DMREF: Design of Organic-Inorganic Membranes for Extreme Chemical Environments

非技术描述：人们在日常生活中使用许多化学产品。药品、化妆品、燃料、胶水和塑料都是化学品。制造这些产品需要将许多化学品的混合物分离成单一的纯化学品流。世界上大约十分之一的能源消耗用于净化化学品。用膜净化化学品可以降低90%的能源消耗。膜是非常薄的材料，具有非常小的孔隙，可按大小和类型分离化学品。 不幸的是，目前的膜材料不适用于许多纯化过程。塑料薄膜易于大量制造，但在许多化学混合物中溶解。无机膜很难大量制造，但在大多数化学混合物中是稳定的。该项目探索了一种向塑料膜中添加无机物的新方法。这些新膜易于大量制造，在化学混合物中更稳定。由于这些无机物可以以多种方式添加到塑料中，因此试错法测试是不切实际的。相反，该项目使用计算模拟和数据分析来加速发现最佳膜。该项目的学生将接受膜科学，计算模拟，大数据科学和材料测试方面的培训。该项目还支持格鲁吉亚技术的开放获取，学生运行的材料创新和学习实验室（MILL）的计算材料科学。MILL为学生提供免费的材料研究工具。每年有数百名学生接受这些研究工具的培训。技术说明：该研究项目将扩展最近发现的一类通过气相渗透（VPI）创建的混合膜材料，气相渗透是一种气相过程，将聚合物与无机成分在原子水平上混合。这些杂化膜在有机溶剂中显示出显著增强的稳定性，同时保留了高渗透性和高选择性的突出膜特性。由于这种膜的设计空间-包括聚合物化学，无机化学和混合微结构-是巨大的，传统的基于爱迪生的材料开发方法是不切实际的。为了应对这一挑战，研究团队结合了以下方面的专业知识：（1）VPI材料合成的现象学理论，（2）膜和分离科学，（3）材料模拟和数据驱动设计，以及（4）将已知的现象学物理与有限的初始数据相结合的高级统计算法。在这些领域的努力将迅速转向化学，形态和加工空间的机会。具体而言，该项目将侧重于针对目标膜化学和微结构的材料合成工艺的设计。本研究的结果将是（1）基于具有上级性能和稳定性的固有微孔聚合物的有形混合膜的创建，（2）用于控制这些混合膜中的结构和性能的关键理化描述符的鉴定，以及（3）开发新的策略，用于处理数据稀疏性和将物理现象整合到材料信息学中-该奖项反映了NSF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。

Non-Technical Description: People use many chemical products in their day-to-day lives. Medicines, makeup, fuel, glues, and plastics are all chemicals. Making these products requires separating mixtures of many chemicals into single streams of pure chemicals. About one tenth of the world's energy use goes to purifying chemicals. Purifying chemicals with membranes could lower this energy use by ninety percent. Membranes are very thin materials with very small pores that separate chemicals by size and type. Unfortunately, current membrane materials do not work for many purification processes. Plastic membranes are easy to make in large amounts but dissolve in many chemical mixtures. Inorganic membranes are hard to make in large amounts but are stable in most chemical mixtures. This project explores a new way to add inorganics to plastic membranes. These new membranes are easy to make in large amounts and more stable in chemical mixtures. Because these inorganics can be added to plastics in many ways, trial-and-error testing is impractical. Instead, this project uses computational simulations and data analytics to speed up discovery of the best membranes. Students on this project will be trained in membrane science, computational simulations, big data science, and materials testing. This project also supports computational materials science in Georgia Tech's open-access, student-run Materials Innovation and Learning Lab (The MILL). The MILL provides students with free access to materials research tools. Hundreds of students get trained on these research tools each year. Technical Description: This research project will expand a recently discovered class of hybrid membrane materials created via vapor phase infiltration (VPI), a gas-phase process that infuses polymers with inorganic constituents intermixed at the atomic level. These hybrid membranes show dramatically enhanced stability in organic solvents while retaining salient membrane properties of high permeance and discerning selectivity. Because the design space for such membranes - including polymer chemistry, inorganic chemistry, and hybrid microstructure - is enormous, traditional Edisonian-based materials development methods are impractical. To address this challenge, the research team combines expertise in: (1) phenomenological theory of VPI materials synthesis, (2) membrane and separation science, (3) materials simulations and data-driven design, and (4) advanced statistical algorithms that incorporate known phenomenological physics with limited initial data. Efforts in each of these areas will rapidly steer the search towards chemical, morphological, and processing spaces of opportunity. Specifically, this project will focus on the design of materials synthesis processes for targeted membrane chemistries and microstructures. The outcomes of this research will be (1) the creation of tangible hybrid membranes based on polymers of intrinsic micro-porosity with superior performance and stability, (2) the identification of key physiochemical descriptors for controlling structure and performance in these hybrid membranes, and (3) the development of new strategies for handling data sparsity and physical phenomena integration into materials informatics-based design.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.