  Accurate prediction of the stability of molecular crystals is a longstanding
challenge, as often minuscule free energy differences between polymorphs are
sensitively affected by the description of electronic structure, the
statistical mechanics of the nuclei and the cell, and thermal expansion. The
importance of these effects has been individually established, but rigorous
free energy calculations, which simultaneously account for all terms, have been
prevented by prohibitive computational costs. Here we reproduce the
experimental stabilities of polymorphs of three prototypical compounds --
benzene, glycine, and succinic acid -- by computing rigorous ab initio Gibbs
free energies, at a fraction of the cost of conventional harmonic
approximations. This is achieved by a bottom-up approach, which involves
generating machine-learning potentials to calculate surrogate free energies and
subsequently calculating true ab initio free energies using inexpensive free
energy perturbations. Accounting for all relevant physical effects is no longer
a daunting task and provides the foundation for reliable structure predictions
for more complex systems of industrial importance.
