Jae-Min Myoung

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The process modeling for the growth rate in pulsed laser deposition (PLD)-grown ZnO thin films was investigated using neural networks (NNets) based on the back-propagation (BP) algorithm and the process recipes was optimized via genetic algorithms (GAs). Two input factors were examined with respect to the growth rate as the response factor. D-optimal(More)
The effective synthesis of two-dimensional transition metal dichalcogenides alloy is essential for successful application in electronic and optical devices based on a tunable band gap. Here we show a synthesis process for Mo1-xWxS2 alloy using sulfurization of super-cycle atomic layer deposition Mo1-xWxOy. Various spectroscopic and microscopic results(More)
In this paper, the neural network based modeling for electrical characteristics of the HfO 2 thin films grown by metal organic molecular beam epitaxy was investigated. The accumulation capacitance and the hysteresis index are extracted to be the main responses to examine the characteristics of the HfO 2 dielectric films. The input process parameters were(More)
This work reports the self-limiting synthesis of an atomically thin, two dimensional transition metal dichalcogenides (2D TMDCs) in the form of MoS2. The layer controllability and large area uniformity essential for electronic and optical device applications is achieved through atomic layer deposition in what is named self-limiting layer synthesis (SLS); a(More)
We report low-temperature solution-processed p-CuO nanorods (NRs)/n-ZnO NRs heterojunction light emitting diode (LED), exploiting the native point defects of ZnO NRs. ZnO NRs were synthesized at 90 °C by using hydrothermal method while CuO NRs were synthesized at 100 °C by using microwave reaction system. The electrical properties of newly synthesized CuO(More)
The interactions between a graphene sheet and an aluminium (111) layer in carbon-aluminium nanocomposite systems were investigated for various interfacial configurations using an ab initio simulation based on density functional theory. Dispersion relations and electron density distributions obtained for various interface registries suggest that the bond(More)
Principal component analysis (PCA) based neural network models for the HfO 2 thin film characteristics, such as the accumulation capacitance and the hysteresis index, grown by metal organic molecular beam epitaxy are presented. Considering the number of the principal components, the various input parameters are applied to the neural network modeling. In(More)
The process modeling for the growth rate of pulsed laser deposition (PLD)-grown ZnO thin films was investigated using neural networks (NNets) based on the back-propagation (BP) algorithm and PCA-based NNets using photoluminescence (PL) data. D-optimal experimental design was performed and the growth rate was characterized by NNets. PCA-based NNets were then(More)
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