# Discovering novel materials autonomously

**URL:** <https://community.materialssquare.com/t/discovering-novel-materials-autonomously/594>\
**Category:** News\
**Created:** [August 27, 2024, 1:57pm UTC](https://community.materialssquare.com/t/discovering-novel-materials-autonomously/594 "2024-08-27T13:57:40Z")\
**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:** [August 27, 2024, 1:57pm UTC](https://community.materialssquare.com/t/discovering-novel-materials-autonomously/594/1 "2024-08-27T13:57:40Z")

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This article discusses the work of Qijun Hong, an assistant professor at Arizona State University, who is advancing materials science by using AI and quantum mechanics to autonomously predict the properties of new materials. Hong’s research aims to accelerate the discovery of materials with unique properties for various applications, such as more resilient engines and better aerospace materials. He has developed tools like SLUSCHI and MAPP to automate calculations, significantly speeding up the research process. Hong recently received the 2024 CALPHAD Young Leader Award for his contributions.

For more details, you can read the full article here:

> **[Discovering novel materials autonomously](https://fullcircle.asu.edu/faculty/discovering-novel-materials-autonomously/)**
>
> ASU researcher Qijun Hong is the third person ever to receive the CALPHAD Young Leader Award for advancing the discovery process of new materials.