# New AI Strategy Enhances Materials Discovery Process

**URL:** <https://community.materialssquare.com/t/new-ai-strategy-enhances-materials-discovery-process/519>\
**Category:** News\
**Created:** [July 30, 2024, 11:25am UTC](https://community.materialssquare.com/t/new-ai-strategy-enhances-materials-discovery-process/519 "2024-07-30T11:25:25Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![gabriele1](https://yyz1.discourse-cdn.com/flex003/user_avatar/community.materialssquare.com/gabriele1/32/20_2.png) [@gabriele1](https://community.materialssquare.com/u/gabriele1)\
**Post date:** [July 30, 2024, 11:25am UTC](https://community.materialssquare.com/t/new-ai-strategy-enhances-materials-discovery-process/519/1 "2024-07-30T11:25:25Z")

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Researchers from SLAC National Accelerator Laboratory and Stanford University have developed a novel AI-driven method to enhance materials discovery. This technique integrates machine learning with materials science, enabling “self-driving experiments” that autonomously determine the best parameters for new materials. This approach, published in _npj Computational Materials_, promises to expedite the discovery process, reduce costs, and improve efficiency. Applications extend to areas like climate change, quantum computing, and drug design. The algorithm’s open-source nature fosters global collaboration and innovation.

For more details, visit the article:

> **[New AI Strategy Enhances Materials Discovery Process - Exofeed](https://exofeed.nl/41/1191/new-ai-strategy-enhances-materials-discovery-process/)**
>
> Researchers Have Unveiled an Innovative Approach that Revolutionizes Material Discovery. A groundbreaking AI-driven method has been introduced by a team \[…\]