Evidence map›Paper›PMID 40671376›Full record

ArticleJournal of the American Chemical Society2025

Highly Efficient Near-Infrared Light-Driven Molecular Motor Rotation Enabled by Upconversion Nanoparticles as Nanoscale Light Sources.

Jinyu Sheng, Youxin Fu, Kefan Wu, Thomas Freese, Hong Zhang, Ben L Feringa

Abstract read
In one paragraph

Article in Journal of the American Chemical Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Jinyu ShengStratingh Institute for Chemistry, University of Groningen, Nijenborgh 3, Groningen 9747 AG, The Netherlands.ORCID 0000-0001-8141-9089
Youxin FuStratingh Institute for Chemistry, University of Groningen, Nijenborgh 3, Groningen 9747 AG, The Netherlands.ORCID 0000-0001-6942-6534
Kefan WuVan't Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, Amsterdam 1098 XH, The Netherlands.
Thomas FreeseStratingh Institute for Chemistry, University of Groningen, Nijenborgh 3, Groningen 9747 AG, The Netherlands.ORCID 0000-0002-7792-3415
Hong ZhangVan't Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, Amsterdam 1098 XH, The Netherlands.
Ben L FeringaStratingh Institute for Chemistry, University of Groningen, Nijenborgh 3, Groningen 9747 AG, The Netherlands.ORCID 0000-0003-0588-8435

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Powering light-driven molecular motors with visible or near-infrared (NIR) light is essential in the design of molecular machines, bringing dynamic functions to the next generation of responsive materials particularly for biological applications. However, current strategies suffer from heavy molecular substitution and low photoefficiency of excitation, limiting their practical use in bulk materials and biomolecular systems. Here, we report a general and highly efficient strategy to power NIR light-driven molecular motors via a radiative energy transfer mechanism. Taking advantage of spectrally tunable upconversion nanoparticles (UCNPs), the motors powered by continuous wave NIR light can reach photostationary states (PSS) with high efficiency, comparable to those of direct UV/visible light-driven systems, without a deaeration process needed. The concept is validated on various molecular motors with different rotary speeds, providing a general, broadly applicable principle for the future design of highly efficient NIR-powered photodynamic molecular motor systems.

Identifiers

PMID40671376
PMCPMC12314898

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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.