  A high-fidelity neural network-based force field, NN-F$^{3}$, is developed to
cover the strain states up to material failure and the non-equilibrium,
intermediate nature of fracture. Simulations of fracture in 2D crystals using
NN-F$^{3}$ reveal spatial complexities from lattice-scale kinks to sample-scale
patterns. We find that the fracture resistance cannot be quantified by the
energy densities of relaxed edges as in the literature. Instead, the fracture
patterns, critical stress intensity factors at the kinks, and energy densities
of edges in the intermediate, unrelaxed states offer reasonable measures for
the fracture toughness and its anisotropy.
