Facet-Dependent Zippering Mechanisms in Nanodiamond Coalescence Revealed by Machine-Learning Molecular Dynamics

Abstract

The assembly of nanodiamonds (NDs) dictates their emergent structural and functional states, yet the atomistic mechanisms governing this process remain largely unresolved. In this work, the facet-dependent interactions and temperature-regulated aggregation of NDs are investigated through large-scale deep potential molecular dynamics simulations using a newly developed machine-learning potential. Utilizing dimerized truncated-octahedral C1126 clusters as a model system, we identify a fundamental dichotomy in the assembly motifs: the {100} facets promote spontaneous covalent fusion even at ambient conditions, whereas graphitized {111} surfaces interact predominantly through noncovalent π–π stacking. Under thermal activation, a progressive transition is observed from nonbonded or weakly interacting contacts to increasingly reconstructed interfaces, followed by extensive and ultimately complete coalescence, establishing temperature as a critical parameter for tuning interfacial morphology. At 1500 K, where clear fusion occurs, the two interfaces follow distinct pathways: a center-initiated bidirectional zippering for {100}-{100} and an edge-initiated unidirectional zippering for {111}-{111}. In both cases, bonding is dominated by outer-shell atoms, and the resulting peanut-like core–shell structures contain undercoordinated and curved interfacial motifs that may serve as candidate anchoring environments for metal species.