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Abstract
The design of functional materials with desired properties is essential in driving technological advances in areas such as energy storage, catalysis and carbon capture
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. Generative models accelerate materials design by directly generating new materials given desired property constraints, but current methods have a low success rate in proposing stable crystals or can satisfy only a limited set of property constraints
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. Here we present MatterGen, a model that generates stable, diverse inorganic materials across the periodic table and can further be fine-tuned to steer the generation towards a broad range of property constraints. Compared with previous generative models
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, structures produced by MatterGen are more than twice as likely to be new and stable, and more than ten times closer to the local energy minimum. After fine-tuning, MatterGen successfully generates stable, new materials with desired chemistry, symmetry and mechanical, electronic and magnetic properties. As a proof of concept, we synthesize one of the generated structures and measure its property value to be within 20% of our target. We believe that the quality of generated materials and the breadth of abilities of MatterGen represent an important advancement towards creating a foundational generative model for materials design.
Academic Publication A generative model for inorganic materials design
Research Abstract & Technology Focus
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A generative model for inorganic materials design
Abstract The design of functional materials with desired properties is essential in driving technological advances in areas such as energy storage, catalysis ...
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A foundation model for atomistic materials chemistry
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AbstractStructure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. Generative SBDD methods leverage str...
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What is the core focus of the research titled 'A generative model for inorganic materials design'?
This literature focuses on: Abstract The design of functional materials with desired properties is essential in driving technological advances in areas such as energy storage, catalysis and carbon capture 1–3 ...
Are there open-source GitHub repositories related to A generative model for inorganic materials design?
Yes, open-source projects like PKU-YuanGroup/Helios (Helios: Real Real-Time Long Video Generation Model) are actively building upon these concepts.
Which startups are commercializing the technology behind A generative model for inorganic materials design?
Products like FreeCAD 1.1 are bringing this to market. Their focus is: Extremely powerful, completely free 3D CAD modeling.
What other academic literature is closely related to 'A generative model for inorganic materials design'?
Yes, highly correlated activity was mapped. An entry titled 'A generative model for inorganic materials design' discusses this: Abstract The design of functional materials with desired properties is essential in driving technological ad...
Are there commercial applications of 'A generative model for inorganic materials design' in market news publications?
Yes, highly correlated activity was mapped. An entry titled 'Improving crystal material property prediction with multi-view geometric graph transformer' discusses this: This study presents MGT, an AI model that leverages complementary geometric views of crystals to predict material properties more accurately, impro...
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Commercial Realization
Startups and Open Source tools heavily associated with the concepts explored in this paper.
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GitHubPKU-YuanGroup/Helios
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GitHubwanshuiyin/Auto-claude-code-research-in-sleep
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Product HuntFreeCAD 1.1
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Product HuntNano Banana 2