  We use a generative neural network model to create thousands of new,
one-dimensional materials. The model is trained using 508 stable
one-dimensional materials from the Computational 1D Materials Database (C1DB)
database. More than 500 of the new materials are shown with density functional
theory calculations to be dynamically stable and with heats of formation within
0.2 eV of the convex hull of known materials. Some of the new materials could
also have been obtained by chemical element substitution in the training
materials, but completely new classes of materials are also produced. The band
structures, electronic densities of states, work functions, effective masses,
and phonon spectra of the new materials are calculated, and the data are added
to C1DB.
