My interests are simulation of reactions occurring inside lithium-ion batteries, building 'transferable Machine Learning(ML) potential' that can be applied in various ways using machine learning, Multi-task machine learning using 'SGPR'(Sparse Gaussian Process Regression) which developed from Gaussian process, calculation of theoretical redox potential for several molecules in an aqueous environment.
I'm DongGeon Kim, in the master's course. Recently, the importance of carbon neutrality has emerged worldwide. Accordingly, the share of eco-friendly energy is increasing. With this trend, the demand for batteries, which are the main power source for electric vehicles, potable mobility, gadgets, etc... is increasing.
There are various types of rechargeable batteries(Lead_Acid, Ni-Cd, Ni-MH, Lithium-ion, Li-polymer, etc ...). But Lithium-ion batteries with good efficiency are mostly used nowadays. However, there are still critical problems with the stability of Lithium-ion batteries, the main cause of which is explosion due to evaporation and ignition of liquid electrolyte. Since there is still a lack of theoretical understanding of the correlation between lithium ions and liquid electrolytes, this problem took my interest.
What I did recently is theoretical multi-task Machine Learning and SGPR studying. And binding energy and Lewis acidity calculations of the MOF+Lithium salt model used for composite solid electrolytes.
In the laboratory, I'm in charge of managing the homepage(in progress...) and recording information on the wiki(to be added). Please feel free to contact us by e-mail. :)
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According to the flow, my research goals are as below.
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Understanding & improvement of sparse gaussian process regression(SGPR) based multi-task code.
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Calculation of theoretical redox potential in Aqueous environment.
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Building Transferable ML potential.
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