Inverse design with deep generative models: next step in materials discovery
Shuaihua Lu, Qionghua Zhou, Xinyu Chen, Zhilong Song, Jinlan Wang
Abstract
Data-driven inverse design for inorganic functional materials is a rapidly emerging field, which aims to automatically design innovative materials with target properties and to enable property-to-structure material discovery.
Topics & Concepts
InverseGenerative grammarProperty (philosophy)Computer scienceField (mathematics)Inverse problemData scienceArtificial intelligenceMathematicsGeometryEpistemologyMathematical analysisPhilosophyPure mathematicsMachine Learning in Materials ScienceX-ray Diffraction in CrystallographyComputational Drug Discovery Methods