SNU CBE

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

2026 · Advanced Intelligent Systems

저자

Cristiano Malica, Kostya S. Novoselov, Seong-Min Kim, 정유성 (Yousung Jung), Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Mariví Fernández-Serra, Sara Navarro Rodriguez, Aakash Ashok Naik, Janine George, Ömer H. Omar, Victor Trinquet, Gian‐Marco Rignanese, A. Ustyuzhanin, Sònia Conesa-Boj, Juan Rojo, Minh Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, José H. García, Romain Gautier 외 14명

연구주제

Machine Learning in Materials Science · Advanced Chemical Physics Studies · Computational Drug Discovery Methods

NTIS 과학기술표준분류

화학 > 융합화학 > 화학정보학

배정 근거: 지원 과제·키워드 근거가 없어 AI가 논문 제목·초록을 읽고 고른 분류(정책 연계 맵과 같은 방법).

AI 연구 키워드·방법

autonomous experimentation energy storage material functional materials design

기계학습

키워드 (OpenAlex)

artificial intelligence in materials science machine learning for materials design high-performance simulation autonomous experimentation energy storage materials biomedical materials nanoelectronics quantum devices

초록

Artificial intelligence (AI) is transforming the way materials are designed, understood, and manufactured. This Perspective examines how recent advances in data‐driven modeling, high‐performance simulation, and autonomous experimentation are converging to accelerate the discovery of functional materials for next‐generation technologies—from energy storage and biomedicine to nanoelectronics and quantum devices. We outline ongoing strategies to embed AI across the materials design workflow—from synthesis and characterization to large‐scale simulations enabled by machine learning techniques and approaching ab initio accuracy—and discuss key challenges that remain on the path toward intelligent (bio)materials discovery.

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

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교수 1

정유성

연구주제 1

Machine Learning in Materials Science

정책분야 1

융합화학

방법 1

기계학습