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Microsoft Search today introduced a powerful new AI system that generates new materials with specific desired properties, potentially accelerating the development of better batteries, more efficient solar cells and other critical technologies.
The system, called MatterGenrepresents a fundamental change in the way scientists discover new materials. Rather than screening millions of existing compounds – the traditional approach which can take years – MatterGen directly generates new materials based on desired characteristics, similar to how AI image generators create images from descriptions textual.
“Generative models provide a new paradigm for materials design by directly generating entirely new materials given desired property constraints,” said Tian Xie, senior research director at Microsoft Research and lead author of the study published today in Nature. “This represents a major step forward toward creating a universal generative model for materials design.”
How Microsoft’s AI engine works differently from traditional methods
MatterGen uses a specialized type of AI called diffusion model – similar to those behind image generators like SLAB – but suitable for working with three-dimensional crystal structures. It gradually refines random arrangements of atoms into stable, useful materials that meet specified criteria.
The results exceed previous approaches. According to the research paper, materials produced by MatterGen are “more than twice as likely to be novel and stable, and more than 15 times closer to the local energy minimum” compared to previous AI approaches. This means that the materials generated are both more likely to be useful and physically possible to create.
In a striking demonstration, the team collaborated with scientists from the Chinese center Shenzhen Institutes of Advanced Technology synthesize a new material, TaCr2O6that MatterGen had designed. Real-world hardware closely matched the AI predictions, validating the practical utility of the system.
Real-world applications could transform energy storage and computing
The system is particularly distinguished by its flexibility. It can be “fine-tuned” to generate materials with specific properties – from particular crystal structures to desired electronic or magnetic characteristics. This could be invaluable for designing materials for specific industrial applications.
The implications could be far-reaching. New materials are key to advancing technologies in energy storage, semiconductor design and carbon capture. For example, better materials for batteries could accelerate the transition to electric vehicles, while more efficient materials for solar cells could make renewable energy more profitable.
“From an industrial point of view, the potential here is huge,” Xie said. “Human civilization has always depended on material innovations. If we can use generative AI to make materials design more efficient, it could accelerate progress in sectors like energy, healthcare and beyond.
Microsoft’s open source strategy aims to accelerate scientific discovery
Microsoft released MatterGen source code under an open source license, allowing researchers around the world to build on the technology. This decision could accelerate the impact of the system in various scientific fields.
The development of MatterGen is part of the broader framework of Microsoft AI for science initiative, which aims to accelerate scientific discovery using AI. The project is integrated into Microsoft Azure Quantum Elements platformpotentially making the technology accessible to businesses and researchers via cloud computing services.
However, experts caution that while MatterGen represents a significant advance, moving from computer-designed materials to practical applications still requires extensive testing and refinement. The system’s predictions, although promising, require experimental validation before their industrial deployment.
Nonetheless, this technology represents a significant advance in the use of AI to accelerate scientific discovery. As Daniel Zügner, principal investigator of the project, emphasized: “We are deeply committed to research that can have a positive and real impact, and this is only the beginning. »
