Simulation-Guided Atomic Layer Deposition Enables Deterministic Interfacial Mechanics for Predictive Nanoimprint...

Nanoimprint lithography (NIL) is a key enabler for next-generation nanomanufacturing, yet its industrial scalability remains constrained by persistent challenges at the mold-resist interface, including mold fracture, structural deformation, and inefficient demolding. These limitations arise from the lack of coordinated control over adhesion, friction, and stress evolution during imprinting. Guided by simulation-based insights that identify tunable interfacial layers as a critical lever, we employ conformal molecular/atomic layer deposition (MLD/ALD) as a rational strategy to actively regulate these coupled interactions. Here we systematically investigate MLD/ALD-grown graphene, Al₂O₃, and polyurea as model interfacial layers for NIL molds. By integrating molecular dynamics simulations, finite element modeling, atomic force microscopy (AFM), and experimental imprinting, we establish quantitative links between coating chemistry, interfacial energetics, stress evolution, and pattern fidelity. Among the materials studied, graphene exhibits the most favorable balance of properties, reducing peak imprint-induced mechanical stress to ∼20% of that of bare silicon while maintaining ultralow surface energy (≤0.13 J m^-2) and friction coefficient (≤0.1), thereby minimizing structural deformation during imprinting. We further identify coating-dependent thresholds in adhesion, friction, and elastic modulus that define a practical design window for high-performance NIL molds. This work introduces a unified and predictive framework for active interfacial control via ALD coatings in NIL, providing actionable guidelines for coating selection and establishing a pathway toward durable molds, efficient demolding, and reproducible, high-precision nanoscale pattern transfer.