Myung LAB

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Office:N Center Block C 6F #86680

SungKyunKwan University (SKKU)

2066 Seobu-ro, Suwon-si, Republic of Korea

Our group’s interests lie at developing machine learning methods for understanding complex chemical processes in materials and surfaces. We develop machine learning potential algorithms using sparse Gaussian process regression. Also we study the structure of complex surface by developing machine learning methods for global optimization algorithms. More information on my research is available in research projects.

I’m Chang Woo Myung, an assistant professor in the Department of Energy Science at SungKyunKwan University. Before joining the faculty, I worked as a postdoc researcher at University of Cambridge with Prof. Angelos Michaelides and at ETH Zurich/USI with Prof. Michele Parrinello. I received my PhD in Chemistry under Prof. Kwang S. Kim at UNIST, Korea. Before that, I recieved my MS and BS at POSTECH, Korea.

The group is currently looking for talented Master, PhD students and postdocs. If you have a background in chemistry, physics and materials science and the above projects seem interesting, feel free to contact me.

News

Selected publications

  1. Adv.Ener.Mater.
    Al-doping driven suppression of capacity and voltage fadings in 4d-element containing Li-ion-battery cathode materials: machine learning and density functional theory
    Ha, Miran, Hajibabaei, Amir, Kim, Dong Yeon, Singh, Aditya Narayan, Yun, Jeonghun, Myung, Chang Woo*, and Kim, Kwang S.*
    Advanced Energy Materials 2022
  2. Adv.Ener.Mater.
    Challenges and Opportunities in Metal Halide Perovskites from Machine Learning Perspectives
    Myung, Chang Woo Myung, Hajibabaei, Amir, Cha, Ji-Hyun, and Kim, Kwang S.
    Adv. Energy Mater. 2022
  3. Phys.Rev.Lett.
    Prediction of a Supersolid Phase in High-Pressure Deuterium
    Myung, Chang Woo, Hirshberg, Barak, and Parrinello, Michele
    Phys. Rev. Lett. Jan 2022
  4. Phys.Rev.B
    Sparse Gaussian process potentials: Application to lithium diffusivity in superionic conducting solid electrolytes
    Hajibabaei, Amir, Myung, Chang Woo, and Kim, Kwang S.
    Phys. Rev. B Jun 2021
  5. Adv.Mater.
    Anharmonicity-Driven Rashba Cohelical Excitons Break Quantum Efficiency Limitation
    Myung, Chang Woo, and Kim, Kwang S.
    Advanced Materials Jun 2021
  6. Ener.Environ.Sci.
    Tuning metal single atoms embedded in NxCy moieties toward high-performance electrocatalysis
    Ha, Miran, Kim, Dong Yeon, Umer, Muhammad, Gladkikh, Vladislav, Myung, Chang Woo, and Kim, Kwang S.
    Energy Environ. Sci. Jun 2021
  7. Nat.Commun.
    Superb water splitting activity of the electrocatalyst Fe3Co(PO4)4 designed with computation aid
    Sultan, Siraj, Ha, Miran, Kim, Dong Yeon, Tiwari, Jitendra N., Myung, Chang Woo, Meena, Abhishek, Shin, Tae Joo, Chae, Keun Hwa, and Kim, Kwang S.
    Nature Communications Jun 2019
  8. Adv.Ener.Mater.
    A New Perspective on the Role of A-Site Cations in Perovskite Solar Cells
    Myung, Chang Woo, Yun, Jeonghun, Lee, Geunsik, and Kim, Kwang S.
    Advanced Energy Materials 2022/04/25 2018