Collaborative Research: Scalable Manufacturing of Large-Area Thin Films of Metal-Organic Frameworks for Separations Applications

该基金支持为金属有机框架（MOF）薄膜的形成提供知识的研究，MOF薄膜是一类多孔材料，具有改变分离科学及其应用的能力。mof在电荷和离子传输、分离、基于气体和溶液的传感、催化、环境修复等领域有着广泛的应用。大面积分离膜的形成对于一系列气体分离特别重要，例如从空气或烟气中去除二氧化碳。小型（1平方厘米）mof基膜已显示出一系列高价值分离应用的效用。然而，缺乏基本的知识来创建易于扩展的，先进的大面积MOF膜的制造，仍然保持实验室规模的性能。该奖项支持x射线探针、建模和实验技术的结合，以充分了解MOF薄膜是如何形成的。这一基本知识用于开发连续的卷对卷涂层技术，可以创建具有出色分离性能的大面积MOF薄膜。学生将致力于开发新的MOF结晶理论和建模工具，这些理论和建模工具可用于研究和工业环境。该项目致力于培养学生，特别是来自少数族裔背景的学生，成为成功的化学工程师和材料科学家。低电阻、低成本分离所需的大面积、可扩展薄膜MOF形成很难实现，因为使用可扩展的溶液涂层工艺来控制精确合成MOF薄膜的溶液化学技术有限。该项目采用了包括原位实验、建模和分离测量在内的综合方法，通过可扩展的涂层技术（如流动涂层或最近开发的渗透辅助涂层（PAC）方法）来获得MOF薄膜形成的基础制造研究。利用快速时间尺度、原位x射线散射测量和微动力学建模来了解蒸发/渗透蒸发条件下薄膜MOF的成核和生长机制。微动力学模型模拟了数十亿次的寡聚化反应，以预测成核速率、生长速率和尺寸分布。微动力学模型有助于选择高通量（HT） PAC实验的一系列操作条件，以优化MOF薄膜结构和最大化性能。通过将其连接到气相色谱仪，HT装置也用于获得CO2/N2和CO2/CH4混合物的气体分离因子。随后的工艺-结构-性能关系指导了PAC方法的缩放，以生长50 cm2的MOF薄膜，然后是基于模型的卷对卷涂层系统的设计，用于大规模制造MOF薄膜。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This grant supports research that contributes knowledge to the formation of metal-organic framework (MOF) thin films, a class of porous materials that has the power to transform separations science and its applications. MOFs are useful for a wide range of applications, from charge and ion transport, separations, gas- and solution-based sensing, catalysis, environmental remediation, and more. The formation of large-area separation membranes is especially significant for a range of gas separations, such as for CO2 removal from air or flue gas. Small-scale (1 cm2) MOF-based membranes have shown utility for a range of high-value separation applications. However, a lack of fundamental knowledge exists to create easily scalable, advanced manufacturing of large areas of MOF membranes that still preserve the lab-scale performance. This award supports a combination of x-ray probes, modeling, and experimental techniques to fully understand how MOF thin films form. This fundamental knowledge is used to develop a continuous, roll-to-roll coating technique that can create large-area MOF thin films with outstanding separation performance. Students are engaged to contribute to the development of new MOF crystallization theories and modeling tools that can be used in research as well as industrial environments. The project endeavors to train students, particularly from underrepresented minority backgrounds, to become successful chemical engineers and material scientists. Large area, scalable thin-film MOF formation required for low-resistance, low-cost separations is difficult to achieve due to limited know-how on controlling solution chemistry for precision synthesis of MOF thin films using a scalable solution coating process. This project uses an integrated approach involving in-situ experimentation, modeling, and separation measurements to obtain fundamental manufacturing research on MOF thin film formation using scalable coating techniques, such as flow coating, or the recently developed percolation-assisted coating (PAC) method. Rapid timescale, in-situ x-ray scattering measurements coupled with microkinetic modeling are used to understand thin film MOF nucleation and growth mechanisms under evaporative/pervaporation conditions. The microkinetic model simulates billions of oligomerization reactions to predict nucleation rate, growth rate, and size distribution. The microkinetic model helps in selecting a range of operating conditions for high throughput (HT) PAC experiments for the optimization of MOF thin film structure and maximizing performance. By connecting it to a gas chromatograph, the HT setup is also used to obtain gas separation factors for CO2/N2 and CO2/CH4 mixtures. The ensuing process-structure-property relationships guide the scaling of the PAC method to grow 50 cm2 MOF films, followed by a model-based design of a roll-to-roll coating system for large-scale manufacturing of MOF films.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.