• Journal of the Korean Vacuum Society
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• v.22 no.6
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• pp.285-290
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• 2013

Epitaxial graphene on metal substrates provides excellent platforms to study its atomic and electronic structures, and can be grown either by surface segregation of carbon or by chemical vapor deposition. The growth behaviors of the two methods, however, have not been directly compared each other. Here, we studied domain structures of graphene grown by three different methods, surface segregation, post-annealing with adsorbed ethylene, and high-temperature dose of ethylene, using scanning tunneling microscopy. The first two methods resulted in graphene regions with areas of $100nm^2$, whereas the third method showed large area graphene (> $10^4nm^2$) with regular hexagonal Moire patterns, implying that high-temperature dose of ethylene is preferable for further studies on graphene such as additional growth of organic molecules.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.4
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• pp.265-275
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• 2010

In this work, reliable methodology for device design is presented. Based on this method, the underlap length has been optimized for minimizing the gateinduced drain leakage (GIDL) in a 22-nm node 4-terminal (4-T) silicon-on-insulator (SOI) fin-shaped field effect transistor (FinFET) by TCAD simulation. In order to examine the effects of underlap length on GIDL more realistically, doping profile of the source and drain (S/D) junctions, carrier lifetimes, and the parameters for a band-to-band tunneling (BTBT) model have been experimentally extracted from the devices of 90-nm channel length as well as pnjunction test element groups (TEGs). It was confirmed that the underlap length should be near 15 nm to suppress GIDL effectively for reliable low standby power (LSTP) operation.

• Bulletin of the Korean Chemical Society
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• v.32 no.4
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• pp.1253-1257
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• 2011

The surface structures, adsorption conditions, and thermal desorption behaviors of cyclopentanethiol (CPT) self-assembled monolayers (SAMs) on Au(111) were investigated by scanning tunneling microscopy (STM), X-ray photoelectron spectroscopy (XPS), and thermal desorption spectroscopy (TDS). STM imaging revealed that although the adsorption of CPT on Au(111) at room temperature generates disordered SAMs, CPT molecules at $50^{\circ}C$ formed well-ordered SAMs with a $(2{\surd}3{\times}{\surd}5)R41^{\circ}$ packing structure. XPS measurements showed that CPT SAMs at room temperature were formed via chemical reactions between the sulfur atoms and gold surfaces. TDS measurements showed two dominant TD peaks for the decomposed fragments ($C_5H_9^+$, m/e = 69) generated via C-S bond cleavage and the parent molecular species ($C_5H_9SH^+$, m/e = 102) derived from a recombination of the chemisorbed thiolates and hydrogen atoms near 440 K. Interestingly, dimerization of sulfur atoms in n-alkanethiol SAMs usually occurs during thermal desorption and the same reaction did not happen for CPT SAMs, which may be due to the steric hindrance of cyclic rings of the CPT molecules. In this study, we demonstrated that the alicyclic ring of organic thiols strongly affected the surface structure and thermal desorption behavior of SAMs, thus providing a good method for controlling chemical and physical properties of organic thiol SAMs.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.6
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• pp.557-568
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• 2016

Squeezing is a phenomenon that may occur in deep tunneling and could bring about a large plastic deformation, tunnel closure and collapse of tunnel supports. Therefore, quantitative estimations of deformation and stress from squeezing and its possibility are necessary for establishment of a rational tunneling method. This study carried out three dimensional numerical analyses using a strain softening model in order to simulate the behaviour of squeezing and to estimate deformation and yield area around tunnels quantitatively. Numerical analyses were performed for 42 cases of various stress and strength conditions. As a result, the maximum tangential stress and strength of rock mass ratio could estimate plastic deformation and yield depth around tunnels and equations of relations between them were proposed.

• Journal of the Korean Applied Science and Technology
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• v.37 no.4
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• pp.1034-1040
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• 2020

The mechanical properties of NATM resin of synthetic polyurethane-epoxy resin for stainless steel were measured by SEM, FT-IR, tensile properties, and specific mass loss by EIS analysis, etc. As interest in eco-friendly medium coatings increased, the Heavy duty coatings were synthesized for various metals such as stainless steel composed of Polyol, MDI, water bored Epoxy resin, filling agent, silicon surfactant, catalyst etc. The coatings of synthetic NATM resin were increased tensile strength due to various temperature change, and the low-Specific Mass Loss was measured in a highly electrolytic solution. In conclusion, the NATM coatings composed of polyurethane and waterbored Epoxy, polyurea resin were synthetic microstructure with cross linkage can be good material for coating of anticorrosion of metal substrates such as stainless steel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9A
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• pp.728-735
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• 2003

It is a mainly issue that provide mobility smoothly in Mobile IP networks. The IP mobility support being standardized in the IETF utilized tunneling of IP packets from a home agent to foreign agent and utilized reverse tunneling of IP packets from foreign agent to home agent. In this paper, We propose that solve the triangular routing problem in IP mobility and that lessen the messages about IETF routing optimization. Through the Mobile Routing Table on the edge router, agent process the message instead of a end node when handoff occur and that lessen the routing path length by sending directly from FA to to Correspond Node's router. This action lessen the message occurrence frequency and the packet drop. We compare the standard IP, Routing Optimization of Mobile IP, Wu's method and the proposed algorithm. Finally, the simulation results are presented.

• Proceedings of the Korean Vacuum Society Conference
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• 1999.07a
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• pp.120-120
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• 1999

III-nitride계 물질들은 blue와 UV 영역의 LED, LD와 같은 광소자뿐만 아니라 HBT, FET와 같은 전자소자로도 널리 응용되고 있다. 이와 같은 물질을 이용한 소자를 제작할 수 있는 낮은 저항의 ohmic contact은 필수적이다. Al이나 Ti와 같은 물질을 기초로 한 n-GaN의 경우는 이미 많은 연구결과가 발표되어 전기적 광학적 소자를 동작하는데 충분히 낮은 ohmic contact저항( )을 었다. 그러나 p-GaN의 ohmic contact은 아직까지 많은 문제점을 내포하고 있다. 그 중의 하나는 높은 doping 농도( )의 p-GaN 박막을 성장하기가 어렵다는 것이며, 또 하나는 낮은 접촉 비저항을 얻기 위해선 7.5eV이상의 큰 재가 function을 지닌 금속을 선택해야 한다. 그러나 5.5eV 이상의 재가 function을 갖는 금속은 존재하지 않는다. 위와 같은 문제점들은 p-GaN의 접촉 비저항이 이상의 높은 값을 갖게 만들고 있으며, 이에 대한 해경방안으로는 고온의 열처리를 통하여 p-GaN와 금속 사이에서 화학적 반응을 일으킴으로써 표면 근처에서 캐리어농도를 증가시키고, 캐리어 수송의 형태가 tunneling 형태로 일어날 수 있도록 하는 tunneling current mechanism을 이용하는 것이다. 이로 인해 결국 낮은 접촉 비저항을 얻을 수 있게되며, 일반적으로 p-GaN에서는 Nidl 좋은 물질로 알려져 있다. 그러나 Ni은 50$0^{\circ}C$이상의 열처리에서 쉽게 산화되는 특성 때문에 높은 캐리어를 얻는데 어려운 문제점이 있다. 이에 본 연구에서는 MBE로 성장된 p-GaN박막을 Mg의 activation을 더욱 증가시키기 위해 N2 분위기에서 15분간 90$0^{\circ}C$에서 annealing을 하였으며, ohmic 접촉을 위한 금속으로 높은 재가 function과 좋은 adhesion 그리고 낮은 자체저항을 가지고 있는 Ni/Au를 ohmic metal로 하여 contact한 후에 90$0^{\circ}C$에서 10초간 rapid thermal annealing (RTA)처리를 했다. 성장된 박막의 광학적 성질은 PL로써 측정하였으며, photoconductivity 실험을 통해 impurity의 life time을 분석하였고, persistent photoconductivity를 통해 dark current를 측정하였다. 또한 contact resistance를 계산하기 위해 circular-TLM method을 이용하여 I-V 특성을 조사하였다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.120-131
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• 2016

In this paper, a 512b MTP memory IP is designed by using MTP memory cells which are written by the FN (Fowler-Nordheim) tunneling method with only MV (medium voltage) devices of 5V which uses the back-gate bias, that is VNN (negative voltage). The used MTP cell consists of a CG (control gate) capacitor, a TG (tunnel gate) transistor, and a select transistor. To reduce the size of the MTP memory cell, just two PWs (P-wells) are used: one for the TG and the select transistors; and the other for the CG capacitor. In addition, just one DNW (deep N-well) is used for the entire 512b memory cell array. VPP and VNN generators supplying pumping voltages of ${\pm}8V$ which are insensitive to PVT variations since VPP and VNN level detectors are designed by a regulated voltage, V1V (=1V), provided by a BGR voltage generator.

• Journal of the Korean Magnetics Society
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• v.18 no.4
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• pp.154-158
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• 2008

Magnetite($Fe_3O_4$) is currently one of key materials for applications in magnetic storage and many bioinspired applications because bulk $Fe_3O_4$ has a high Curie temperature($Tc={\sim}850K$) and nearly full spin polarization at room temperature(RT). In this work, $Fe_3O_4$ nanoparticles with different sizes of 12 to 15 nm were prepared in a well-controlled manner by a nonhydrolytic synthetic method. Here, we report the significant intergrain magneto-resistance(MR) of ${\sim}2%$ at RT in $Fe_3O_4$ nanoparticle pellets. The tunneling conductance was also investigated based on the Brinkman model, as well. Our results show clearly that the surface or interfacial property of the particles plays a crucial role in the MR effect.

• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.