Evidence map›Paper›PMID 37360847›Full record

ArticleACS nanoscience Au2023

Complex Dispersion of Detonation Nanodiamond Revealed by Machine Learning Assisted Cryo-TEM and Coarse-Grained Molecular Dynamics Simulations.

Inga C Kuschnerus, Haotian Wen, Juanfang Ruan, Xinrui Zeng, Chun-Jen Su, U-Ser Jeng, George Opletal, Amanda S Barnard, Ming Liu, Masahiro Nishikawa and 1 more

Abstract read
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In one paragraph

Article in ACS nanoscience Au, 2023. 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. Diamond Chemistry: Advances and Perspectives.Angewandte Chemie (International ed. in English) · 2025
    Review
  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

11 authors.

Inga C KuschnerusSchool of Materials Science and Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia.
Haotian WenSchool of Materials Science and Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia.
Juanfang RuanElectron Microscope Unit, Mark Wainwright Analytical Centre, University of New South Wales, Sydney, New South Wales 2052, Australia.
Xinrui ZengSchool of Materials Science and Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia.
Chun-Jen SuNational Synchrotron Radiation Research Center, Hsinchu Science Park, Hsinchu 30076, Taiwan.
U-Ser JengNational Synchrotron Radiation Research Center, Hsinchu Science Park, Hsinchu 30076, Taiwan.ORCID https://orcid.org/0000-0002-2247-5061
George OpletalCSIRO Data61, Clayton, Victoria 3168, Australia.
Amanda S BarnardSchool of Computing, Australian National University, Acton, Australian Capital Territory 2601, Australia.ORCID https://orcid.org/0000-0002-4784-2382
Ming LiuDaicel Corporation, Osaka 530-0011, Japan.
Masahiro NishikawaDaicel Corporation, Osaka 530-0011, Japan.
Shery L Y ChangSchool of Materials Science and Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia.ORCID https://orcid.org/0000-0001-7514-4584

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the polydispersity of nanoparticles is crucial for establishing the efficacy and safety of their role as drug delivery carriers in biomedical applications. Detonation nanodiamonds (DNDs), 3-5 nm diamond nanoparticles synthesized through detonation process, have attracted great interest for drug delivery due to their colloidal stability in water and their biocompatibility. More recent studies have challenged the consensus that DNDs are monodispersed after their fabrication, with their aggregate formation poorly understood. Here, we present a novel characterization method of combining machine learning with direct cryo-transmission electron microscopy imaging to characterize the unique colloidal behavior of DNDs. Together with small-angle X-ray scattering and mesoscale simulations we show and explain the clear differences in the aggregation behavior between positively and negatively charged DNDs. Our new method can be applied to other complex particle systems, which builds essential knowledge for the safe implementation of nanoparticles in drug delivery.

Identifiers

PMID37360847
PMCPMC10288606

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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.