Is There a Stable Deacon Catalyst? Computational Screening Approach for the Stability of Oxide Catalysts under Harsh Conditions

Under harsh reaction conditions, lack of catalyst stability can impede the large-scale implementation of a technical process. Current computational screening approaches address catalyst activity or selectivity, but screening models that predict catalyst stability under operating conditions are still lacking. Herein, a screening model is presented that can predict catalyst stability under harsh reaction conditions based on the thermodynamic data of bulk phases while accounting for variations in the operating conditions (temperature, gas feed composition, and conversion). It is applied to oxide catalysts for the oxidation of HCl (Deacon reaction), where catalysts can chlorinate irreversibly or leach from the catalyst bed in the form of volatile chlorides and oxychlorides, resulting in loss of catalyst activity. Two numerical descriptors are computed from the thermodynamic data, ranking the oxides according to their stability against chlorination and vaporization, which enables large-scale screening. The underlying computations provide detailed insights on the possible reactions of the catalyst with the gas stream in the form of reaction free energy diagrams. This allows one to identify where the reactor degradation is the most severe and improve the catalyst stability by addressing these stability bottlenecks. For the Deacon reaction, the oxides and chlorides of 66 elements are examined. The two descriptors are empirically found to be largely complementary, which means that most oxides are prone to either chlorination or volatility, with a few exceptions. It is found that both chlorination and volatility are most severe close to the reactor inlet, which suggests that a highly stable catalyst material must be employed at the reactor inlet. The late rare-earth oxychlorides, as well as Nb2O5 and Ta2O5, are identified as promising candidates with high stability in both categories at the reactor inlet. The developed model can be applied to catalytic processes where phase transformations of the catalyst material under operating conditions are the major cause of catalyst deactivation and are in principle applicable to any process that runs at sufficiently high temperatures.在严苛的反应工况下，催化剂稳定性不足会阻碍工艺过程的规模化落地应用。当前的计算筛选方法多聚焦于催化剂活性或选择性，但仍缺乏可预测实际操作条件下催化剂稳定性的筛选模型。本文提出一款筛选模型，可基于体相（bulk phases）热力学数据，同时纳入操作条件（温度、气体进料组成与转化率）的变化，实现严苛反应条件下催化剂稳定性的预测。该模型被应用于氯化氢（HCl）氧化的迪肯反应（Deacon reaction）体系中的氧化物催化剂，此类催化剂可能发生不可逆氯化，或以挥发性氯化物、氯氧化物的形式从催化剂床层浸出，最终导致催化剂活性流失。研究从热力学数据中提取了两项数值描述符，可依据催化剂抗氯化与抗汽化稳定性对氧化物进行排序，从而支撑规模化筛选工作。本研究开展的基础计算以反应自由能图的形式，为催化剂与气流间的潜在反应路径提供了详尽的机理洞察，可用于定位反应器降解最为严重的区域，并通过针对性优化这些稳定性瓶颈来提升催化剂整体稳定性。针对迪肯反应，本研究考察了66种元素对应的氧化物与氯化物。经验分析表明，两项描述符在很大程度上互为补充：绝大多数氧化物仅倾向于发生氯化或挥发过程，仅存在少数例外情况。研究发现，氯化与挥发过程的剧烈程度均在反应器入口附近达到峰值，这提示反应器入口区域必须采用高稳定性的催化剂材料。后期稀土氯氧化物、五氧化二铌（Nb₂O₅）以及五氧化二钽（Ta₂O₅）被确定为极具潜力的候选材料，在反应器入口处同时具备优异的抗氯化与抗挥发稳定性。本研究所开发的模型可应用于以催化剂材料在操作条件下发生相转变为主要失活原因的催化过程，原则上适用于所有在足够高温度下运行的反应体系。