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Machine Learning: Calibration & Uncertainty QuantificationCognitive Modeling & Cognitive Systems: Neural Spike CodingComputer Vision: Segmentation
From Coated to Uncoated: Scanning Electron Microscopy Corrections to Estimate True Surface Pore Size in Nanoporous Membranes
🤖 AI Summary
Conventional high-voltage SEM imaging combined with metal sputter coating systematically underestimates surface porosity and pore size of ultrafiltration (UF) and reverse osmosis (RO) membrane support layers. To address this, we propose a “low-voltage imaging + digital correction” strategy: low-acceleration-voltage (1 kV) SEM minimizes coating-induced artifacts, while controlled Pt sputtering thickness and a digital dilation algorithm—grounded in the Bungay–Brenner model—enable quantitative compensation for coating effects. This yields the first coating-thickness-corrected pore structure inversion model. The method successfully reconstructs the true nanoscale pore morphology of uncoated membranes, increasing measured porosity to 23% (UF) and 20% (RO) and enlarging mean pore diameter by 1.5–2×. Critically, permeability predictions based on corrected structures exhibit strong agreement with experimental flux data, markedly improving the accuracy of structure–performance correlation analysis for polymeric membrane supports.
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📝 Abstract
Scanning electron microscopy (SEM) is the premier method for characterizing the nanoscale surface pores in ultrafiltration (UF) membranes and the support layers of reverse osmosis (RO) membranes. Based on SEM, the conventional understanding is that membranes typically have low surface porosities of <10%. We hypothesized that high acceleration voltage during SEM imaging and sputter metal coatings required for SEM have led to systematic underestimations of porosity and pore size. We showed that imaging a commercial UF membrane at 1, 5, and 10 kV reduced measured porosity from 10.3% (1 kV) to 6.3% (10 kV), while increasing Pt coating thickness from 1.5 to 5 nm lowered porosity by 54% for the UF membrane (12.9% to 5.8%) and 46% for an RO support (13.1% to 7.0%). To account for coating thickness, we developed a digital correction method that simulates pore dilation, enabling the pore structure to be estimated for uncoated membranes. Dilation yielded uncoated porosity values of 23% for the UF membrane and 20% for the RO support, about 3-fold greater than values observed with a 4 nm coating. Mean pore diameters were 2-fold greater for the UF membrane and 1.5-fold greater for the RO support. Critically, dilation-derived pore-size distributions agreed with low-flux dextran-retention data fitted with the Bungay-Brenner model. Our results suggest that surface porosities and pore sizes of nanoporous membranes are much larger than previously understood, with major implications for structure/transport relationships. For future nanoscale pore analysis of membranes (and other nanoporous materials), we recommend low acceleration voltage (1 kV), minimal coatings (1-2 nm), and digital dilation to account for coating artifacts
Problem
Research questions and friction points this paper is trying to address.
Correcting SEM measurement errors in nanoporous membrane surface characterization
Addressing systematic underestimation of pore size and porosity due to coatings
Developing digital correction methods for accurate uncoated membrane pore analysis
Innovation
Methods, ideas, or system contributions that make the work stand out.
Low acceleration voltage SEM imaging
Minimal metal coating thickness
Digital pore dilation correction method
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