Jin Pyo Hong
(Hanyang University, Korea)
Title
Current-future semiconductor memory devices: general DRAM & V-NAND
Professor Hong Jin Pyo is a Distinguished Professor at Hanyang University, affiliated with both the Physics and Nano Semiconductor Engineering Departments. He is also working as a dean of Natural Science at Hanyang University. He completed his education at the University of California, Los Angeles (UCLA), earning his Ph.D. in Physics in 1992 after obtaining his Bachelor's degree in 1987.
Professor Hong Jin Pyo focuses on cutting-edge areas in physics and engineering, such as spintronics, advanced memory systems, semiconductor technology, and new ways to harvest and store energy. His research includes studying how spin-based technologies can improve artificial intelligence devices, like creating materials that act like brain cells. He's also working on making memory storages, such as SOT/STT-MRAM & ReRAM-based AI, novel SOM (selector-only-memory), oxide semiconductor-based capless 2T-0C frame and defect analyses, more efficient and reliable, exploring how different materials can switch on and off to store data. He's also interested in how to generate power from sources like movement or light, especially using 1D/2D hybrid materials that can be woven into fabrics. This could lead to clothes or materials that can charge devices or monitor health. To support his work, Professor Hong uses special tools and techniques to closely examine how materials work at a very small scale, helping to invent new technologies and improve existing ones.
This seminar analyzes the dominance of South Korea in the global DRAM market, attributing it to relentless technological innovation and systematic development of semiconductor experts domestically. With the advent of the Memory-centric computing era and the AI semiconductor era, the demand for high-performance DRAM, such as HBM, is expected to surge. In this context, DRAM technology will continue to play a pivotal role in the computing environment of the future.
DRAM's main advantages include high density and low manufacturing costs, which enable efficient processing of large data volumes. Furthermore, its fast access speed and dynamic data refresh capabilities make it an essential memory solution for high-performance computing systems.
The seminar will provide a detailed explanation of the basic structure of the DRAM, the 1T-1C cell, and its operating principles. We will also introduce real DRAM device images and the process integration workflow. Additionally, we will discuss the potential of next-generation memory technologies, such as Selector-only Memory (SOM), 3D DRAM, capless 2T-OC, and SOT-MRAM, which could replace DRAM. Each technology's fundamental operating principles and structures will be examined in depth.
Prof. Xiaoqin Li
(University of Texas-Austin)
Title
The Versatile World of Excited States in Semiconductor Moiré Superlattices
Prof. Li is a professor in the physics department at the University of Texas-Austin. She received her Ph.D. at the University of Michigan in 2003 and worked as a postdoctoral researcher at JILA, Colorado. Since establishing her research group at the University of Texas in 2007, she has worked in several research areas including low-dimensional semiconductors, most recently in atomically thin van der Waals materials, magnetic materials, and nanophotonics. She has received several awards including the Presidential Early Career Award for Scientists and Engineers in the U. S. and a Sloan Fellowship. She was a Humboldt research fellow at the Technical University of Berlin between 2013-2015. She is a fellow of the American Physics Society and OPTICA.
When two atomically thin van der Waals (vdW) layers are vertically stacked together, the atomic alignment between the layers exhibits periodical variations, leading to a new type of in-plane superlattices known as the moiré superlattices. In moiré superlattices formed by transition metal dichalcogenide (TMD) monolayers, optical properties are dominated by tightly bound excitons that are stable at room temperature and relevant for optoelectronic devices. The fundamental properties of excitons are modified by the moiré potential including their optical selection rules, spin-valley correspondence, mobility, and quantum dynamics. The lectures will provide a basic introduction to excitons, phonons, and correlated states probed via exciton resonances in TMD moiré superlattices with a discussion of open questions and challenges.
Chung Sam Jeon
(nanoPDL, Korea)
Title
Innovation of nanoPDM(nano Process Diagnostics Method) for hyperspace Era of semiconductor device
- Nano PDL, Korea
- Vice-President of Samsung Electronics (2021)
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Kangbong Seo
(SKHU)
Title
The journey to the smart sensor (like the eye, beyond the eye)
Kangbong seo received B.S. and M.S. degree in electronics engineering from Hanyang university, Seoul, Korea, in 1993 and 1995. After then he joined SK Hynix and has about 30 years of experience in the semiconductor industry.
From 1995 ~ 2007, he has researched for semiconductor device, reliability and circuit modeling.
From 2007 ~ 2009, he has developed various logic technology and PDK.
From 2009 ~ 2019, he has developed various CMOS Image sensor product.
And then he has worked with advanced technology of CMOS image sensor as a research fellow.
He is currently a professor at SK Hynix. his current research areas are advanced architecture and new application of CMOS image sensor
The emergence of CMOS Image Sensor (CIS) as a semiconductor enabling the processing of visual information has had a significant impact on the development of the ICT eco system. Initially, significant technological advancements were made to accurately represent objects as they are, leading to becoming an essential part of smartphones and various electronics devices. Through continuous development over time, CIS has partially caught up with the evolutionary capabilities of the human eye. It is now beginning to contribute to enriching human life not only by capturing and storing good images but also by providing various information through light. Furthermore, recently developed deep learning technologies have also begun to be actively adopted and evolved in CIS. In this lecture, we will discuss the requirements of CIS, past technological trends, and future directions of change.
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