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 ($K_{\text{bend}}$) and attractive strength ($\varepsilon$). Geometric constraints create a critical adsorption threshold $\varepsilon_k$. Below this threshold, increasing attraction converts loops and tails into extended trains, improving surface-parallel alignment. Beyond $\varepsilon_k$, saturation causes competitive displacement that fragments trains and reduces orientational order. Machine learning analysis identifies tail segment length $L_{\text{tail}}$ as the primary controlling parameter of interfacial thickness $\delta_{\mathrm{RMS}}$ (relative importance >89\%). The derived scaling laws describe how rigidity enhances tail extension efficiency. Attractive strength influences thickness indirectly through its effect on $L_{\text{tail}}$ within adsorption saturation constraints. These results establish two design principles: using rigidity-controlled tail manipulation for precise thickness tuning and applying $\varepsilon_k$-optimized attraction to maximize adsorption efficiency. This provides concrete guidelines for engineering nanocomposite interfaces.