همایش بین المللی هوش مصنوعی

صفحه اصلی / دومین همایش بین المللی هوش مصنوعی

AI-Driven Materials Genome: Accelerated Discovery of Multi-Functional Sensing Materials

نویسندگان :

Farzane Hasheminia¹ Sadegh Sadeghzadeh² Behrouz Minaei-Bidgoli³

1- دانشگاه علم و صنعت ایران 2- دانشگاه علم و صنعت ایران 3- دانشگاه علم و صنعت ایران

کلمات کلیدی :

materials genome،ai-driven،materials design،sensor،dataset

چکیده :

Multi-functional sensing materials play a critical role in advanced technologies, including medical devices, environmental monitoring, and smart infrastructure. The discovery and development of these materials using traditional methods is often time-consuming and costly, relying predominantly on experimental testing. The materials genome approach, which integrates computational data, simulations and predictive analyses, provides a pathway to accelerate the materials discovery process. In this article, a roadmap for the design of multi-functional sensing materials is presented, encompassing data-driven strategies, predictive algorithms, and experimental feedback loops. Limitations such as data scarcity, model uncertainty, and challenges in result interpretability are also discussed, along with perspectives on developing faster and more efficient methods for materials discovery and optimization.