Junseok Kim
Korea University · 材料科学
研究室紹介
Professor Junseok Kim's research lab specializes in advanced materials and numerical methods for energy conversion and storage, with a strong focus on solid oxide fuel cells (SOFCs) and proton ceramic electrochemical cells (PCECs). The lab develops innovative sintering strategies—such as dual-phase reaction sintering and roll calendering—to enhance electrolyte densification and electrochemical performance while minimizing high-temperature degradation. It also combines computational modeling, including adaptive mesh refinement and operator-splitting methods, to solve complex partial differential equations governing phase separation and financial derivatives, demonstrating a multidisciplinary approach to materials science and numerical analysis. The lab’s work bridges materials synthesis, microstructure engineering, and mathematical modeling to enable efficient, low-temperature energy devices.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15A strategy of naturally diffused sintering aid enables the fabrication of defect-free bilayer electrolyte in solid oxide cells.
We consider a numerical method, the so-called an unconditionally gradient stable adaptive mesh refinement scheme, for solving the Cahn-Hilliard equation representing a model of phase separation in a binary mixture. The continuous problem has a decreasing total energy. We show the same property for the corresponding discrete problem by using eigenvalues of the Hessian matrix of the energy functional. An unconditionally gradient stable time discretization is used to remove the high-order time-step
The facilitated rearrangement of electrolyte particles<italic>via</italic>roll calendering owing to shearing effects enhances sinterability and electrochemical performance of solid oxide fuel cells (SOFCs).
Abstract The proton‐conducting oxides, widely employed as electrolytes in ceramic electrochemical cells, exhibit remarkable proton conductivity that facilitates efficient energy conversion processes. However, their inherent refractory nature poses a challenge in producing chemically stoichiometric and physically dense electrolytes within devices. Here a novel approach is presented, dual‐phase reaction sintering, which can overcome the inherent low sintering ability of the representative BaCeO 3‐
This paper presents the numerical valuation of the two-asset step-down equitylinked securities (ELS) option by using the operator-splitting method (OSM). The ELS is one of the most popular financial options. The value of ELS option can be modeled by a modified Black-Scholes partial differential equation. However, regardless of whether there is a closedform solution, it is difficult and not efficient to evaluate the solution because such a solution would be represented by multiple integrations. T
Proton ceramic electrochemical cells (PCECs) offer significant advantages for operation at intermediate-to-low temperature operation (≤600 °C), but their development is hindered by the challenge of achieving a fully dense electrolyte without compromising the hydrogen electrode’s high active surface area. The extensively studied electrolyte BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3-δ (BCZYYb4411) is widely known for its high proton conductivity and excellent chemical stability. However, it typically requi
We present a finite difference method for solving the Ohta--Kawasaki model, representing a model of mesoscopic phase separation for the block copolymer. The numerical methods for solving the Ohta--Kawasaki model need to inherit the mass conservation and energy dissipation properties. We prove these characteristic properties and solvability and unconditionally gradient stability of the scheme by using Hessian matrices of a discrete functional. We present numerical results that validate the mass c
This paper presents a wavelet multiresolution analysis based process fault detection algorithm to improve the accuracy of fault detection. Using Haar wavelet, coefficients that well reflect the process condition are selected and Hotelling's T2 control chart that uses the selected coefficients is constructed for assessing the process condition. To enhance the overall efficiency and accuracy of fault detection, the following two steps are suggested:First, a denoising method that is based on wavele
Abstract Traditional tooth whitening agents, particularly those based on hydrogen peroxide, are effective in achieving significant dental whitening but are prone to side effects such as tooth hypersensitivity and structural damage because of the highly concentrated production of reactive oxygen species (ROS). Although various nanoparticles, including metal oxides, ceramics, and piezoelectric materials, have been explored as alternative whitening agents, they often exhibit limitations such as ins
For a simple implementation, a linear convex splitting scheme was coupled with the Fourier spectral method for the Cahn--Hilliard equation with a logarithmic free energy. However, an inappropriate value of the splitting parameter of the linear scheme may lead to incorrect morphologies in the phase separation process. In order to overcome this problem, we present a nonlinear convex splitting Fourier spectral scheme for the Cahn--Hilliard equation with a logarithmic free energy, which is an approp
This paper presents accurate and efficient numerical methods for calculating thesensitivities of two-asset European options, the Greeks. The Greeks are important financialinstruments in management of economic value at risk due to changing market conditions. Theoption pricing model is based on the Black–Scholes partial differential equation. The model isdiscretized by using a finite difference method and resulting discrete equations are solved bymeans of an operator splitting method. For Delta, G
In the field of artificial intelligence and machine learning, physics-informed neural networks (PINNs) have received considerable attention because of their extensive applications in flow problems. PINN is a highly effective tool for discovering the intrinsic physics behind transport phenomena by incorporating governing equations into the training procedure of the neural network. The system of nonlinear partial differential equations is developed using non-Newtonian Casson fluid over a cylinder
We propose a new robust and accurate method for the numerical solution of medical image segmentation. The modified Allen-Cahn equation is used to model the boundaries of the image regions. Its numerical algorithm is based on operator splitting techniques. In the first step of the splitting scheme, we implicitly solve the heat equation with the variable diffusive coefficient and a source term. Then, in the second step, using a closed-form solution for the nonlinear equation, we get an analytic so