In the past detonation nanodiamonds (DNDs), sized 3–5 nm, have been praised for their colloidal stability in aqueous media, thereby attracting vast interest in a wide range of applications including nanomedicine. More recent studies have challenged the consensus that DNDs are monodispersed after their fabrication process, with their aggregate formation dynamics poorly understood. Here we reveal that DNDs in aqueous solution, regardless of their post-synthesis de-agglomeration and purification methods, exhibit hierarchical aggregation structures consisting of chain-like and cluster aggregate morphologies. With a novel characterization approach combining machine learning with direct cryo-transmission electron microscopy and with X-ray scattering and vibrational spectroscopy, we show that their aggregate morphologies of chain and cluster ratios and the corresponding size and fractal dimension distributions vary with the post-synthesis treatment methods. In particular DNDs with positive ζ-potential form to a hierarchical structure that assembles aggregates into large networks. DNDs purified with the gas phase annealing and oxidation tend to have more chain-like aggregates. Our findings provide important contribution in understanding the DND interparticle interactions to control the size, polydispersity and aggregation of DNDs for their desired applications.



Publication Status

Open Access


Australian Research Council, Grant 1R15EY029813-01A1

Keywords and Phrases

Cryo-TEM; Machine learning; Nanodiamonds; SAXS

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


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© 2023 Elsevier, All rights reserved.

Publication Date

01 Nov 2023

Included in

Chemistry Commons