Evidence map›Paper›PMID 41444795›Full record

ArticleScientific reports2025

An open-source slicer for 3D mSLA printing of microfluidic chips.

Maria Emmerich, Benjamin Liertz, Robert Wille

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Maria Emmerich *Technical University of Munich (TUM), Arcisstrasse 21, 80333, Munich, Germany. maria.emmerich@tum.de.
Benjamin Liertz *Technical University of Munich (TUM), Arcisstrasse 21, 80333, Munich, Germany. benjamin.liertz@tum.de.
Robert WilleTechnical University of Munich (TUM), Arcisstrasse 21, 80333, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microfluidic chips enable high-precision handling and automation of chemical and biological experiments by transporting and manipulating fluids through complex channel networks embedded on-chip. While polydimethylsiloxane (PDMS) soft lithography remains the standard for microfluidic device fabrication, it is labor-intensive and requires specialized expertise. Masked stereolithography (mSLA) 3D printing offers a rapid, high-resolution alternative, where the 3D chip geometry is fabricated layer-by-layer. These layers are cross-sections of the geometry and stacked on top of each other. However, all existing "off the shelf" slicing processes are optimized for speed and printing outside features rather than the small channels inside microfluidic chips. As a result, the fabrication of these chips still frequently leads to imperfect quality as manifested, e.g., in clogged channels or rough surfaces, which influence the flow through these channels or even render the result unusable. In this work, we propose a novel slicing tool, OpenSLAice, that is optimized for 3D printing of microfluidic chips. To this end, we present a slicing method that automatically detects microfluidic features within a microfluidic chip and, then, orients the chip as well as dynamically slices it so that the imperfections in the fabrication of those features are avoided. It rasterizes the sliced cross-layers and, if several parts should be printed at the same time, it automatically arranges them. Finally, a single print exposure calibration is presented to efficiently determine the required exposure times per layer thickness for resin-printer combinations. The modular, open-source tool is available at https://github.com/cda-tum/mmft-openSLAice and allows to pre-process microfluidic chips for mSLA fabrication.

Indexed as

3D printingMicrofluidicsSLASlicer

Identifiers

PMID41444795
PMCPMC12738676

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.