Evidence map›Paper›PMID 40509600›Full record

ArticleSmall methods2026

Benchmarking Mechanical Properties of 3D Printed Elastomeric Microstructures.

Or Eivgi, Clara Vazquez-Martel, Jaroslav Lukeš, Eva Blasco

Abstract read
In one paragraph

Article in Small methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Or EivgiInstitute for Molecular Systems Engineering and Adv. Mater. (IMSEAM), Heidelberg University, Im Neuenheimer Feld 225, 69120, Heidelberg, Germany.ORCID https://orcid.org/0000-0003-0997-1711
Clara Vazquez-MartelInstitute for Molecular Systems Engineering and Adv. Mater. (IMSEAM), Heidelberg University, Im Neuenheimer Feld 225, 69120, Heidelberg, Germany.ORCID https://orcid.org/0000-0002-4656-6056
Jaroslav LukešBruker Nano Surfaces and Metrology, Technická 4, Prague, 160 00 Prague 6, Czech Republic.
Eva BlascoInstitute for Molecular Systems Engineering and Adv. Mater. (IMSEAM), Heidelberg University, Im Neuenheimer Feld 225, 69120, Heidelberg, Germany.ORCID https://orcid.org/0000-0002-0849-4223

Funding

Carl-Zeiss-Stiftung Carl-Zeiss-Foundation-Focus@HEiKADeutsche Forschungsgemeinschaft EXC-2082/1-390761711
6 · The paper itself

Abstract

The characterization of mechanical properties in soft three-dimensional (3D) printed materials at the microscale remains a significant challenge due to the lack of standardized methodologies. To address this issue, a microscale nanoindentation protocol for elastomeric 3D printed microstructures is developed, optimized, and benchmarked. Herein, a conospherical indenter tip (r = 10.26 µm), a modified trapezoidal displacement profile with lift-off segments to capture adhesion interactions, and the nano-Johnson-Kendall-Roberts model for data analysis are employed. The protocol is optimized and verified using four newly developed polydimethylsiloxane (PDMS)-based inks for two-photon 3D laser printing. The results are compared to a state-of-the-art literature protocol that uses a Berkovich tip and the Oliver-Pharr model. It is shown that adhesion forces play a significant role in mechanical properties overestimation, showing differences of up to 80% between the different protocols. This study highlights the importance of carefully selecting characterization protocol to yield comparable results between studies. By providing a standardized protocol, it paves the way for straightforward and accurate characterization of mechanical properties in soft 3D printed materials at the microscale.

Indexed as

additive manufacturingelastomersmechanical propertiesnanoindentationPDMStwo‐photon polymerization

Identifiers

PMID40509600
PMCPMC12825332

What OpenQuestion holds

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Registered trials

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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.