Covalent organic frameworks (COFs)
linked by poorly reversible
covalent bonds lack dynamic formation and cleavage, so the synthesis
of their single-crystal structures necessitates slow crystallization
rates to mitigate defect formation. This, however, inherently restricts
opportunities for facet-selective engineering beyond traditional compositional
and topological controls. To address this fundamental limitation,
we developed an acetal/CH3COOH protocol that paradoxically
accelerated crystallization while enhancing structural perfection,
reducing the synthesis time for 60 μm-sized single-crystal COF-300
to 1 h, while achieving crystal sizes of up to 120 μm within
48 h, and 300 μm after 30 days. Capitalizing on this accelerated
synthesis platform, we systematically interrogated crystallization
landscapes through multiparameter explorationmodulator chemoselectivity,
catalyst dosages, temporal evolution, and reactive temperatureto
decode possible growth mechanisms of single-crystal COFs. Based on
these, the relationship between reaction conditions and the crystal
size, size distribution, shape, and growth dynamics of single-crystal
COFs was trained and predicted by a machine learning (ML) model.