Computational Design of Ultraselective Desalination Membranes using Molecular Simulations and Path Sampling Techniques

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Semipermeable membranes selectively impede the passage of undesirable molecules and ions in a fluid, while allowing the desirable molecules to pass through the membrane. This type of technology is key to many applications as well as natural processes. For instance, membranes that are only water permeable and reject most other ions and molecules are used in water desalination. Similarly, biological cells feature membranes capable of modulating the passage of small molecules and ions into and out of the cell. On a molecular level, a membrane’s selectivity is dictated by its nanostructure, i.e., the geometry, topology, and chemistry of its constituent nanopores. However, there is much yet to learn about how a membrane's structure is fundamentally related to its selectivity for certain ions and molecules. On one hand, existing experimental techniques lack the necessary spatiotemporal resolution to characterize membrane structure and to probe isolated solute (the molecule or ion) passage events. On the other hand, conventional molecular simulation techniques can provide information about events at the correct length-scale, but the average time it takes to observe an undesirable solute passing through a highly selective membrane is beyond the reach of standard molecular simulation methods. These factors limit our ability to understand important natural processes (such as biological membrane transport and solute transport in porous media) and hamper efforts to rationally design ultraselective membranes for desalination and gas and chemical separation applications.The goal of this proposal is to conduct a systematic investigation of the structure-selectivity relationship in nanoporous membranes using molecular dynamics simulations and advanced path sampling techniques. The investigator recently developed a novel path sampling algorithm that makes it possible to accurately and efficiently estimate arbitrarily long solute transport timescales under operationally realistic conditions. The algorithm is also capable of reconstructing an accurate and statistically representative picture of the solute transport mechanism. This approach will be used to probe the kinetics and molecular mechanisms of pressure-driven solute transport through nanoporous membranes with well-defined geometries and chemistries. The project focuses on membranes used in desalination applications, but the developed computational tools can be universally applied to other membrane-based separation processes. The research plan sets out first to develop new computational tools and methods for studying solute transport through membranes. Subsequently, the investigator will conduct a set of hypothesis-based calculations that address important fundamental questions about the structure-selectivity relationship in membranes and hindered transport under nanoscale confinement. To this end, both simple model carbon-based membranes with well-defined structures and chemistries and synthetic membranes such as zeolites and metal-organic frameworks will be examined. Collaboration with experimental groups at Yale complements the modeling efforts, as membranes with well-defined structures will be synthesized and performance in membrane-based desalination will be assessed.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.