Evidence map›Paper›PMID 42230541›Full record

ArticleMicrosystems & nanoengineering2026

Seal whisker-inspired fully printed MEMS flow sensor via micron-scale soft material additive manufacturing.

Engincan Tekin, Ming Cao, Ajay Giri Prakash Kottapalli

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2026. 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.

Engincan TekinDepartment of Bioinspired MEMS and Biomedical Devices (BMBD), Engineering and Technology Institute (ENTEG), University of Groningen, Groningen, Netherlands.
Ming CaoDepartment of Discrete Technology and Production Automation, Engineering and Technology Institute (ENTEG), University of Groningen, Groningen, the Netherlands.
Ajay Giri Prakash KottapalliDepartment of Bioinspired MEMS and Biomedical Devices (BMBD), Engineering and Technology Institute (ENTEG), University of Groningen, Groningen, Netherlands. a.g.p.kottapalli@rug.nl.ORCID http://orcid.org/0000-0002-3868-7069

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) ERC-STG-101042370
6 · The paper itself

Abstract

Seals are renowned for their exceptional ability to hunt, a capability attributed to the uniquely evolved whisker morphology that suppresses vortex-induced vibrations and enables them to track hydrodynamic trails in the water. In this study, we present the first direct experimental comparison of replicated whisker geometries from harbor seals, gray seals, and sea lions, integrated into an artificial follicle-sinus complex flow sensor. A custom-formulated elastic resin was developed to address the limitations of current photocurable soft materials, enabling the fabrication of mechanically compliant structures with high spatial fidelity. All components, including biologically accurate whisker geometries and a soft, cavity-integrated FSC, were fabricated using projection micro-stereolithography, achieving sub-10 μm resolution in a single-step process. Piezoresistive sensing was achieved via capillary infusion of graphene nanoplatelet (GNP) ink into the 500 µm embedded channels with 20 µm corrugated layers within the FSC base. Static and dynamic characterization confirmed high strain sensitivity (GF = 16.57 in tension, 10.67 in compression) and stable performance over 3000 cycles, demonstrating suitability for both steady-state flow sensing and vortex characterization measurements. Comparative flow experiments further revealed that phocid seal whiskers (harbor and gray seals) suppress vortex-induced vibrations and provide superior signal-to-noise ratios compared to sea lion whiskers. This work lays the foundation for high-resolution, species-specific sensing technologies that can advance both biological understanding and engineered flow navigation systems.

Identifiers

PMID42230541
PMCPMC13230687

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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.