EE Prof. Kim, SangHyeon’s team, develops display using 3D integration techniques, promising applications on next generation displays

EE Prof. Kim, SangHyeon’s team, develops display using 3D integration techniques, promising applications on next generation high resolution displays

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[ Prof. Kim, SangHyeon, Ju Hyeok Park (P.H.D candidate), Dr. Dae-myeong Geum, Woo Jin Baek (P.H.D candidate), From left]

 

KAIST EE Prof. Kim, SangHyeon’s research team has successfully developed a 1600-PPI MicroLED display by utilizing monolithic 3D integration techniques, as announced.

(*monolithic 3D integration: dubbed the ultimate 3D integration tech, wherein after the lower-layer devices, the upper layer’s thin film is created and stacking proceeds sequentially so as to maximize the upper-lower device alignment)

(* PPI: pixels per inch)

 

KAIST EE Prof. Kim, SangHyeon Kim’s research team members Ju Hyeok Park and Dr. Dae-myeong Geum led the work as co-first authors, collaborating with Woo Jin Baek from the same research lab and Dr. Johnson Shieh from Jasper Display in Taiwan. Their joint work has been presented at the “semiconductor Olympics”, the 2022 IEEE Symposium on VLSI Technology & Circuits. (Paper: Monolithic 3D sequential integration realizing 1600-PPI red micro-LED display on Si CMOS driver IC)

MicroLED devices using inorganic-based III-V compound semiconductors are gaining attention as core candidates for next-generation ultra-high resolution displays that are growing rapidly in demand. MicroLEDs offer advantages over current OLED and LCD displays widely used in modern TVs and mobile devices with features such as high luminance and contrast ratio, and a longer pixel life.

(*III-V compound semiconductors: Semiconductors comprising of compounds of Group III and Group V elements in the periodic table, offering excellent charge transport and light characteristics)

 

A monolithic 3D integration of red light-emitting LEDs on a Si CMOS circuit board was applied to solve the issues present in existing device technology. A demonstration of high-resolution display was made successful through continuous semiconductor processes on the wafer. Through this process, the LED semiconductor display layer was designed to reduce the thickness of the active layer for light emission to 1/3 and greatly reduce the challenges of the etching process required for pixel formation. In addition, to prevent performance degradation of the lower display driving circuit, the research team was able to maintain the performance of the lower Driver IC even after the integration of the upper layer by using ultra-low temperature processes such as wafer bonding that integrates the upper III-V layer below 350 C.

By successfully implementing state-of-the-art resolution of 1600-PPI MicroLED display using a monolithic 3D integration of red LEDs, this result is expected pave way for the next-generation ultra-high resolution displays.

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EE Professor Kim, SangHyeon’s team develop 3D Stackable Quantum Computing Readout Device

Title:  EE Professor Kim, SangHyeon’s Research Team Develops 3D Stackable Quantum Computing Readout Device

KAIST Builds 3D Stackable Quantum Computing Readout Device  Low-power, low-noise, high-speed device integrated in 3D operates at super-low temperatures and promises large-scale applications to quantum computing devices.

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<(From left) EE Prof. Kim, SangHyeon, PhD candidate Jeong, Jae Yong, NanoFab PhD candidate Kim, Jongmin, and KBSI Prof. Park, Seung-Young>

 

KAIST EE Prof. Kim, SangHyeon’s research team has developed a 3D-stacked semiconductor readout device integration technology, as made public on the 16th. The team made this possible by applying the strengths of monolithic 3D integration to overcome large-scale qubit implementation based on existing quantum computing systems. Their work is a first of its kind exhibiting the 3D stackability of quantum computing readout devices after an actively pursued line of research on monolithic 3D stacking of high-speed devices following a 2021 VLSI presentation, a 2021 IEDM presentation, and a 2022 ACS Nano publication.

(*monolithic 3D integration: dubbed the ultimate 3D integration tech, wherein after the lower-layer devices, the upper layer’s thin film is created and stacking proceeds sequentially so as to maximize the upper-lower device alignment)

KAIST EE Prof. Kim, SangHyeon Kim’s research team member Jeong, Jae Yong led the work as first author, collaborating with NanoFab PhD candidate Kim, Jongmin and KBSI Prof. Park, Seung-Young. Their joint work has been presented at the “semiconductor Olympics”, Symposium on VLSI Technology. (Paper: 3D stackable cryogenic InGaAs HEMTs for heterogeneous and monolithic 3D integrated highly scalable quantum computing system)

A qubit is capable of processing twice the amount computation compared with that of a bit. Number of qubits increasing linearly results in exponential speedup of their computation. Thus, developing large-scale quantum computing is of utmost importance. IBM, for instance, presented Eagle containing 127 qubits, and the IBM roadmap outlines development of a 4,000-qubit quantum computer by 2025 and one with 10,000-qubits or more in 10 years.

Designing such large-scale quantum computers with many qubits requires implementing devices for qubit control/readout. The research team has not only proposed and implemented 3D-stacked control/readout devices but also achieved world-best cutoff frequency characteristics at cryogenic settings despite the 3D stacking.

This work has been supported by the National Research Foundation of Korea, the System Semiconductor Development Program funded by Gyeonggi-do, and the Korea Basic Science Institute.

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EE Prof. Kim, Changick and Jeong, Jae-Woong Awarded on KAIST Research Day

 EE Professors Kim, Changick and Jeong, Jae-Woong Awarded on 2022 KAIST Research Day.

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[From left, Prof. Kim, Changick, Prof. Jeong, Jae-Woong]

 

Professor Kim, Changick has been recognized with the Transdisciplinary Research Prize for his contributions to computer vision- and artificial intelligence-based monitoring  technology of anthropocene effects on the planet. Anthropocene is a scientific concept referring to the recent geological epoch distinct from previous ones, marked by unprecedented transformations in the planet’s system from human activities since the Industrial Revolution. Prof. Kim has been conducting research with satellite images, computer modeling, and deep learning tools on monitoring the compromised states of planet Earth, such as climate change and sea level rises. In addition, as part of AI-based digital study of ecology, he has cooperated closely with anthropogeography and ecology experts to detect endangered species in the DMZ; he has developed a deep network capable of counting and classifying endangered species, such as the red-crowned cranes, the white-naped cranes, and the white-fronted geese. This study is meaningful in automating and maintaining the monitoring process of endangered species in the DMZ and Cheorwon.

 

Professor Jeong, Jae-Woong has been awarded the KAIST Scholastic Award for proposing a new direction in the automated treatment of brain diseases and cognitive research by developing for the first time an IoT (Internet of Things) based wireless remote control system for neural circuits in the brain. The proposed direction sets a vision for one of humanity’s most difficult challenges: overcoming brain diseases. Prof. Jeong has also led the field of research in wirelessly rechargeable soft subdermal implantable devices. These works have been published in 2021 in top journals of medical engineering: Nature Biomedical Engineering and Nature Communications. Said studies were led by Prof. Jeong’s team, with international collaborators in Washington University in School of Medicine, attracting over 60 press reports across the world.

 

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Prof. Seunghyup Yoo, wins the Merck Award at the 2021 International Meeting on Information Display (IMID 2021)

EE Prof. Seunghyup Yoo, wins the Merck Award at the 2021 International Meeting on Information Display (IMID 2021)

 

Professor Seunghyup Yoo of our EE Faculty was honored with the Merck Award at the International Meeting on Information Display (IMID) 2021 held at COEX, Seoul from August 25 to 27.

 

The Merck Awards have been given at IMID hosted by the Korean Information Display Society (KIDS) since 2004, the 100th anniversary of Merck’s liquid crystal research. To encourage innovative and excellent research and development in the display field, this award has been given to selected researchers with outstanding achievements in display technology.

 

Professor Seunghyup Yoo has achieved excellent research results with academic depth and industrial impact in the fields of displays and lighting devices based on organic light-emitting diodes (OLEDs) as well as flexible and wearable electronics. In particular, he conducted systematic research to achieve the ultimate efficiency of OLEDs, which includes the result such as bringing the efficiency of OLED to the level of state-of-the-art inorganic LEDs. Recently, he is pioneering a new field in which wearable IT, optical technology, and medical technology are converged to expand the application fields of OLEDs and organic electronic devices to healthcare. He has also been contributing to the international societies such as the Korea Information Display Society (KIDS) and the Optical Society of America (OSA) for advance and spread of display technologies. 

 

Meanwhile, Merck held an online meeting called Merck Science Connect in line with IMID 2021, and “The power of displaying, as an interface” can be viewed at the following link, in which Professor Seunghyup Yoo participated as a panel.

 

(link) https://youtu.be/HYwvUjMu_qo

 

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[2021 Merck Arawd (Prof.Seunghyup Yoo , KAIST) and Merch young scientists winners]

 

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[Prof. Seunghyup Yoo]

EE Prof. Myoungsoo Jung, Shinhyun Choi, Wanyeong Jung are selected as 2021 Samsung’s Future Technology development project

Research team of EE Prof. Myoungsoo Jung, Shinhyun Choi, Wanyeong Jung was selected as Samsung’s Future Technology development of 2021

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Professors of School of Electrical Engineering Prof. Myoungsoo Jung, Shinhyun Choi, Wanyeong Jung ‘s research project was selected as Samsung’s Future Technology Development of 2021. The project covers a wide range of fields including computer architecture, AI frameworks, operating systems, circuits and devices. It is the first ICT convergence creative project with multidisciplinary project that covers device-circuit-systems in the Future Technology Development . 

 

The details of the selected project is as follows:

 

 

Field

Project name

Project Manager

ICT Convergence creative project

Heterogeneous new memory-based hardware and system software framework for accelerating graph neural network based machine learning.

Myoungsoo Jung

 

The research team focuses on speeding up the popular GNN based machine learning model that uses relationship information in graph data. The project tries to solve the fundamental problems of GNNs by providing solutions from the device, circuit, architecture and operating system level.

 

The selection of the project is significant in that it suggests a multidisciplinary cooperation between device, circuit and computer science experts and builds a practical solution to the problem.

 

Samsung Elecgronics has been selecting Future Technology proejcts each year since 2014. Samsung Electronics selects vital technological projects that is necessary for the future of the country from fields of natural science, information communication technology.

 

Congratuations and a great thanks to the professors.

 

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Professor Jae-Woong Jeong’s Research Team Develops Soft Wirelessly Chargeable Brain Transplant Device

 Our department’s professor Jeong’s research team has developed a brain transplant device that can be charged wirelessly. The phone-controlled device can manipulate the brain’s neural circuits by using light without the need for changing the battery after being transplanted. The research was conducted along with Yonsei University Medical School’s professor JungHoon Kim’s research team.

One of the great advantages of this research is that it can be applicable for curing mental illnesses such as Parkinson’s disease and animal experiments that need long-time monitoring.

Our department’s Ph.D candidate Choongyun Kim and Yonsei University’s Ph.D candidate Minjung Koo have been enlisted as co 1st authors in the paper published in Nature Communications last January 22. (Paper title : Soft subdermal implant capable of wireless battery charging and programmable controls for applications in optogenetics

The research team will expand the research for further miniaturization and MRI-based applications. The research was funded by Ministry of Science & ICT, Korea Research Foundation and KAIST.

We congratulate professor Jeong and Ph.D candidate Choongyun Kim for the innovative research.

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Conductive-bridging random-access memories for emerging neuromorphic computing

A research article authored by Jun-Hwe Cha (KAIST EE), Sang Yoon Yang (KAIST EE), Jungyeop Oh (KAIST EE), Shinhyun Choi (KAIST EE), Sangsu Park (SK Hynix), Byung Chul Jang (Samsung Electronics), Wonbae Ahn (KAIST EE) and Sung-Yool Choi (KAIST EE; Corresponding author) was published in Nanoscale (2020.07)

Article title: Conductive-bridging random-access memories for emerging neuromorphic computing

With the increasing utilisation of artificial intelligence, there is a renewed demand for the development of novel neuromorphic computing owing to the drawbacks of the existing computing paradigm based on the von Neumann architecture. Extensive studies have been performed on memristors as their electrical nature is similar to those of biological synapses and neurons. However, most hardware-based artificial neural networks (ANNs) have been developed with oxide-based memristors owing to their high compatibility with mature complementary metal–oxide–semiconductor (CMOS) processes. Considering the advantages of conductive-bridging random-access memories (CBRAMs), such as their high scalability, high on–off current with a wide dynamic range, and low off-current, over oxide-based memristors, extensive studies on CBRAMs are required. In this review, the basics of operation of CBRAMs are examined in detail, from the formation of metal nanoclusters to filament bridging. Additionally, state-of-the-art experimental demonstrations of CBRAM-based artificial synapses and neurons are presented. Finally, CBRAM-based ANNs are discussed, including deep neural networks and spiking neural networks, along with other emerging computing applications. This review is expected to pave the way toward further development of large-scale CBRAM array systems.

 

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Stress-Relief Substrate Helps OLED Stretch Two-Dimensionally​

Highly functional and free-form displays are critical components to complete the technological prowess of wearable electronics, robotics, and human-machine interfaces.

A KAIST team created stretchable OLEDs (Organic Light-Emitting Diodes) that are compliant and maintain their performance under high-strain deformation. Their stress-relief substrates have a unique structure and utilize pillar arrays to reduce the stress on the active areas of devices when strain is applied.

Traditional intrinsically stretchable OLEDs have commercial limitations due to their low efficiency in the electrical conductivity of the electrodes. In addition, previous geometrically stretchable OLEDs laminated to the elastic substrates with thin film devices lead to different pixel emissions of the devices from different peak sizes of the buckles.

To solve these problems, a research team led by Professor Kyung Cheol Choi designed a stretchable substrate system with surface relief island structures that relieve the stress at the locations of bridges in the devices. Their stretchable OLED devices contained an elastic substrate structure comprising bonded elastic pillars and bridges. A patterned upper substrate with bridges makes the rigid substrate stretchable, while the pillars decentralize the stress on the device.

Although various applications using micropillar arrays have been reported, it has not yet been reported how elastic pillar arrays can affect substrates by relieving the stress applied to those substrates upon stretching. Compared to results using similar layouts with conventional free-standing, flat substrates or island structures, their results with elastic pillar arrays show relatively low stress levels at both the bridges and plates when stretching the devices. They achieved stretchable RGB (red, green, blue) OLEDs and had no difficulties with material selection as practical processes were conducted with stress-relief substrates.

Their stretchable OLEDs were mechanically stable and have two-dimensional stretchability, which is superior to only one-direction stretchable electronics, opening the way for practical applications like wearable electronics and health monitoring systems.

Professor Choi said, “Our substrate design will impart flexibility into electronics technology development including semiconductor and circuit technologies. We look forward this new stretchable OLED lowering the barrier for entering the stretchable display market.”

This research was published in Nano Letters titled Two-Dimensionally Stretchable Organic Light-Emitting Diode with Elastic Pillar Arrays for Stress Relief. (https://dx.doi.org/10.1021/acs.nanolett.9b03657).  This work was supported by the Engineering Research Center of Excellence Program supported by the National Research Foundation of Korea.

 

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Figure. Photographs of the patterned rigid part of the substrate on the finger joint indicating 2D dimensional stretchability and images of stretchable OLEDs on a finger joint emitting green light

Professor Shin-Hyun Choi’s Research Laboratory [Memristor for AI]

Link: https://www.shinhyunlab.kaist.ac.kr/

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Memristor-based Network Simulation

using State-of-Art Algorithms

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Memristor-based Network Simulation

using State-of-Art Algorithms

Memristor for AI

Memristor, also called RRAMs, have attracted tremendous attention as a candidate for machine learning, neuromorphic computing and artificial intelligence. Memristor has two terminals structure, which allows the device to be fabricated into large crossbar array. Moreover, a single memristor has an analog switching behavior unlike conventional devices such as CMOS based processor. Due to these characteristics, effective matrix operation is possible through memristor array, which makes the memristor adequate as a device for deep learning process and artificial intelligence. The inherent memory effect of memristor removes bottlenecks between memory and processor unit, existing on conventional AI processor. Other properties such as high scalability, low power consumption and fast switching speed are the remarkable strength of memristor for AI and deep learning applications.

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Research area of Emerging Nano Technology and Integrated Systems Lab (ENTIS)

Our lab focuses are 1) to overcome the limitations of conventional memristor and 2) to develop memristor-based platform for various deep neural network(DNN), spiking neural network(SNN) and other applications.

1. Memristor Devices Development

Conventional memristors suffer from unavoidable spatial-temporal variation due to uncontrollable, stochastic filament formation. Our Lab is now developing a new strategy to achieve uniform switching through CMOS compatible materials/fabrication steps as well as linearity, retention and endurance.

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2. Artificial Neural Network Simulation using memristor

To optimize Memristor devices for Artificial Neural Network (ANN) algorithm such as Deep Neural Network (DNN) and Spiking Neural Network (SNN), our Lab is simulating memristor devices arrays using software reflecting hardware conditions.

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3. Artificial Neural Network System Design and Integration

Our lab designs artificial neural network system on customized PCB board and integrated chip based on memristor device utilized as an AI hardware. The goal is developing large-scale neural network array for AI hardware processing big data. Another aim is integration of the system, broadening the application of memristor-based ANN system.

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Professor Sangh-Hyeon Kim, Monolithic integration of GaAs//InGaAs photodetectors for multicolor detection

 Professor Sang-Hyeon Kim’s paper on the multi-color photodetector which can be used as a compact photonic sensor for AI chip was presented in VLSI symposia 2019*.

*VLSI symposia is the one of flagship conference in VLSI society.

Title: Monolithic integration of GaAs//InGaAs photodetectors for multicolor detection

Multicolor photodetectors (PDs) by using bulk p-i-n based visible GaAs and near-infrared (IR) InGaAs PD was successfully fabricated via monolithic integration by wafer bonding and epitaxial lift-off. It showed high-performance individual operation comparable to that of bulk PDs with tight vertical alignment on a single substrate for future high-resolution multicolor PDs. At the same time, it covered a broad wavelength range from visible to IR.

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Figure 1. Multi-Color Photodetector