MatterGen
M
Mattergen
Overview :
Launched by Microsoft Research, MatterGen is a generative AI tool for material design. It can directly generate new materials with specific chemical, mechanical, electronic, or magnetic properties based on application design requirements, providing a new paradigm for material exploration. This tool is expected to accelerate the R&D process for novel materials, lower R&D costs, and play a significant role in fields such as batteries, solar cells, and CO2 adsorbents. Currently, MatterGen's source code is open-sourced on GitHub for public use and further development.
Target Users :
Target audience includes materials scientists, researchers, and engineers in related fields. They can leverage MatterGen to swiftly explore new materials, expedite R&D processes, reduce experimental costs, and enhance the efficiency and success rate of material design.
Total Visits: 1154.6M
Top Region: US(20.76%)
Website Views : 69.6K
Use Cases
When searching for new materials with a high bulk modulus, MatterGen can continuously generate qualifying candidate materials, whereas traditional screening methods stagnate due to the depletion of known candidates.
In collaboration with the Shenzhen Institute of Advanced Technology, MatterGen successfully generated and experimentally synthesized a novel material TaCr2O6, with a measured bulk modulus deviating by less than 20% from the design specifications.
MatterGen works in synergy with MatterSim, creating a flywheel that accelerates new material simulation and exploration, further enhancing material R&D efficiency.
Features
Generate new materials directly using diffusion models instead of filtering existing materials.
Generate materials based on specific design requirements such as chemical composition, crystal symmetry, or material properties.
Achieve industry-leading levels in generating stable, unique, and novel structures.
Handle compositional disorder in materials, providing new definitions of novelty and uniqueness.
Validate the feasibility of generated materials through experimental synthesis.
How to Use
1. Visit MatterGen's GitHub page to access the source code and related documentation.
2. Define the design requirements for materials based on your research needs, such as chemical composition and physical properties.
3. Utilize the MatterGen model to input design requirements and generate corresponding new material structures.
4. Analyze and evaluate the generated material structures to filter out candidates that meet expectations.
5. Conduct experimental synthesis to validate the actual performance of the materials, optimizing design requirements and iterating the generation process.
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase