A Leak-proof Countermeasure for 3D-printed Vessels Under Pressure

Allen, C., Gaidica, M.

The Neurotech Hub, Department of Neuroscience, Washington University in St Louis School of Medicine, St Louis, MO


Filament-based 3D parts are made by layering heated material. These layers form a leaky structure. Therefore, despite these parts being well-suited for rapid, custom enclosures, they are not naturally suited for water-borne applications. We aimed to determine if a spray coating could mitigate leaking. Furthermore, if deployed as a submersible/vessel, could our parts withstand acute exposure to external pressure (e.g., up to 80 meters)?


At the Neurotech Hub, we designed and printed three “vessels” (2 in. outer diameter) using PLA filament. Two vessels were left uncoated (one as control) and one was coated with two layers of spray lacquer. The two vessels had brass inserts inserted for screws and were sealed using a custom-cut rubber gasket and acrylic top (Fig 1). An internal vacuum was pulled (-30 in. Hg) for 30 minutes to simulate exposure to 80 meters depth while the vessel was submerged in red UV dye. Vessels were removed, dried by hand, and then cut in half with a jeweler’s saw to expose the 3D structure.

Fig 1. Experimental methods.

Fig 1. Experimental methods. (a) Unassembled experiment apparatus  (pressure gauge, acrylic panel, gasket, threaded inserts, and PLA printed part). (b) Two coats of spray lacquer applied to one of the vessel. (c) Assembly of apparatus. (d) Apparatus connected to the vacuum pump. (e) Vessel submerged in UV dye during vacuum (-30 in. Hg). (f) Jewelers saw cut the vessel in half after hand drying.


Fig 2. Sectioned 3D parts for each condition under UV light.

Fig 2. Sectioned 3D parts for each condition under UV light. Each part was selected in MATLAB for analysis (blue line). The UV dye is visible on the swab (arrow) which was used to calibrate the photo filter.

Samples from each condition were imaged between two UV light panels using a Canon EOS-R camera in raw format alongside a swab of the UV liquid (Fig 2). After raw image conversion, a custom saturation filter was applied in Photoshop calibrated by the swab, and exported as a PNG image. In MATLAB, the image was converted to HSL color space. Each sample (i.e., condition) was selected with a rectangle tool and then split into 100 equally sized sections based on pixels, and saturation values for each section were summed. Thus, a single condition was associated with 100 unique values. An ANOVA analysis was performed to indicate if a significant difference existed between the mean saturation of all samples. Tukey’s Honestly Significant Difference test was performed to test the null hypothesis that there is no true difference between the means.


The no coat sample rejected the null hypothesis against the other samples (p=0.00); that is, it was unlikely that the means were different from chance alone.

However, the 2 coat and Control samples had statistically non-significant means (p=0.97; Fig 3).

Fig 3. UV dye Saturation vs. Coat Condition.

Fig 3. UV dye Saturation vs. Coat Condition.


We found that two coats of spray lacquer effectively leak-proofed 3D-printed filament parts exposed to a simulated depth of 80 meters, enabling a method of creating rapidly producible submersible vessels. This may be useful for future aquatic applications where scientific tooling needs to be encapsulated.


Other approaches to leak-proof devices include using resin or metals. We are currently developing subtractive manufacturing protocols to create parts out of aluminum using our 3D CNC mill (Fig 4). This involves using custom 3D-printed vice jigs and optimizing 3D tool paths using computer-aided design techniques.

Fig 4. Process of machining an aluminum part at the Neurotech Hub.

Fig 4. Process of machining an aluminum part at the Neurotech Hub. (a) Stock of aluminum inserted into the vise of the Nomad3 CNC mill. (b) Aluminum stock, along with the vise, modeled in Fusion360 displaying the initial facing toolpath to ensure the top stock of the part is flat and ready to machine. (c) Second and third toolpaths displaying clearing of the inside geometry and center drilling holes. (d) Finished machined part with an electronic module inserted in the cavity.

We thank Peter Bayguinov, PhD, Assistant Director, Washington University Center for Cellular Imaging (WUCCI) for assisting with initial imaging techniques.

The Neurotech Hub is supported by the McDonnell Center’s for Systems Neuroscience, and Cellular and Molecular Neurobiology.

View the poster PDF.

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