Identifying High-Performance Metal–Organic Frameworks for Low-Temperature Oxygen Recovery from Helium by Computational Screening

Metal–organic frameworks (MOFs) are an important
class of
porous crystalline materials for applications ranging from gas adsorption
and separation to catalysis. There are thousands of potential MOFs
available for separation applications. We developed a computational
approach to screen MOFs for the separation of oxygen–helium
mixtures at low temperatures (100–200 K), conditions that were
motivated by issues associated with propulsion in space-based settings.
We used detailed molecular simulations for a small number of MOFs
to develop screening methods that were then used to estimate the optimum
temperatures for separations using pressure swing adsorption for 2932
MOFs from the CoRE MOF database and the swing capacity and oxygen–helium
selectivity at these temperatures. We used the stability of the best-performing
structures in the presence of moisture as a means to provide a short
list of high-performance materials. In addition to identifying specific
materials for oxygen–helium separations, this approach could
prove useful for selecting adsorbents for other gas separations.

金属有机框架（Metal–organic frameworks, MOFs）是一类重要的多孔晶体材料，应用场景涵盖气体吸附分离、催化等诸多领域。目前已有数千种潜在MOFs可用于分离相关应用。我们开发了一种计算筛选方法，用于遴选适用于低温（100–200 K）下氧氦混合气分离的MOFs，该工况的选取源于天基推进系统相关的技术挑战。我们先针对少量MOFs开展精细的分子模拟，以此构建初筛方法；随后利用该方法对CoRE MOF数据库中的2932种MOFs进行全面评估，估算出其变压吸附分离的最优温度，并得到该温度下的循环吸附容量与氧氦选择性。我们还以性能最优的结构在潮湿环境下的稳定性作为附加筛选标准，最终生成了一份高性能材料候选清单。本研究不仅筛选出了适用于氧氦分离的特定材料，该方法同样可推广至其他气体分离体系的吸附剂选型工作中。