ArticlebioRxiv : the preprint server for biology2026
A robust and user-agnostic step-emulsion platform for scalable microgel fabrication.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Over the past decade, the integration of microgel-based granular hydrogels in biomedical technologies has experienced substantial growth due to the numerous benefits microgels offer. However, the inability to easily adopt uniform microgel fabrication workflows at scale constitutes a major bottleneck, or in some cases, a barrier-to-entry that stunts further growth of the field. The gold-standard technique for emulsion-based microgel production is through microfluidic droplet-generating devices that produce liquid gel precursor droplets that gel post-production. However, traditional microfluidic workflows often require multiple independent flows and controlled pressure sources, along with a steep learning curve in using microfluidics to achieve uniform droplet sizes reproducibly and repeatedly. This difficulty in adopting microgel fabrication is further compounded by low throughput and the extensive flow rate calibration required when switching to new formulations (e.g., material type, droplet size). In this work, we present a step-emulsion system that bridges the gap by providing a robust and simple setup. We experimentally characterize and evaluate how flow and outlet channel dimension contribute to the generation of uniform droplet populations at specific sizes. With our large dataset consisting of various outlet channel dimensions, we evaluated outlet channel geometrical impacts (height, width, cross-sectional area, aspect-ratio, etc.) on gel precursor droplet size and generation throughput. We demonstrate robust, highly compatible, and repeatably uniform droplet generation from various gel precursor polymer backbones, users with varying microfluidics experience, and a wide viscosity range, including alginate solutions with 650 times the viscosity of water. Furthermore, we confirmed consistent gel precursor droplet generation outcomes driven by a constant flow source (syringe pump) and by direct manual injection as a simple and highly adoptable option for the generation of gel precursor droplets. This platform is ideal for researchers seeking rapid and easy microgel fabrication, regardless of microfluidics experience.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.