Orientation-independent bubble trap with internal partition for robust operation of microfluidic systems

A new monolithic bubble trap has been developed with a unique, orientation-independent design. The bubble trap has a spherical cavity and a central partition with internal passages that eliminate air bubbles effectively for extended periods of time. Flow testing was performed in a closed-loop microfluidic system to demonstrate effectiveness and robustness of the bubble trap. Flow rate was continually monitored on a stationary benchtop and also in simulated microgravity conditions on a 3-D random positioning machine. Data collected from flow sensors placed fore and aft of the bubble trap confirmed that randomly occurring bubbles were effectively eliminated by the trap throughout 24 hour closed-loop perfusion tests. To highlight the orientation-independent benefit of the bubble trap in a specific application of interest, continuous-flow experiments were conducted using human umbilical vein endothelial cells in a closed-loop microfluidic system. The bubble trap successfully protected the integrity of confluent layers that otherwise suffered from cell detachment without the trap. Image analysis showed that random orientation reduced directional alignment of cell nuclei, relative to baseline experiments performed under normal gravity.

Authors

Institutions

Publication Details

Journal
Lab on a Chip
Published
2025-01-01
DOI
https://doi.org/10.1039/d4lc01060d
Primary Topic
Innovative Microfluidic and Catalytic Techniques Innovation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Orientation-independent bubble trap with internal partition for robust operation of microfluidic systems

Calvin Lui, Sang-Joon John Lee, Max Kim, Anand K. Ramasubramanian et al.
Lab on a Chip
Innovative Microfluidic and Catalytic Techniques Innovation
article

Orientation-independent bubble trap with internal partition for robust operation of microfluidic systems

Calvin Lui, Sang-Joon John Lee, Max Kim, Anand K. Ramasubramanian, Jason Tran, Bhavagyna Vegunta, Maya Papez
article en

Abstract

A new monolithic bubble trap has been developed with a unique, orientation-independent design. The bubble trap has a spherical cavity and a central partition with internal passages that eliminate air bubbles effectively for extended periods of time. Flow testing was performed in a closed-loop microfluidic system to demonstrate effectiveness and robustness of the bubble trap. Flow rate was continually monitored on a stationary benchtop and also in simulated microgravity conditions on a 3-D random positioning machine. Data collected from flow sensors placed fore and aft of the bubble trap confirmed that randomly occurring bubbles were effectively eliminated by the trap throughout 24 hour closed-loop perfusion tests. To highlight the orientation-independent benefit of the bubble trap in a specific application of interest, continuous-flow experiments were conducted using human umbilical vein endothelial cells in a closed-loop microfluidic system. The bubble trap successfully protected the integrity of confluent layers that otherwise suffered from cell detachment without the trap. Image analysis showed that random orientation reduced directional alignment of cell nuclei, relative to baseline experiments performed under normal gravity.

Lab on a ChipVol. 25(14)
San Jose State University (US)
National Aeronautics and Space Administration, Nuclear Safety and Security Commission
Openalex Percentile: Top 87%
Innovative Microfluidic and Catalytic Techniques Innovation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.