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Pore2Chip Python Package: From 3D Soil Scans to Creation of Lab-on-Chip Micromodels

Pore2Chip converts 3D X-ray computed tomography scans of porous media such as soil into representative 2D micromodel designs ready for use to fabricate microfluidic devices. These devices are used to isolate specific soil characteristics for higher throughput experimentation.

Illustration with four image panels than pan out from a photo of a soil core display the four stages of how a soil chip (or TerraForm) is created, from XCT image, to digital conversion, to creation of a physical soil chip. This imagery is displayed on top of a background of a soil surface.

A multi-institutional team of researchers developed a Python package called Pore2Chip used to design realistic soil pore network details for creating microfluidic devices that allow for the isolation and study of specific soil parameters controlling key functions like critical mineral availability. (Image courtesy of the Environmental Molecular Sciences Laboratory)

The Science

Because soils are opaque, it is hard to observe nutrient flow and microbe-mineral interactions directly. Traditional microfluidic devices allow researchers to study microbial and plant-microbe interactions in a transparent, simulated, and controlled environment. But while they are used to mimic the physical structure of soil as the basis for molecular-level experimentation, most don’t reflect real-life soil pore networks. Scientists from the Environmental Molecular Sciences Laboratory (EMSL) worked with a collaborator at the U.S. Department of Agriculture to develop Pore2Chip, a Python package used to design realistic geometric pore network details. These details are printed or laser-etched on a plastic or glass chip used for experimentation—also known as a TerraForm. Using these TerraForms, researchers can perform a range of chemical imaging and analysis to study key molecular interactions and movement of nutrients within a simulated soil environment.

The Impact

The Pore2Chip Python package provides scientists with realistic synthetic soil parameters on a low-cost chip—a TerraForm. Because specific parameters within the TerraForm can be precisely controlled, experiments conducted are highly repeatable and yield consistent results. Their transparency allows for optimized chemical imaging. Controlled measurements also generate AI-compatible datasets for optimal model calibration that train physics-informed neural networks. Modelers use the data to calibrate flow and transport simulations of molecules. The result is faster experiment and modeling cycles, lower cost, and more reliable, reproducible predictions.

 

Graphic displaying the model-data-experiment loop for Pore2Chip. Through the loop, 3D soil volumes are scanned, distilled into a 2D chip design, fabricated, and tested. Experimental results are produced to calibrate flow and AI/machine learning models, improving the next design iteration toward critical mineral science applications.
This graphic displays the model-data-experiment loop for Pore2Chip. Through the loop, 3D soil volumes are scanned, distilled into a 2D chip design, fabricated, and tested. Experimental results are produced to calibrate flow and AI/machine learning models, improving the next design iteration toward critical mineral science applications. (Image courtesy of Michael Perkins and Ben Watson, Pacific Northwest National Laboratory)

Summary

The Pore2Chip Python package converts 3D X-ray computed tomography scans into representative 2D micromodel layouts that can be fabricated into synthetic soil chips quickly and inexpensively using laser manufacturing. The chips, a type of TerraForm created by EMSL, can include embedded minerals, enabling controlled studies of transport and microbe-mineral reactions in realistic pore geometries. Experiments on these chips enable reproducible datasets that help calibrate flow simulations and train physics-informed neural networks. The result is faster, lower-cost investigations with greater reproducibility. Pore2Chip is open source and available for researchers to adapt and use.

Contacts

Aramy Truong 
EMSL 
aramy.truong@pnnl.gov

Maruti Mudunuru 
Pacific Northwest National Laboratory (PNNL) 
maruti@pnnl.gov

Arunima Bhattacharjee 
EMSL 
arunimab@pnnl.gov

Funding

This research was performed on a project award from the Environmental Molecular Sciences Laboratory, a Department of Energy Office of Science user facility sponsored by the Biological and Environmental Research program.

Publication

A. Truong et al. “Pore2Chip: All-in-one python tool for soil microstructure analysis and micromodel design.” Journal of Open Source Software, 10(112), 8052 (2025). [DOI: 10.21105/joss.08052]