Evidence map›Paper›PMID 42909381›Full record

ArticleRSC applied polymers2026

Evaporation-assembled magnetic microrobots with stable geometry and polymer-tunable function.

Pavlos Kotronaros, Haiyue Li, Jan Frey, Haitam Rarhai, Diya Bose, Michael Kappl, Bradley J Nelson, Salvador Pané, Minghan Hu

Abstract read
In one paragraph

Article in RSC applied polymers, 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

9 authors.

Pavlos KotronarosDepartment of Mechanical and Process Engineering, ETH Zurich Tannenstrasse 3 Zurich 8092 Switzerland minghu@ethz.ch.
Haiyue LiDepartment of Mechanical and Process Engineering, ETH Zurich Tannenstrasse 3 Zurich 8092 Switzerland minghu@ethz.ch.
Jan FreyDepartment of Mechanical and Process Engineering, ETH Zurich Tannenstrasse 3 Zurich 8092 Switzerland minghu@ethz.ch.
Haitam RarhaiDepartment of Mechanical and Process Engineering, ETH Zurich Tannenstrasse 3 Zurich 8092 Switzerland minghu@ethz.ch.
Diya BoseDepartment of Mechanical and Process Engineering, ETH Zurich Tannenstrasse 3 Zurich 8092 Switzerland minghu@ethz.ch.
Michael KapplMax Planck Institute for Polymer Research Ackermannweg 10 55128 Mainz Germany.ORCID https://orcid.org/0000-0001-7335-1707
Bradley J NelsonDepartment of Mechanical and Process Engineering, ETH Zurich Tannenstrasse 3 Zurich 8092 Switzerland minghu@ethz.ch.ORCID https://orcid.org/0000-0001-9070-6987
Salvador PanéDepartment of Mechanical and Process Engineering, ETH Zurich Tannenstrasse 3 Zurich 8092 Switzerland minghu@ethz.ch.ORCID https://orcid.org/0000-0003-0147-8287
Minghan HuDepartment of Mechanical and Process Engineering, ETH Zurich Tannenstrasse 3 Zurich 8092 Switzerland minghu@ethz.ch.ORCID https://orcid.org/0000-0002-9001-6780

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic microrobots require anisotropic geometries to achieve controlled locomotion and adaptable material compositions to incorporate functions such as stimuli-responsive cargo release. However, existing fabrication strategies rarely combine stable, well-defined anisotropic structures with broad material versatility. Here, we introduce a bottom-up assembly approach that converts magnetic polymer nanoparticles into solid conical microrobots while retaining compatibility with multiple polymer systems. Using the same fabrication protocol, we assemble microrobots from different biocompatible or biodegradable polymers, including poly(methyl methacrylate), poly(l-lactic acid), and poly(lactic-

Identifiers

PMID42909381
PMCPMC13684354

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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.