Metal–organic frameworks are of high interest for a range of energy and environmental applications due to their stable gas storage properties. A new machine learning approach based on a pre-trained multi-modal transformer can be fine-tuned with small datasets to predict structure-property relationships and design new metal-organic frameworks for a range of specific tasks.
- Yeonghun Kang
- Hyunsoo Park
- Jihan Kim
