Rigidity-driven tail extension controls interfacial thickness in polymer-nanoparticle composites

We employ coarse-grained molecular dynamics simulations to investigate interfacial reorganization in polymer-nanoparticle composites, focusing on the competing effects of chain rigidity (Kbend) and attractive strength (ɛ). Geometric constraints create a critical adsorption threshold ɛk. Below this threshold, increasing attraction converts loops and tails into extended trains, improving surface-parallel alignment. Beyond ɛk, saturation causes competitive displacement that fragments trains and reduces orientational order. Machine learning analysis identifies the average tail segment length, ⟨Ltail⟩, as the primary controlling parameter of interfacial thickness δRMS (relative importance >89%). The derived scaling laws describe how rigidity enhances tail extension efficiency. Attractive strength influences thickness indirectly through its effect on ⟨Ltail⟩ within adsorption saturation constraints. These results establish two design principles: using rigidity-controlled tail manipulation for precise thickness tuning and applying ɛk-optimized attraction to maximize adsorption efficiency. This provides concrete guidelines for engineering nanocomposite interfaces.