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