学思想是在更高的阴极电极电位下周期性地优先在表面填充活性中间体，然后在更高的阳极电极电位下快速生成产物。因此，在特征共振条件下，当施加的参数变化与固有催化时间尺度匹配时，这两个区域之间的周期性切换可以提高整体的时间平均反应速度和效率。我们将在原子洞察明确定义的催化模型表面和真实催化剂材料的活性中心和活性表面相的动力学以及它们的动态行为的多尺度模拟之间建立桥梁，在强迫振荡操作的影响下以金红石型酸性OER催化剂(IrO2，RuO2，混合(Ru-Ir-Ti)O2)为例。我们将探索酸性条件下OER中催化活性动态共振态的存在、机制和开发，包括i)基于超高真空和原位表面科学方法(光电子能谱、振动光谱)在单晶和薄膜模型电极(Hofmann)上的原位表面科学方法(光电子能谱、振动光谱)，以阐明动态电化学条件(DEC)下的表面物种数量；ii)计算研究，包括密度泛函理论、动态动力学蒙特卡罗(DKMC)和耦合到电化学系统的数值模型(HESS)来预测DEC对OER活性的影响。将利用从头算分子动力学计算开关瞬变过程中中间体表面的光谱特征，以帮助指定实验光谱；iii)对模型薄膜和更真实的纳米粒子电极进行电催化研究，利用实时差分电化学质谱仪(DEMS)和操作手动势X射线吸收光谱监测和关联DEC(Strasser)下的产品形成速率、表面空穴电荷和法拉第产品效率。在DaCapo获得的实验数据和模拟模型将与SPP2080中协作基团的宏观建模相关，目的是通过多尺度理解来理解和实现OER电催化中的动态控制应用。

The project “DaCapo” will study and test a fundamental hypothesis derived from Dynamic Resonance Theory (DRT) as to the feasibility of time-averaged catalytic performance benefits in periodically driven versus stationary operation regimes. The DRT hypothesis will be tested and mechanistically analyzed in terms of catalytic reactivity, stability, and efficiency using the electrocatalytic oxygen evolution reaction (OER) on rutile-based model and nanostructured oxide catalysts under dynamically driven electrode potentials. The key atomistic idea of this approach is to periodically and preferentially populate the surface with reactive intermediates at more cathodic electrode potentials, followed by rapid product formation at more anodic electrode potentials. As a result, at characteristic resonance conditions, where applied parameter variations match intrinsic catalytic time scales, the periodic switching between these two regimes can enhance the overall time-averaged reaction rate and efficiency. We will form a bridge between atomic insights into the dynamics of active site and active surface phases of well-defined catalytic model surfaces and real catalyst materials and multiscale simulations of their dynamic behavior, exemplified by rutile based acidic OER catalyst (IrO2, RuO2, mixed (Ru-Ir-Ti)O2) under the influence of forced oscillatory operation. We will explore the existence, mechanisms, and exploitation of catalytically active dynamic resonant states in the OER under acidic conditions using a three-branched combination of i) ultrahigh vacuum-based and in situ surface science methods (photoemission, vibrational spectroscopies) on single crystal and thin film model electrodes (Hofmann) to elucidate the population of surface species under dynamic electrochemical conditions (DEC); ii) computational studies including density functional theory, dynamic kinetic Monte Carlo (DKMC) and coupling to a numerical model of the electrochemical system (Hess) to predict the influence of DEC on OER activity. Spectroscopic signatures of intermediates on the surface during switching transients will be computed with Ab-initio Molecular Dynamics to assist in the assignment of experimental spectra; iii) electrocatalytic studies on model thin-film and more realistic nanoparticle electrodes employing real-time Differential Electrochemical Mass Spectrometry (DEMS) and operando potentiodynamic X-ray absorption spectroscopy to monitor and correlate product formation rates, surface hole charge, and Faradaic product efficiencies under DEC (Strasser). The experimental data and simulation models obtained in DaCapo will be placed in relation to macroscale modelling of collaborating groups in the SPP2080 with the goal to understand and enable application of dynamic control in OER electrocatalysis through a multiscale understanding.