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Growth driven phase transitions in Zinc Oxide nanoparticles through machine-learning assisted simulations

Materials Science 2026-04-14 v2 Mesoscale and Nanoscale Physics

Abstract

This study investigates the formation of zinc oxide (ZnO) nanoparticles, a material of significant technological interest with complex structural properties, through atom-by-atom deposition modeling a process common in bottom-up synthesis. Our findings demonstrate that, although the body-centered tetragonal (BCT) structure is thermodynamically stable at equilibrium for small particle sizes, the deposition process induces a crystal-to-crystal phase transition into the more stable wurtzite (WRZ) phase. This transformation is facilitated by a specific redistribution of the nanoparticle ions, which effectively compensates the emerging polar facets at the moment of transition. These insights offer a deeper understanding of oxide nanoparticle formation, which should ultimately help the design of materials with targeted structural features.

Keywords

Cite

@article{arxiv.2511.19025,
  title  = {Growth driven phase transitions in Zinc Oxide nanoparticles through machine-learning assisted simulations},
  author = {Quentin Gromoff and Magali Benoit and Jacek Goniakowski and Carlos R. Salazar and Julien Lam},
  journal= {arXiv preprint arXiv:2511.19025},
  year   = {2026}
}

Comments

9 pages, 8 figures

R2 v1 2026-07-01T07:51:58.579Z