A simplified temperature swing adsorption (TSA) model is presented for a three-step cycle with open cooling. The model is developed for rapid screening of adsorbents for the recovery of the strongly adsorbed species from a gas mixture. Four indicators—purity, recovery, specific thermal energy demand, and cyclic working capacity—are used to evaluate adsorbent performance. The shortcut model is validated by comparing with results from a detailed adsorption column model and found to be in good agreement: all performance indicators were within 14% of the detailed model predictions. The model is applied for extensive parametric screening of zeolite 13X and 75 other real and hypothetical adsorbents for post-combustion CO₂ capture. The results provide useful insights into the dependence of performance indicators on operating conditions. Each run of the shortcut model solves in less than 0.04 s on a standard desktop computer. The computational speed and accuracy of the model make it ideal for large-scale screening exercises to identify novel adsorbents for gas separation by TSA and for extensive parametric analysis to identify suitable operating conditions.

中文翻译：

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快速筛选吸附剂的新的平衡快捷温度波动吸附模型

提出了一种简化的变温吸附（TSA）模型，用于三步循环开放式冷却。该模型用于快速筛选吸附剂，以从气体混合物中回收强烈吸附的物质。纯度，回收率，特定热能需求和循环工作能力这四个指标用于评估吸附剂的性能。通过与详细的吸附塔模型的结果进行比较来验证快捷方式模型，发现该模型非常一致：所有性能指标均在详细模型预测的14％以内。该模型适用于13X沸石和75种其他真实和假设的吸附剂对燃烧后CO _2的广泛参数筛选捕获。结果为了解性能指标对操作条件的依赖性提供了有用的见解。在标准台式计算机上，快捷方式模型的每次运行都可以在不到0.04 s的时间内解决。该模型的计算速度和准确性使其非常适合进行大规模筛选，以识别用于通过TSA进行气体分离的新型吸附剂，以及进行广泛的参数分析以识别合适的操作条件。