An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties

Understand

Realizing general inverse design could greatly accelerate the discovery of new materials with user-defined properties.

• However, state-of-the-art generative models tend to be limited to a specific composition or crystal structure.
• Herein, we present a framework capable of general inverse design (not limited to a given set of elements or crystal structures), featuring a generalized invertible representation that encodes crystals in both real and reciprocal space, and a property-structured latent space from a variational autoencoder (VAE).
• In three design cases, the framework generates 142 new crystals with user-defined formation energies, bandgap, thermoelectric (TE) power factor, and combinations thereof.