# Development of a Tool for Verifying Leakage Detection in Microfluidic Systems

## TL;DR

This paper introduces a new tool to detect and verify leaks in microfluidic medical devices, improving their reliability and safety.

## Contribution

A novel analytical model and bench test method for verifying leakage detection in microfluidic systems is developed.

## Key findings

- The tool can detect leakages ranging from 0.1% to 10% in microfluidic systems.
- PEEKsil tubing showed lower experimental uncertainties compared to PEEK and COC materials.
- The proposed method can be used as a verification tool for leakage detection in medical devices.

## Abstract

While submissions of microfluidic-based medical devices to the Food and Drug Administration (FDA) have increased in recent years, leakage remains a common but difficult failure mode to detect in microfluidic systems. Here, we have developed a sensitive tool to measure and verify leakages ranging from 0.1% to 10% in leakage detection systems, which can then be used to detect leak in microfluidic devices. Our methodology includes an analytical model that applies hydrodynamic resistance using different fluid-contacting elements (e.g., tubing, junctions, and connectors) to tune the leakage rate based on the application-specific acceptance criteria. We then used three polymer-based microfluidic systems to target leakage rates of approximately 0.1, 1.0, and 10%. The experimental uncertainties in Polyether Ether Ketone (PEEK) tubing were 23.08%, 13.64%, and 1.16%, respectively, while the PEEK-Coated Fused Silica (PEEKsil) tubing system had errors of 0.00%, 0.72%, and 1.59%, respectively, relative to the theoretical values for the same target leak rates. The commonly used commercial grade Cyclic Olefin Copolymer (COC) microfluidic chips produced errors of 7.69% and 5.05%, respectively, for target leakage rates of 0.24% and 1.88%. We anticipate that the proposed bench test method can be useful for device developers as a verification tool for leakage detection systems before assessing flow-mediated leakage failure modes in microfluidic medical devices.