Fig. 2: InvDesFlow-AL for the generation of low formation energy materials.
From: InvDesFlow-AL: active learning-based workflow for inverse design of functional materials
a InvDesFlow-AL employs a crystal generation model to generate new crystal structures, followed by formation energy prediction using FormEGNN. A lower threshold is applied to retain newly generated materials for fine-tuning the generative model. After five iterations, a progressive decrease in formation energy is observed. b InvDesFlow-AL adopts the same strategy to generate materials with low Ehull. Through multiple rounds of generation, a total of 1,610,600 new crystal structures with Ehull < 50 meV have been obtained, expanding the chemical space exploration to a broader range of atomic species. c Crystal structures containing 2, 3, ..., and up to 7 elements generated by InvDesFlow-AL.
