Agentic AI and Machine Learning for Accelerated Materials Discovery and Applications

TL;DR

This review explores how agentic AI and machine learning accelerate materials discovery across chemistry, healthcare, and manufacturing, emphasizing efficient discovery, core concepts, and applications like flow chemistry, biosensors, and batteries.

Contribution

It provides a comprehensive overview of agentic AI's role in materials discovery, highlighting recent progress and diverse applications beyond traditional chemistry.

Findings

AI accelerates materials discovery processes

Agentic AI enhances efficiency in chemical and healthcare applications

Applications include flow chemistry, biosensors, and batteries

Abstract

Artificial Intelligence (AI), especially AI agents, is increasingly being applied to chemistry, healthcare, and manufacturing to enhance productivity. In this review, we discuss the progress of AI and agentic AI in areas related to, and beyond polymer materials and discovery chemistry. More specifically, the focus is on the need for efficient discovery, core concepts, and large language models. Consequently, applications are showcased in scenarios such as (1) flow chemistry, (2) biosensors, and (3) batteries.