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determines water and salt permeation in commercial ion exchange membranes. ChemRxiv. Preprint.Ion exchange membrane (IEM) performance in electrochemical processes such as fuel cells, redox flow batteries, or reverse electrodialysis (RED) is typically quantified through membrane selectivity and conductivity, which together determine the energy efficiency. However, water and co-ion transport (i.e., osmosis and salt diffusion / fuel crossover) also impact energy efficiency by allowing uncontrolled mixing of the electrolyte solutions to occur. For example, in RED with hypersaline water sources, uncontrolled mixing consumes 20-50% of the available mixing energy. Thus, in addition to high selectivity and high conductivity, it is desirable for IEMs to have low permeability to water and salt in order to minimize energy losses.Unfortunately, there is very little quantitative water and salt permeability information available for commercial IEMs, making it difficult to select the best membrane for a particular application. Accordingly, we measured the water and salt transport properties of 20 commercial IEMs and analyzed the relationships between permeability, diffusion and partitioning according to the solution-diffusion model. We found that water and salt permeance vary over several orders of magnitude among commercial IEMs, making some membranes better-suited than others to electrochemical processes that involve high salt concentrations and/or concentration gradients. Water and salt diffusion coefficients were found to be the principal factors contributing to the differences in permeance among commercial IEMs. We also observed that water and salt permeability were highly correlated to one another for all IEMs studied, regardless of polymer type or reinforcement. This finding suggests that transport of mobile salt in IEMs is governed by the microstructure of the membrane, and provides clear evidence that mobile salt does not interact strongly with polymer chains in highly-swollen IEMs. File list (2)download file view on ChemRxiv RK-P3A-Manuscript-v5.1 clean ChemRxiv.pdf (700.14 KiB) download file view on ChemRxiv RK-P3A-SI-v5 clean.pdf (365.46 KiB)

In this work, we demonstrate a method to quantify uncertainty in corrections to density functional theory (DFT) energies based on empirical results. Such corrections are commonly used to improve the accuracy of computational enthalpies of formation, phase stability predictions, and other energy-derived properties, for example. We incorporate this method into a new DFT energy correction scheme comprising a mixture of oxidation-state and composition-dependent corrections and show that many chemical systems contain unstable polymorphs that may actually be predicted stable when uncertainty is taken into account. We then illustrate how these uncertainties can be used to estimate the probability that a compound is stable on a compositional phase diagram, thus enabling better-informed assessments of compound stability.