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https://github.com/cda-tum/mmft-spheroid-trap-designer

A tool that generates a microfluidic chip or channel design for trapping spheroids.

https://github.com/cda-tum/mmft-spheroid-trap-designer

Science Score: 39.0%

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    Found 2 DOI reference(s) in README
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    Low similarity (17.3%) to scientific vocabulary

Keywords

microfluidics organs-on-chip spheroid-trap spheroids
Last synced: 6 months ago · JSON representation

Repository

A tool that generates a microfluidic chip or channel design for trapping spheroids.

Basic Info
Statistics
  • Stars: 3
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 4
Topics
microfluidics organs-on-chip spheroid-trap spheroids
Created 10 months ago · Last pushed 6 months ago
Metadata Files
Readme License

README.md

Spheroid-Trap-Designer

The MMFT spheroid-trap designer is a tool that generates a microfluidic chip and/or channel design for trapping spheroids based on hydrodynamic principles in a dedicated location on a chip, by employing a SAT solver to optimize the design process and automatically compute the required parameters while adhering to ISO guidelines. It is possible to chain several traps together and thereby trap several spheroids. These traps are especially useful for studying complex biological processes such as the vascularization of spheroids and organoids [1].

The tool is available online: https://www.cda.cit.tum.de/mmft-spheroid-trap-desiger. It is part of the Munich Microfluidics Toolkit (MMFT) by the Chair for Design Automation at the Technical University of Munich.

If you have any questions about the fabrication and the trapping experiments feel free to contact us at microfab@cea.fr. If you have questions about using or the development of the code write us via microfluidics.cda@xcit.tum.de or by creating an issue on GitHub.

System Requirements

The project is tested with python 3.11. To install the required python packages please type the following in your command line: bash pip install -r requirements.txt

Run

To run the script, via the command line, type: bash python spheroid_all.py

You can adapt the parameters in the same script.

Simulation Setup

The Spheroid Trap Designer allows you to generate a customized geometry based on your specified parameters. Once the geometry is created, you can simulate fluid flow within it. For this you can use OpenFOAM, an open-source computational fluid dynamics (CFD) tool, COMSOL, a commercial CFD tool, or any other tool. For OpenFOAM and COMSOL we have included some of the simulation files that can be adapted for personal use.

OpenFOAM

Before proceeding, ensure that OpenFOAM is installed on your system. Installation instructions can be found on the official OpenFOAM website. The set up described here is tailored for OpenFOAM 12.

Simulation Setup Guide

1. Generate the Geometry

  • Define your parameters and generate the spheroid trap geometry via the web interface or by running the provided command-line tool.
  • The generated STL file will represent the 3D shape of the trap. The generated STL is defined in mm, here the STL is automatically scaled to size.

2. Prepare for Simulation

  • Copy the generated STL file into the following directory: (You might need to generate the geometry folder) sh /simulation/openFoam/constant/geometry
  • Rename the STL file to trap.stl.
  • Modify the vertices in the blockMeshDict file to ensure the mesh properly fits around your geometry:
    sh /simulation/openFoam/system/blockMeshDict Important: The block mesh needs to "cut-off" the inlet and the outlet so these can be defined as specialized boundaries, i.e., that an inflow or outflow can be defined. Currently the block mesh is defined for a trap input for spheroids with a diameter of 300 µm.

3. Run the Fluid Flow Simulation

  • Navigate to the OpenFOAM simulation directory:
    sh cd /simulation/openFoam
  • Start the simulation by executing:
    sh run

This will generate the computational mesh and simulate fluid flow within your custom spheroid trap.

COMSOL

The comsol simulation file is uploaded in the simulation folder. The simulation parameters can be adapted via the user interface of the tool.

References

[1] Quintard, C., Tubbs, E., Jonsson, G. et al. A microfluidic platform integrating functional vascularized organoids-on-chip. Nat Commun 15, 1452 (2024).

Developed in collaboration between:

TUM × CEA-Leti

Owner

  • Name: Chair for Design Automation, TU Munich
  • Login: cda-tum
  • Kind: organization
  • Location: Germany

The CDA provides expertise for all main steps in the design and realization of integrated circuits, embedded systems, as well as cyber-physical systems.

GitHub Events

Total
  • Release event: 12
  • Watch event: 2
  • Delete event: 13
  • Push event: 26
  • Pull request event: 17
  • Create event: 20
Last Year
  • Release event: 12
  • Watch event: 2
  • Delete event: 13
  • Push event: 26
  • Pull request event: 17
  • Create event: 20

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 41
  • Total Committers: 1
  • Avg Commits per committer: 41.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 41
  • Committers: 1
  • Avg Commits per committer: 41.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
MariaEmmerich 1****h 41

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 0
  • Total pull requests: 24
  • Average time to close issues: N/A
  • Average time to close pull requests: less than a minute
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 24
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 24
  • Average time to close issues: N/A
  • Average time to close pull requests: less than a minute
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 24
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
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  • MariaEmmerich (36)
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Dependencies

.github/workflows/deploy.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v5 composite
pyproject.toml pypi
  • matplotlib ==3.7.2
  • numpy ==1.25.1
  • numpy-stl ==3.1.1
requirements.txt pypi
  • ezdxf ==1.3.5
  • flask ==2.3.3
  • matplotlib ==3.9.2
  • numpy ==2.1.1
  • numpy-stl ==3.1.1
  • z3-solver ==4.13.0.0