Forensics of Bottlebrush Networks: Decoding Network Topology and Synthesis History from Nonlinear Deformation

The elasticity of polymer networks is governed by the connectivity of load-bearing strands, yet their topology, fixed during synthesis, cannot generally be inferred from the nominal formulation. Structural parameters of the as-prepared network, including strand degree of polymerization, crosslink functionalities, loops, dangling structures, and other defects, depend on the synthesis history. Here, we demonstrate that nonlinear mechanical response can be used as a forensic probe for decoding this hidden network structure and detecting flaws in synthesis. We apply the forensics methodology to poly(n-butyl acrylate) bottlebrush networks prepared in independent synthetic trials using nominally identical formulations. Analysis of the structural modulus and strain-stiffening parameter obtained from nonlinear deformation determines whether a series of networks possesses a self-similar topology and differs primarily in crosslink density. For self-similar networks, the forensics framework provides the actual degree of polymerization between crosslinks, the topology coefficient of the load-bearing strands, and the contribution of non-load-bearing strands. Independent synthetic trials reveal that nominally identical formulations and synthetic protocols may either reproduce the same topological scaling or generate distinctly different network structures. These results establish network forensics as a characterization method that connects nonlinear mechanical response to network topology and provides quantitative feedback for refining network synthesis.