Nanoscale control of internal inhomogeneity enhances water transport in desalination membranes

Abstract

Finding the path to better desalination Polyamide membranes have been used in large-scale desalination for decades. However, because of the thinness of the membranes and their internal variability, it has been hard to determine which aspects of the membranes most affect their performance. Culp et al. combined electron tomography, nanoscale three-dimensional (3D) polyamide density mapping, and modeling of bulk water permeability with zero adjustable parameters to quantify the effect of 3D nanoscale variations in polymer mass on water transport within the polyamide membrane (see the Perspective by Geise). They found that variability in local density most affects the performance of the membranes. Better synthesis methods could thus improve performance without affecting selectivity. Science, this issue p. 72; see also p. 31 Electron tomography reveals how inhomogeneities in pore distributions affect performance of water filtration membranes. Biological membranes can achieve remarkably high permeabilities, while maintaining ideal selectivities, by relying on well-defined internal nanoscale structures in the form of membrane proteins. Here, we apply such design strategies to desalination membranes. A series of polyamide desalination membranes—which were synthesized in an industrial-scale manufacturing line and varied in processing conditions but retained similar chemical compositions—show increasing water permeability and active layer thickness with constant sodium chloride selectivity. Transmission electron microscopy measurements enabled us to determine nanoscale three-dimensional polyamide density maps and predict water permeability with zero adjustable parameters. Density fluctuations are detrimental to water transport, which makes systematic control over nanoscale polyamide inhomogeneity a key route to maximizing water permeability without sacrificing salt selectivity in desalination membranes.

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Identifiers

DOI

10.1126/science.abb8518

Journal

Science

Year

2021