Evidence map›Paper›PMID 42756983›Full record

ArticleNanoscale advances2026

Controlled composition of Zn-doped iron oxide nanoparticles for optimised MPI performance.

Deandra L Pragasam, Emma E Brotherton, Agus R Poerwoprajitno, Zeno R Ramadhan, Brendan Lee, Andre Bongers, Kartika Wardhani, Dale L Huber, Richard D Tilley

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nanoscale advances, 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.

Deandra L PragasamSchool of Chemistry, University of New South Wales Sydney NSW 2052 Australia r.tilley@unsw.edu.au.
Emma E BrothertonSchool of Chemistry, University of New South Wales Sydney NSW 2052 Australia r.tilley@unsw.edu.au.
Agus R PoerwoprajitnoCenter for Integrated Nanotechnologies, Sandia National Laboratories Albuquerque NM 87185 USA arpoerw@sandia.gov.ORCID https://orcid.org/0000-0002-1932-8669
Zeno R RamadhanElectron Microscope Unit, Mark Wainwright Analytical Centre, University of New South Wales Sydney NSW 2052 Australia.ORCID https://orcid.org/0000-0001-7042-8780
Brendan LeeBiological Resources Imaging Laboratory, Mark Wainwright Analytical Centre, University of New South Wales Sydney NSW 2052 Australia.ORCID https://orcid.org/0000-0002-0347-2105
Andre BongersBiological Resources Imaging Laboratory, Mark Wainwright Analytical Centre, University of New South Wales Sydney NSW 2052 Australia.
Kartika WardhaniCenter for Integrated Nanotechnologies, Sandia National Laboratories Albuquerque NM 87185 USA arpoerw@sandia.gov.ORCID https://orcid.org/0000-0001-9718-1028
Dale L HuberCenter for Integrated Nanotechnologies, Sandia National Laboratories Albuquerque NM 87185 USA arpoerw@sandia.gov.ORCID https://orcid.org/0000-0001-6872-8469
Richard D TilleySchool of Chemistry, University of New South Wales Sydney NSW 2052 Australia r.tilley@unsw.edu.au.ORCID https://orcid.org/0000-0003-2097-063X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanoparticle composition and crystal phase critically affect magnetic particle imaging performance by influencing magnetic properties. Compositional optimisation can be based on the iron oxide phase and potential dopants. Here, we show that 13 nm zinc-doped maghemite nanoparticles exhibit MPI signal intensity comparable to that of a 25 nm commercial tracer. Their smaller size and maghemite crystal phase make them promising alternative tracers for future MPI applications.

Identifiers

PMID42756983
PMCPMC13585089

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.