Exsolution of transition metals from host perovskites has emerged as a unique synthesis method for designing catalysts for energy applications. Here, using accurate first-principles density functional theory, coupled with an ab initio steered molecular dynamics and umbrella sampling framework, we rationalize both the energetics as well as the dynamics of the exsolution process of a quintessential system: Pt-doped ATiO₃ (A = Ca/Sr/Ba) perovskites and identify the major driving forces for Pt exsolution. From the developed ab initio thermodynamic framework, we find that Pt exsolution from ATiO₃ (A = Ca/Sr/Ba) perovskites has a distinct host-perovskite facet dependence and likely proceeds through sub-surface vacancy formation followed by diffusion of the doped Pt to the surface of the host perovskite. The molecular dynamics simulations reveal that the exsolution process has a clear temperature and host-perovskite dependence, establishing that only specific dopant-host perovskite combinations at favorable thermophysical conditions result in the catalyst with the novel properties. This opens new paths for the predictive synthesis of intelligent catalysts.

中文翻译：

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使用第一性原理模拟ATiO ₃钙钛矿中Pt的溶出（A = Ca / Sr / Ba）

从主体钙钛矿中提取过渡金属已经成为设计能源应用催化剂的独特合成方法。在这里，我们使用精确的第一原理密度泛函理论，再加上从头算起的分子动力学和伞形采样框架，我们对一个典型系统的能量学和解离过程的动力学进行了合理化：掺Pt的ATiO ₃（A = Ca / Sr / Ba）钙钛矿，并确定Pt释放的主要驱动力。从发达的从头算热力学框架，我们发现ATiO _3的Pt释放（A = Ca / Sr / Ba）钙钛矿具有明显的主体-钙钛矿小平面依赖性，并且可能通过形成表面下的空位，然后将掺杂的Pt扩散到主体钙钛矿的表面进行。分子动力学模拟表明解离过程具有明确的温度和主体-钙钛矿的依赖性，从而确定只有在有利的热物理条件下特定的掺杂剂-主体钙钛矿的组合才能产生具有新颖性质的催化剂。这为智能催化剂的预测合成开辟了新途径。