Welcome to Professor Jihan Kim's Research Group. 

We are a computational chemistry group at KAIST that focuses on solving some of today's most important energy and environmental related problems.  We aim to develop accurate and efficient models to create, in silico, materials that can be used for wide range of applications such as carbon capture, methane/hydrogen storage, and batteries.   Finally, we are not afraid to use concepts from many other disciplines (e.g. computer sciences, artificial intelligence, music, graphics) to develop unique solutions that can differentiate our group.  



 

8/2019:   Ohmin's paper "Computational-aided discovery of connected metal-organic frameworks" has been published in Nature Communications.  This was a collaborative work with Prof. Hoi Ri Moon's group (UNIST), we demonstrated that we can "connect" two different MOFs into core-shell structure from molecular level design.  This is the first instance where synthesis of composite MOFs originated from theoretical predictions and we anticipate that computational tools will become more prominent when it comes designing composite nanomaterials.  Congratulations to everyone involved!

3/2019:   Hoeyeon's paper "Computational Analysis of Linker Defective Metal-organic Frameworks for Membrane Separation Applications" has been accepted to Langmuir.  In this work, we have analyzed the effect of linker vacancies on the diffusion properties of metal-organic frameworks.  As such, we have come to the conclusion that if we take linker vacancies into account, the rankings of the best membrane separation materials changes (sometimes drastically) and as such, this should be taken into account for rational materials design.  Congrats!

3/2019:   We welcome three new students to the group: Mingyu Jeon, Junkil Park, and Yeonghun Kang!  

1/2019:   Sangwon's paper "Predicting performance limits of methane gas storage in zeolites with artificial neural network" has been accepted to Journal of Materials Chemistry A.  In this work, we have developed a neural net work called ESGAN (energy shape generative adversarial network) to create "energy shapes" of materials that can let us deduce the maximum performance limits for a given class of materials.  Congratulations!

1/2019:   Prof. Jihan Kim has been awarded the 2018년 KAIST 공과대학 기술 혁신상.  

1/2019:   Hoeyeon has graduated with her master's degree and she will be working at the Samsung SDI.  We wish her the best of luck in the future.