응용역학 및 재료설계 연구실

Research

Combinatorial Studies of Materials

We develop novel functional/structural materials based on combinatorial approaches. Thin film deposition technique is used to synthesize thin films with composition spread. Rapid characterization tools have been developed to map out composition dependent properties of thin films.  This methodology allows rapid mapping of previously unexplored compositional landscape, allowing development of compounds with exceptional properties. This technique has been used to develop and study metallic glasses and ultra-high temperature ceramics.

Sensor arrays for

High-throughput characterizations

We utilize MEMS-processed sensor arrays, such as micro-tensile testers and nanocalorimeters to perform high-throughput and combinatorial characterization of thin films with composition spreads. Advanced robotics and image processing techniques are used to further speed up material characterizations/discovery. By using this methods, we characterize mechanical properties as well as thermal properties of materials.

 

Exp & Modeling

Combination of experimentation and modeling can guide each other providing a significant understanding of materials behavior. In order to understand materials behavior found from combinatorial experiments, we use sophisticated modeling tools, such as ab-initio simulations.

 

Materials engineering for robotics

Integration of novel materials to robots and sensors can provide unique opportunities to develop unprecedented systems. We use metallic glasses, polymers, liquid metals, shape memory alloys to develop multi-functional robotic systems.

Injun Oh†, Donghyun Park†, Euimin Cheong, Haechan Jo, Sanghun Park, Daegun You, Taeyeop Kim, Yuhyun Park, Kyunghoon Kim, Gi-Dong Sim, Chansun Shin* and Dongwoo Lee*
“Anisotropic He-ion irradiation damages in nanocolumnar W thin films,”
Extreme Mechanics Letters, 2020, Vol. 41, No. 100984, pp. 0~ 0

Daegun You, Shraddha Ganorkar, Sooran Kim, Keonwook Kang, Won-Yong Shin*, Dongwoo Lee*,
“Machine Learning-based Prediction Models for Formation Energies of Interstitial Atoms in HCP Crystals,”
Scripta Materialia, 2020, Vol. 183, No. 0, pp. 1~ 5

Daegun You, Shraddha Ganorkar, Minsoo Joo, Donghyun Park, Sooran Kim, Keonwook Kang*, and Dongwoo Lee*
Ab initio study of H, B, C, N, O, and self-interstitial atoms in hcp-Zr,
Journal of Alloys and Compounds,, 2019, Vol. 787, No. 0, pp. 631~ 637