Multi-scale engineering toolbox for systematic assessment of porous materials in the context of adsorption and membrane separations

我们将把结构表征、分子模拟和过程模拟方法集成到一个计算工具箱中，并应用这个工具箱来探索多尺度方法在评估多孔材料在吸附和膜分离过程中的性能方面的范围和准确性。分离过程消耗的能源约占全球能源的10%-15%，而碳捕获的高能源成本仍然是这项技术实施的主要障碍。最近发现的新型多孔材料为提高能量效率的吸附和膜分离提供了前所未有的机会；然而，大量的新材料要求从传统的反复试验的过程设计过渡到基于计算筛选的合理材料选择。在这个项目中，我们开发了这一过渡所需的计算工具，针对实验室规模的实验对它们进行测试，并探索它们在筛选现实工艺配置的材料方面的稳健性。在后一种情况下，我们使用便携式氧气浓度技术作为广泛参考数据的来源，以测试计算预测。与此同时，我们以此为契机，应用多尺度方法探索便携式氧气浓缩器(POC)的进一步优化，使这些医疗设备更轻，电池寿命更长。

We will integrate structure characterization, molecular simulation and process modelling methods into a single computational toolbox and apply this toolbox to explore the scope and accuracy of multi-scale approaches in the assessment of performance of porous materials in adsorption and membrane separation processes. Separation processes consume about 10-15% of global energy, while high energy cost of carbon capture still presents a major hurdle in the implementation of this technology. Recent discovery of new families of porous materials opens unprecedented opportunities to advance energy efficient adsorption and membrane separations; however the large number of new materials demands a transition from traditional trial-and-error process design to rational selection of materials based on computational screening. In this project, we develop computational tools required for this transition, test them against bench scale experiments, and explore their robustness in screening materials for realistic process configurations. In the latter case, we use portable oxygen concentration technologies as a source of extensive reference data to test computational predictions. At the same time, we use this case as an opportunity to apply multi-scale approaches to explore further optimization of portable oxygen concentrators (POC) to make these medical devices even lighter with longer battery life.