• Journal of the Korean institute of surface engineering
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• v.47 no.5
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• pp.227-232
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• 2014

In this study, we propose the application of doping process technology for atmospheric pressure plasma. The plasma treatment means the wafer is warmed via resistance heating from current paths. These paths are induced by the surface charge density in the presence of illuminating Argon atmospheric plasmas. Furthermore, it is investigated on the high-concentration doping to a selective partial region in P type solar cell wafer. It is identified that diffusion of impurities is related to the wafer temperature. For the fixed plasma treatment time, plasma currents were set with 40, 70, 120 mA. For the processing time, IR(Infra-Red) images are analyzed via a camera dependent on the temperature of the P type wafer. Phosphorus concentrations are also analyzed through SIMS profiles from doped wafer. According to the analysis for doping process, as applied plasma currents increase, so the doping depth becomes deeper. As the junction depth is deeper, so the surface resistance is to be lowered. In addition, the surface charge density has a tendency inversely proportional to the initial phosphorus concentration. Overall, when the plasma current increases, then it becomes higher temperatures in wafer. It is shown that the diffusion of the impurity is critically dependent on the temperature of wafers.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2305-2314
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• 2023

The governing equations of atmospheric dispersion most often taking the form of a second-order partial differential equation (PDE). Currently, typical computational codes for predicting atmospheric dispersion use the Gaussian plume model that is an analytic solution. A Gaussian model is simple and enables rapid simulations, but it can be difficult to apply to situations with complex model parameters. Recently, a method of solving PDEs using artificial neural networks called physics-informed neural network (PINN) has been proposed. The PINN assumes the latent (hidden) solution of a PDE as an arbitrary neural network model and approximates the solution by optimizing the model. Unlike a Gaussian model, the PINN is intuitive in that it does not require special assumptions and uses the original equation without modifications. In this paper, we describe an approach to atmospheric dispersion modeling using the PINN and show its applicability through simple case studies. The results are compared with analytic and fundamental numerical methods to assess the accuracy and other features. The proposed PINN approximates the solution with reasonable accuracy. Considering that its procedure is divided into training and prediction steps, the PINN also offers the advantage of rapid simulations once the training is over.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.16-19
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• 2018

The development speed of semiconductor and display device manufacturing technology is growing faster than the development speed of process equipment. So, there is a growing need for process diagnostic technology that can measure process conditions in real time and directly. In this study, a plasma diagnosis was carried out using impedance variation due to the plasma discharge. Variation of the measurement impedance appears as a voltage change at the reference impedance, and the plasma density is calculated using this. The above experiment was conducted by integrating the plasma diagnosis system and the linear atmospheric pressure DBD plasma source. It was confirmed that plasma density varies depending on various parameters (gas flow rate, $Ar/O_2$ mixture ratio, Input power).

• Asian Journal of Atmospheric Environment
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• v.5 no.3
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• pp.172-180
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• 2011

The transfer of microorganisms is important process for ecosystems. Microorganisms in dryland can transport itself to wetland through atmospheric diffusion, but only few papers reported about the atmospheric bioaerosol present over dryland. We carried out the direct sampling using a tethered balloon over Dunhuang City, China's northwestern dryland. Bioaerosols were collected using a tethered balloon with a bioaerosol collector at 820 m above the ground (1,960 m above the sea level) around noon on August 17, 2007. The bioaerosols were cultured after the collection at Dunhuang Meteorological observatory. Two strains of molds were isolated using the Nutrient agar medium. About 400-bp 18S rRNA partial sequences were amplified by PCR and determined afterwards. The results of a homology search by 18S rRNA sequences of isolates in DNA databases (GenBank, DDBJ, and EMBL) and an observation of the form revealed that two bioaerosols in the convective mixed layer over Dunhuang City were Cladosporium sp. and Aspergillus sp.

• Proceedings of the Korean Vacuum Society Conference
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• 2006.02a
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• pp.134-134
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• 2006

• Proceedings of the KSRS Conference
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• v.2
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• pp.997-1000
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• 2006

We estimate the net heat flux in the tropical and subtropical Atlantic Ocean using satellite data. These fluxes are related to changes in sea surface temperature (SST). This variable influences atmospheric circulations and is indicative of surface and subsurface oceanic circulations. We employ data from the geostationary METEOSAT-7 and 8 satellites and from the Special Sensor Microwave/Imager (SSM/I) for the shortwave and long-wave radiative fluxes, and for estimates of SST. For turbulent flux calculations, we use the bulk aerodynamic method with satellite estimates for wind speed and atmospheric humidity and temperature.

• Atmosphere
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• v.33 no.2
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• pp.73-104
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• 2023

Over the past 60 years, Korean numerical weather prediction (NWP) has advanced rapidly with the collaborative effort between the science community and the operational modelling center. With an improved scientific understanding and the growth of information technology infrastructure, Korea is able to provide reliable and seamless weather forecast service, which can predict beyond a 10 days period. The application of NWP has expanded to support decision making in weather-sensitive sectors of society, exploiting both storm-scale high-impact weather forecasts in a very short range, and sub-seasonal climate predictions in an extended range. This article gives an approximate chronological account of the NWP over three periods separated by breakpoints in 1990 and 2005, in terms of dynamical core, physics, data assimilation, operational system, and forecast application. Challenges for future development of NWP are briefly discussed.

• The Bulletin of The Korean Astronomical Society
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• v.31 no.1
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• pp.18.2-18.2
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• 2006

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2009.10a
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• pp.173-174
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• 2009

• The Bulletin of The Korean Astronomical Society
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• v.13
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• pp.10-10
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• 1988