Аннотация:Our lives cannot be imagined without polymer networks, which rangewidely, from synthetic rubber to biological tissues. Their properties—elasticity, strain-stiffening and stretchability—are controlled by aconvolution of chemical composition, strand conformation and networktopology. Yet, since the discovery of rubber vulcanization by CharlesGoodyear in 1839, the internal organization of networks has remaineda sealed ‘black box’. While many studies show how network propertiesrespond to topology variation, no method currently exists that wouldallow the decoding of the network structure from its properties.We address this problem by analysing networks’ nonlinear responsesto deformation to quantify their crosslink density, strand flexibility andfraction of stress-supporting strands. The decoded structural informationenables the quality control of network synthesis, comparison of targetedto actual architecture and network classification according to theeffectiveness of stress distribution. The developed forensic approachis a vital step in future implementation of artificial intelligence principlesfor soft matter design.