• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.35-41
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• 2017

With the advances in Internet over Things, the demand in diverse electronic devices such as mobile phones and sensors has been rapidly increasing and boosting up the researches on those products. Semiconductor materials, devices, and fabrication processes are becoming more diverse and complicated, which accompanies finding parameters for an optimal fabrication process. In order to find the parameters, a process simulation before fabrication or a real-time process control system during fabrication can be used, but they lack incorporating the feedback from post-fabrication data and compatibility with older equipment. In this research, we have developed an artificial intelligence based simulator, which finds parameters for an optimal process and controls process equipment. In order to apply the control concept to all the equipment in a fabrication sequence, we have developed a prototype for a manipulator which can be installed over an existing buttons and knobs in the equipment and controls the equipment communicating with the AI over the Internet. The AI is based on the deep learning to find process parameters that will produce a device having target electrical characteristics. The proposed simulator can control existing equipment via the Internet to fabricate devices with desired performance and, therefore, it will help engineers to develop new devices efficiently and effectively.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.16-22
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• 2024

With advances of artificial intelligence (AI) technology, the demand is increasing for high-end semiconductors in various places such as data centers. In order to improve the performance of semiconductors, reducing the pitch of patterns and increasing density of I/Os are required. For this issue, 2.5dimension(D) packaging is gaining attention as a promising solution. The core technologies used in 2.5D packaging include microbump, interposer, and bridge die. These technologies enable the implementation of a larger number of I/Os than conventional methods, enabling a large amount of information to be transmitted and received simultaneously. This paper proposes the Molded Bridge die on Substrate (MBoS) process technology, which combines molding and Redistribution Layer (RDL) processes. The proposed MBoS technology is expected to contribute to the popularization of next-generation packaging technology due to its easy adaption and wide application areas.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2002.11a
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• pp.81-84
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• 2002

The effects of the isoelectronic AI-doping of GaN grown by metal organic chemical vapor deposition were investigated for the first time using scanning electron microscopy (SEM), Hall measurements, photoluminescence (PL), and time-resolved PL. When a certain amount of Al was incorporated into the GaN films, the room temperature photoluminescence intensity of the films was approximately two orders larger than that of the undoped GaN. More importantly, the electron mobility significantly increased from 130 for the undoped sample to $500\textrm{cm}^2/Vs$ for the sample grown at a TMAl flow rate of $10{\mu}mol/min$, while the unintentional background concentration only increased slightly relative to the TMAl flow. The incorporation of Al as an isoelectronic dopant into GaN was easy during MOCVD growth and significantly improved the optical and electrical properties of the film. This was believed to result from a reduction in the dislocation-related non-radiative recombination centers or certain other defects due to the isoelectronic Al-doping.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2005.09a
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• pp.142-146
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• 2005

패턴화된 ITO (indium tin oxide)/Glass 기판 위에 정공수송층인 PEDOT:PSS [poly(3,4-othylenedioxythiophene):poly(styrene sulfolnate)]와 발광층인 MEH-PPV [poly(2-methoxy-5-(2-ethyhexoxy)-1,4phenylenvinylene)]를 사용하여 ITO/PEDOT:PSS/MEH-PPV/AI 구조를 갖는 고분자 유기 발광다이오드 (polymer light emitting diode: PLED)를 제작하였다. PLED 제작시 MEH-PPV 의 농도를 ($0.1\;wt\%\;{\~}\;0.9\;wt\%$) 변수로 하여 박막의 표면 거칠기와 박막 층의 마찰재수(friction coefficient) 측정을 통하여 농도에 따른 특성 변화를 조사하였다. MEH-PP 의 농도를 $0.1\;wt\%$ 에서 $0.9\;wt\%$ 로 증가함에 따라 발광 층의 RMS (root mean square)같은 1.72 nm 에서 1.00 nm 로 감소하여 거칠기가 개선되는 경향을 보여 주었다. 그러나 박막간의 마찰계수는 0.048 에서 0.035 로 감소하여 박막간의 접합상태가 나빠지는 현상을 나타내었다. 소자의 전기, 광학적 특성의 경우 MEH-PPV 농도가 $0.5\;{\~}\;0.9\;wt\%$ 범위에서 약 0.35 mA (at 9V)의 전류밀도를 나타내었으며, 최대 휘도는 $0.5\;wt\%$ 농도에서 $409\;cd/m^2$의 값을 나타내었다.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.121-125
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• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.6-9
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• 2021

The 3D industry is drawing attention for its applications in various markets, including architecture, media, VR/AR, metaverse, imperial broadcast, and etc.. The current feature of the architecture we are introducing is to make 3D models more easily created and modified than conventional ones. Existing methods for generating 3D models mainly obtain values using specialized equipment such as RGB-D cameras and Lidar cameras, through which 3D models are constructed and used. This requires the purchase of equipment and allows the generated 3D model to be verified by the computer. However, our framework allows users to collect data in an easier and cheaper manner using cell phone cameras instead of specialized equipment, and uses 2D data to proceed with 3D modeling on the server and output it to cell phone application screens. This gives users a more accessible environment. In addition, in the 3D modeling process, object classification is attempted through deep learning without user intervention, and mesh and texture suitable for the object can be applied to obtain a lively 3D model. It also allows users to modify mesh and texture through requests, allowing them to obtain sophisticated 3D models.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.104-112
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• 2023

Agriculture plays an industrial and economic role, as well as an environmental and ecological conservation role, group harmony and the inheritance of traditional culture. However, no matter how advanced the industry is, the basic food necessary for human life can only be produced through the photosynthesis of plants with natural resources such as the sun, water, and air. The Food and Agriculture Organization of the United Nations (FAO) predicts that the world's population will increase by another 2 billion people by 2050, and it faces a myriad of complex and diverse factors to consider, including climate change, food security concerns, and global ecosystems and political factors. In particular, in order to solve problems such as increasing productivity and production of agricultural products, improving quality, and saving energy, it is difficult to solve them with traditional farming methods. Recently, with the wind of the 4th industrial revolution, ICT convergence technology and artificial intelligence have been rapidly developing in many fields, but it is also true that the application of new technologies is somewhat delayed due to the unique characteristics of agriculture. However, in recent years, as ICT and artificial intelligence utilization technologies have been developed and applied by many researchers, a revolution is also taking place in agriculture. This paper summarizes the current state of research so far in four categories of agriculture, namely crop cultivation environment management, soil management, pest management, and irrigation management, and smart farm research data that has recently been actively developed around the world.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.53-58
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• 2023

The storage capacity of 3D-NAND flash memory has been enhanced by the multi-layer dielectrics. The deposition process has become more challenging due to the tight process margin and the demand for accurate process control. To reduce product costs and ensure successful processes, process diagnosis techniques incorporating artificial intelligence (AI) have been adopted in semiconductor manufacturing. Recently there is a growing interest in process diagnosis, and numerous studies have been conducted in this field. For higher model accuracy, various process and sensor data are required, such as optical emission spectroscopy (OES), quadrupole mass spectrometer (QMS), and equipment control state. Among them, OES is usually used for plasma diagnostic. However, OES data can be distorted by viewport contamination, leading to misunderstandings in plasma diagnosis. This issue is particularly emphasized in multi-dielectric deposition processes, such as oxide and nitride (ON) stack. Thus, it is crucial to understand the potential misunderstandings related to OES data distortion due to viewport contamination. This paper explores the potential for misunderstanding OES data due to data distortion in the ON stack process. It suggests the possibility of excessively evaluating process drift through comparisons with a QMS. This understanding can be utilized to develop diagnostic models and identify the effects of viewport contamination in ON stack processes.

• Korean Journal of Materials Research
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• v.7 no.9
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• pp.811-823
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• 1997

차세대 반도체 배선분야에서, Cu박막은 현재의 AI을 대체할 물질로서 대두되고 있으며 CVD에 의한 선택적 증착은 Cu의 patterning과 관련하여 상당한 관심을 일으키고 있다. 본 연구에서는 (hfac)Cu(VTMS)의 유기원료를 사용하여, CVD공정변수, 운반기체, 표면 처리 공정에 따른 SiO$_{2}$, TiN, AI기판에 대한 선택성을조사하였다. 선택성은 저온(15$0^{\circ}C$), 저합(0.3Torr)에서 향상될 수 있었으며, 특히, HMDS in-situ-predosing공정에 의해 더욱 향상될 수 있었다. 모든 경우에 대해, H$_{2}$운반기체가 Ar 보다 짧은 incubation time과 높은 증착 속도가 얻어졌으며, Cu입자들의 크기가 작고 연결상태가 보다 양호하였다. 이는 H$_{2}$경우에 기판표면에 원료가 흡착되어 핵을 형성시키는 위치 (-OH)가 보다 많이 제공되기 때문으로 여겨진다. 이러한 미세구조의 차이는 H$_{2}$경우에 보다 낮은 비저항을 얻게 했다. HMDS in-situ predosing공정에 의한 Cu박막내 불순물 차이는 없었으며 뚜렷한 비저항의 차이도 나타나지 않았다.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.1
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• pp.30-41
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• 2023

With the aggressive down-scaling of advanced integrated circuits (ICs), electronic packages have become the bottleneck of both reliability and performance of whole electronic systems. In order to resolve the reliability issues, Institute of Electrical and Electronics Engineers (IEEE) laid down a roadmap on fault detection and diagnosis (FDD), thrusting the digital twin: a combination of reliability physics and artificial intelligence (AI). In this paper, we especially review research works regarding the signal-based FDD approaches on the electronic packages. We also discuss the research trend of FDD utilizing AI techniques.