CMDD @ KAIST

CMDD @ KAIST

We develop battery materials by combining computation, AI and experiments.

We study how materials work and how to design them. Our research connects battery-material problems with atomistic modelling, AI and experimental methods.

CONNECTED DISCOVERY
Explore a method. Discover the connections.

Battery materials

The scientific problems connect the methods: structure, ion transport, redox chemistry and stability.

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Two InnoCORE postdoctoral openings · January 2027 | Graduate study · Spring 2027View openings →
Computational Materials Design & Discovery LabDepartment of Materials Science & Engineering

Overview

Understanding materials. Accelerating discovery.

We combine experimental and computational methods to understand materials properties and reaction mechanisms at the atomic scale and develop new energy storage materials, including electrodes and solid electrolytes for rechargeable batteries. First-principles calculations and density functional theory (DFT) connect atomic and electronic structures with ion transport, electrochemical reactions and degradation. Synthesis, characterization and cell testing help us discover new materials and validate predictions.

We also combine artificial intelligence (AI), machine learning (ML) and robotics in self-driving laboratories to accelerate battery materials development. These platforms collect large experimental datasets, search for promising materials, optimize compositions and synthesis conditions, and test predictions from AI and atomistic modeling through synthesis and measurements.

Keywords: lithium-ion batteries, electrodes, solid electrolytes, first-principles calculations, density functional theory (DFT), artificial intelligence, machine learning, self-driving lab.

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CMDD lab group outdoors at KAIST
Computational Materials Design & Discovery Lab · KAIST Meet the group →

Research themes

Different methods.
Connected questions.

Explore the materials we study and the methods we develop. A project can connect more than one theme.

01

Understand the material.
Improve the design.

Discovering new electrode and electrolyte materials and understanding how local structure, synthesis pathways and reaction mechanisms govern ion transport, energy storage and degradation.

The connection

Atomistic simulation, AI-assisted analysis and experimental validation.

From the lab · Past 12 months

Latest research & news.

Lab news

Poster award for Jaekyeong Han

Jaekyeong Han received a poster award at the LG Energy Solution Industry–Academia Conference for work on sodium-ion battery electrolytes using an autonomous battery system.

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Publication

Self-Driving Laboratories in Korea: A New Era of Autonomous Discovery

Jiho Hwang†, Seongmin Kim†, Sooyoun Lim, Juhwan Kim, Seungwoo Lee, Seonghyeon Min, Jisoo Song, Jeongwook Lim, Seonghun Hong, Jin-Ha Hwang, Youn-Suk Choi, Dong-Hwa Seo, Sang Soo Han, KangGeon Kim, Su-Hyun Yoo, Jungho Shin, Jang Wook Choi, Jaewook Nam, Jungwon Park, Jaeyune Ryu*, Yousung Jung*

Digital Discovery

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Bring your questions.
Build on ours.

Find your research interests in our themes, or start a conversation about a materials problem.

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