Developing accessible polymeric materials is a challenging task for generative AI models. Here, the authors show that a domain-specific language enables the use of historical data to tune generative models to produce experimentally achievable material designs.
- Nathaniel H. Park
- Matteo Manica
- Pedro L. Arrechea
