  In computational materials science, predicting the yield strain of
crosslinked polymers remains a challenging task. A common approach is to
identify yield as the first critical point of stress-strain curves simulated by
molecular dynamics (MD). However, in such cases the underlying data can be
excessively noisy, making it difficult to extract meaningful results. In this
work, we propose an alternate method for identifying yield on the basis of
deformation-recovery simulations. Notably, the corresponding raw data (i.e.
residual strains) produce a sharper signal for yield via a transition in their
global behavior. We analyze this transition by non- linear regression of
computational data to a hyperbolic model. As part of this analysis, we also
propose uncertainty quantification techniques for assessing when and to what
extent the simulated data is informative of yield. Moreover, we show how the
method directly tests for yield via the onset of permanent deformation and
discuss recent experimental results, which compare favorably with our
predictions.
