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Mineral precipitation reactions in porous media can change the porosity and permeability of the rock formations. Predicting the rate of reaction and impacts on formation properties is challenging due to a lack of understanding of mineral precipitation reaction kinetics and mechanisms in porous media. This is furthermore challenging due to the highly heterogeneous nature of natural porous media. Here, we aim to develop a novel experimental platform leveraging 3D printing to facilitate replicable mineral precipitation experiments in controlled, heterogenous porous media systems. This requires fundamental understanding of the kinetics of mineral precipitation on the polymer materials used to fabricate the 3D printed porous media. In this work, we manipulate (via sulfonation) material surfaces (high impact polystyrene, HIPS) to promote calcite precipitation from supersaturated solutions to inform the design of synthetic subsurface systems. Calcite precipitation on HIPS films of varied surface sulfonation is confirmed using X-ray diffraction (XRD) analysis and weight-based precipitation experiments where increased precipitation with increased surface functionalization and solution saturation index are observed. This approach is then applied to 3D-printed porous media to enhance understanding of geochemical reactions, specifically calcite precipitation. Three dimensional images of Bentheimer Sandstone are used as the basis for 3D-printed porous media samples. Two 3D-printed samples were functionalized with acid to activate the surface and promote mineral precipitation. Functionalized and unfunctionalized samples underwent calcite precipitation core flooding experiments with oversaturated calcite solutions for 96 hours. Three dimensional X-ray micro-CT imaging revealed calcite growth in functionalized samples, with a calcite volume fraction of approximately 2.6% and a substantial reduction in porosity. Unfunctionalized samples exhibited diminished calcite precipitation and porosity changes. These findings demonstrate that reactive 3D-printed porous media can provide a versatile geochemical modeling and experimentation platform. Functionalizing 3D printed samples enhances reactivity, allowing investigations of mineral precipitation processes in complex porous media. This research highlights the potential for further exploration of 3D-printed media in various geochemical contexts.
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This content will become publicly available on July 1, 2026
UTILE-Pore: Deep Learning-Enabled 3D Analysis of Porous Materials in Polymer Electrolyte Membrane-Based Energy Devices
3D imaging of porous materials in polymer electrolyte membrane (PEM)-based devices, coupled with in situ diagnostics and advanced multi-scale modelling approaches, is pivotal to deciphering the interplay of mass transport phenomena, performance, and durability. The characterization of porous electrode media in PEM-based cells encompassing gas diffusion layers and catalyst layers often relies on traditional analytical techniques such as 2D scanning electron microscopy, followed by image processing such as Otsu thresholding and manual annotation. These methods lack the 3D context needed to capture the complex physical properties of porous electrode media, while also struggling to accurately and effectively discriminate porous and solid domains. To achieve an enhanced, automated segmentation of porous structures, we present a 3D deep learning-based approach trained on calibrated 3D micro-CT, focused ion beam-scanning electron microscopy datasets, and data from physical porosity measurements. Our approach includes binary segmentation for porous layers and a multiclass segmentation method to distinguish the microporous layers from the gas diffusion layers. The presented analysis framework integrates functions for pore size distribution, porosity, permeability, and tortuosity simulation analyses from the resulting binary masks and enables quantitative correlation assessments. Segmentations achieved can be interactively visualized on-site in a 3D environment.
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- Award ID(s):
- 2046060
- PAR ID:
- 10625161
- Publisher / Repository:
- Journal of The Electrochemical Society
- Date Published:
- Journal Name:
- Journal of The Electrochemical Society
- Volume:
- 172
- Issue:
- 7
- ISSN:
- 0013-4651
- Page Range / eLocation ID:
- 074515
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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