Capturing the dynamic fluctuations in structure and adsorbate coverage on catalytic surfaces under operating conditions is of critical importance to the identification of active sites and subsequent design of materials for targeted bond activation but remains challenging to achieve both experimentally and computationally. Field ion microscopy achieves such in situ reaction monitoring on single catalytic grains via applied electric fields which ionize atmospheric gases at the surface, providing images of the working catalyst surface. However, such images remain difficult to deconvolute without simplifying assumptions. Here, we use density functional theory to probe the mechanism for field ionization of a series of imaging gases (O₂, N₂, and NO) over oxygen, nitrogen, sulfur, and carbon covered Pd(331). From this dataset of field ionization systems, we determined that the primary factors affecting field ionization are the relative energy levels for the imaging gas’s occupied states and the surface’s unoccupied states, both of which are tunable through choice of imaging gas and the presence of adsorbates, respectively. Using such quantitative descriptors of the electronic accessibility of both the imaging gas and adsorbate covered surface, we develop a predictive tool for the rapid assessment of any system’s field ionization potential. Overall, this work provides fundamental insight into the field ionization mechanism and presents an easy-to-use predictive tool that can assist with both the analysis of existing field ion microscopy images and the design of future experiments.

捕获操作条件下催化表面上结构和吸附物覆盖率的动态波动对于活性位点的识别和用于目标键活化的材料的后续设计至关重要，但在实验和计算上仍面临挑战。场离子显微镜通过施加的电场在单个催化颗粒上实现了这种原位反应监测，该电场使表面的大气气体电离，从而提供了工作催化剂表面的图像。然而，在不简化假设的情况下，这样的图像仍然难以去卷积。在这里，我们使用密度泛函理论来探究一系列成像气体（O ₂，N ₂和NO）覆盖在Pd（331）上的氧，氮，硫和碳上。从该场电离系统数据集中，我们确定影响场电离的主要因素是成像气体的占据状态和表面的未占据状态的相对能级，这两者都可以通过选择成像气体和存在吸附物来进行调整，分别。使用成像气体和被吸附物覆盖的表面的电子可及性的这种定量描述符，我们开发了一种预测工具，可快速评估任何系统的场电离势。总的来说，这项工作提供了对现场电离机理的基本见解，并提供了一种易于使用的预测工具，可以帮助分析现有的现场离子显微镜图像和设计未来的实验。