Elucidating the kinetics of surface reconstruction is fundamentally important yet inherently challenging due to the complex collective atomic motions occurring across high-dimensional potential-energy landscapes. Here, we combine machine-learning-based molecular dynamics simulations enhanced by well-tempered metadynamics with in situ environmental transmission electron microscopy to directly uncover the critical role of surface titanium diffusion in driving the structural evolution of the ${\mathrm{TiO}}_2(110)\text{−}(1\times 2)$ reconstruction. Under oxygen-deficient conditions, the ${\mathrm{TiO}}_2(110)\text{−}(1\times 2)$ reconstruction remains thermodynamically stable, and surface Ti migration is largely suppressed. In contrast, under oxygen-rich conditions, the surface Ti atomic rows exhibit pronounced splitting and migration, facilitated by the incorporation of additional oxygen atoms that enhance Ti mobility. Our simulations demonstrate that these oxygen-promoted processes can induce structural transformations of the ${\mathrm{TiO}}_2(110)\text{−}(1\times 2)$ reconstruction, resulting in transitions from double-row to single-row or triple-row configurations. These predictions are further validated by experimental observations. This Letter establishes a microscopic mechanism for rutile surface reconstruction kinetics and provides valuable insights for the controlled manipulation of surface structures under varying chemical environments.

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• First-principles calculations
• Surface diffusion
• Surface reconstruction
• Thermodynamics
• Transmission electron microscopy