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As our knowledge of machine learning grows, the current von Neuman computers are gravitating toward neuromorphic architectures. Understanding the mechanisms of neural information processing is crucial for the evolution of today's computing. Compared to von Neumann machines, the brain is characterized by massive parallelism, a huge number of connections, ultra-high density in 3D, low power, adaptive learning, and constant data collection. To develop a more advanced computer, I believe the correct approach is to form a hybrid electronic platform in which both the strength of the CMOS and the novel nanodevices are exploited. Our goal is to investigate the future of computing and electronics in general by exploiting new structures, devices, materials, ideas, and engineering concepts.

Exploratory Nanoelectronics

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Current applications of interest include:

  • Unique structures (3D vertical, HEMT, junction transistor, TFT, Tunneling junction, Schottky junction, NEMS)

  • Novel mechanisms (Ion, defect engineering, quantum confinement, floating gates, barrier conrol, ferroelectric)

  • New materials (III-V, chalcogenide material, transition metal oxides, Nitrides, low-dimensional material)

Related projects:

  • Development of ultra-thin 3D integration process technology (Samsung)

  • Study on integrated multifunctional sensor platform based on autonomous energy

  • Memristor Fault-Aware Neuromorphic System for 3D Memristor array

  • Development of CXL-based PIM (Processor in Memory) semiconductor technology with memory coherency for multiple DRAM modules

  • Developement of radiation hardened electron devices based on functional nanomaterials

Related Publications

  • Jinho Lim, Arman Kadyrov, Dasom Jeon, Yongsu Choi, Junho Bae, and Seunghyun Lee “Contact Engineering of Vertically Grown ReS2 with Schottky Barrier Modulation” ACS Applied Materials & Interfaces IF 9.2 (2021)

  • Sunghwan Lee,et al., and Seunghyun Lee, “Metal oxide resistive memory with a deterministic conduction path”, Journal of Materials Chemistry C, IF 7.4 (2019)

  • Alimkhanuly, Batyrbek,et al.,and Seunghyun Lee “Electromagnetic analysis of vertical resistive memory with a sub-nm thick electrode.” Nanomaterials IF 5.1 (2020)

  • Seunghyun Lee, Alvin Tang, Shaul Aloni, H. -S. Philip Wong, ‘‘Statistical Study on the Schottky Barrier Reduction of Tunneling Contacts to CVD Synthesized MoS2", Nano Letters 16, 276-281 (2016).

  • Seunghyun Lee, Joon Sohn, Zizhen Jiang, Hong-Yu Chen, and H. -S. Philip Wong, ‘‘Metal Oxide Resistive Memory using Graphene Edge Electrode", Nature Communications 6, 8407 (2015).

  • Rebecca Park, Max Shulaker, Gage Hills, Luckshitha Suriyasena Liyanage, Seunghyun Lee, Alvin Tang, Subhasish Mitra, and H-S Philip Wong. ‘‘Hysteresis in Carbon Nanotube Transistors: Measurement and Analysis of Trap Density, Energy Level, and Spatial Distribution." ACS nano 10, no. 4 (2016).

  • Dongkyu Seo, et al. “Total Ionizing Dose Effect on Ring Oscillator Frequency in 28-nm FD-SOI Technology”, IEEE Electron Device Letters IF 4.2 (2019)

  • Seunghyun Lee, Kyunghoon Lee, and Zhaohui Zhong, ‘‘Wafer Scale Homogeneous Bilayer Graphene Films by Chemical Vapor Deposition", Nano Letters 10 (11), 4702-4707, Oct. 8, (2010)

  • Seunghyun Lee, Alvin Tang, James P. McVittie, H. -S. Philip Wong, ‘‘NEM relays using 2-dimensional nanomaterials for low energy contacts", Energy Efficient Electronic Systems, pp. 1,2.

Large-scale Integration of Nanoelectronics on CMOS and other platforms

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Current applications of interest include:

  • Integration of explanatory nanodevices on CMOS

  • BEOL integration on CMOS circuits

  • Wafer-level bonding and its reliabiltiy

  • Merging of technologies and substrates

Related projects:

  • Development of CXL-based PIM (Processor in Memory) semiconductor technology with memory coherency for multiple DRAM modules

  • Novel Highly Reliable ReRAM based PIM Device, Circuit, Architecture Development for Sequential Data Processing and Image Recognition Applications

  • Ultra-small pixel micro LED display manufacturing technology

  • Development of ultra-thin 3D integration process technology (Samsung)

  • Study on integrated multifunctional sensor platform based on autonomous energy

Related Publications

  • Junho Bae, YuSeop Shin,et al.,and Seunghyun Lee “Quantum dot-integrated GaN light-emitting diodes with resolution beyond the retinal limit” Nature Communications IF 14.9 (2022)

  • Batyrbek Alimkhanuly,et al.,and Seunghyun Lee “Graphene-based 3D XNOR-VRRAM with ternary precision for neuromorphic computing” Nature Partner Journal: 2D materials & applications IF 11.1 (2021)

  • Seunghyun Lee, Zhaohui Zhong, ‘‘Nanoelectronic circuits based on two-dimensional atomic layer crystals", Nanoscale, 6(22) 13283-13300. (2014)

  • Seunghyun Lee, Kyunghoon Lee, Chang-Hua Liu, Girish S. Kulkarni, and Zhaohui Zhong, ‘‘Flexible and Transparent All-Graphene Circuits for Quaternary Digital Modulations", Nature Communications, 3, 1018 (2012).

  • Seunghyun Lee, Seow Yuen Yee, Ali Besharatian, Hanseup Kim, and Khalil Najafi, ‘‘Adaptive gas pumping by controlled timing of active microvalves in peristaltic micropumps", in IEEE Solid-State Sensors, Actuators and Microsystems, Denver, Colorado.

  • Li, Ling, Xiangyu Chen, Ching-Hua Wang, Ji Cao, Seunghyun Lee, Alvin Tang, Chiyui Ahn, Susmit Singha Roy, Michael S. Arnold, and H-S. Philip Wong. “Vertical and Lateral Copper Transport through Graphene Layers.” ACS nano 9, no. 8 (2015): 8361-8367.

Neuromorphic Hardware (emphasis on 3D synapse and edge computing)

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Current applications of interest include:

  • Memristor Fault-Aware Neuromorphic System for 3D Memristor array

  • Memristor implementation of binary neural network and XNOR-net

  • Neuromorphic hardware for Near/In memory computing and edge devices

  • Ultralow power artifical neurons in vertical cross-point architecture

Related projects:

  • Memristor Fault-Aware Neuromorphic System for 3D Memristor array

  • Development of CXL-based PIM (Processor in Memory) semiconductor technology with memory coherency for multiple DRAM modules

  • Developing Re-RAM-bsed a near-memory bit-vector computing unit

  • Novel Highly Reliable ReRAM based PIM Device, Circuit, Architecture Development for Sequential Data Processing and Image Recognition Applications

Related Publications

  • Batyrbek Alimkhanuly,et al.,and Seunghyun Lee “Graphene-based 3D XNOR-VRRAM with ternary precision for neuromorphic computing” Nature Partner Journal: 2D materials & applications IF 11.1 (2021)

  • Vo, Quang Hieu,et al.,and Seunghyun Lee “Hardware Platform-Aware Binarized Neural Network Model Optimization.” Applied Sciences (2021)

  • Muhammad Salman Ali,et al., “ERDNN: Error-Resilient Deep Neural Networks With a New Error Correction Layer and Piece-Wise Rectified Linear Unit”, IEEE Access IF 3.74 (2020)

  • Sunghwan Lee,et al., and Seunghyun Lee, “Metal oxide resistive memory with a deterministic conduction path”, Journal of Materials Chemistry C, IF 7.4 (2019)

  • Shem Seo, Jinho Lim, Sunghwan Lee, Batyrbek Alimkhanuly, Arman Kadyrov, Dasom Jeon, Seunghyun Lee, “Graphene-edge electrode on a Cu-based chalcogenide selector for 3D vertical memristor cells”, ACS Applied Materials & Interfaces IF 9.2 (2019)

  • Seunghyun Lee, Joon Sohn, Zizhen Jiang, Hong-Yu Chen, and H. -S. Philip Wong, ‘‘Metal Oxide Resistive Memory using Graphene Edge Electrode", Nature Communications 6, 8407 (2015).

  • Ahn, Chiyui, Scott W. Fong, Yongsung Kim, Seunghyun Lee, Aditya Sood, Christopher M. Neumann, Mehdi Asheghi, Kenneth E. Goodson, Eric Pop, and H-S. Philip Wong. ‘‘Energy-efficient phase-change memory with graphene as a thermal barrier", Nano Letters 15, no. 10 (2015): 6809-6814.

  • Seunghyun Lee, Joon Sohn (co-1st author), Zizhen Jiang, Hong-Yu Chen and H.-S. Philip Wong, ‘‘Atomically Thin Graphene Plane Electrode for 3D RRAM", IEDM, paper 5.3, pp. 116-119, (2014)

  • Yang, Yuchao, Jihang Lee, Seunghyun Lee, CheHung Liu, Zhaohui Zhong, and Wei Lu. ‘‘Oxide Resistive Memory with Functionalized Graphene as Built?in Selector Element", Advanced Materials 26, no. 22 (2014): 3693-3699.

Heat Management for Higher Energy Efficiency and Reliability

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Current applications of interest include:

  • Heat management of systems using anistropic heat transfer materials

  • Thermal analysis of 3D vertical architectures

  • Temperature dependent carrier transfer characteristics

Related projects:

  • Reliability Improvement of GaN devices utilizing the anistropic thermal conductance of 2D materials

  • Ultra-small pixel micro LED display manufacturing technology

  • Development of ultra-thin 3D integration process technology (Samsung)

Related Publications

  • Yuseop shin, Junho Bae,et al., and Seunghyun Lee, “Coupled thermo–electrical analysis of highly scaled GaN micro-LEDs with meshed hybrid conductors”, Semiconductor Science and Technology (2019)

  • Dasom Jeon, Jinho Lim, Junho Bae, Arman Kadirov, Yongsu Choi, and Seunghyun Lee “Suppression of self-heating in nanoscale interfaces using h-BN based anisotropic heat diffuser”, Applied Surface Science IF 6.7 (jcr 2.3%) , (2021)

  • Ahn, Chiyui, Scott W. Fong, Yongsung Kim, Seunghyun Lee, Aditya Sood, Christopher M. Neumann, Mehdi Asheghi, Kenneth E. Goodson, Eric Pop, and H-S. Philip Wong. ‘‘Energy-efficient phase-change memory with graphene as a thermal barrier", Nano Letters 15, no. 10 (2015): 6809-6814.