Kim, Jeehwan - Massachusetts Institute of Technology - Department of Materials Science and Engineering

个人简介

Education and work experience 2015-Present, Assistant Professor of Mechanical Engineering, MIT 2008-2015, Research Staff Member, Master Inventor, IBM TJ Watson Research Center 2008, Ph.D. Materials Science and Engineering, University of California at Los Angeles 1999-2002, Korea Air Force, military service 1999, M.S. Materials Science and Engineering, Seoul National University, Seoul, Korea 1997, B.S. Materials Science and Engineering, Hongik University, Seoul, Korea Awards Master Inventor of IBM Corporation, 2012 25 Invention Achievement Awards, 2008-2015 15 High Value Patent Awards, 2008-2015

研究领域

Graphene-Based Layer Transfer A graphene-based layer transfer technology offers infinitive growths & transfers of high quality single-crystalline semiconductor films on single-crystalline graphene. We develop a method to perform van der Waals epitaxy of defect-free single-crystalline films on epitaxial graphene in general material system and we study mechanics for repeatable & precise exfoliation of epilayers on graphene. Our focus is to fabricate high performance electronic/photonic/photovoltaics devices with low manufacturing cost based on a graphene-based layer transfer technique. Brain-Inspired Neuromorphic Computing Shortcomings in supercomputer originate in their von Neumann architecture, which involves a CPU, an input/output unit, and a storage (memory) unit. Because communication between these CPU and memory requires data buses, this system inherently cannot accommodate the speed necessary for real-time AI computation. In addition, implementing AI with von Neumann computing would involve training hundreds of thousands of CPUs, GPUs, and memory devices. Brain-inspired neuromorphic computing has recently emerged as a plausible alternative computing method for AI because it enables ultrafast real-time data processing in small footprint. The parallelism property of the ReRAM’s dot-product calculation algorithm enables its fast computing speed. More importantly, ReRAMs’ ability to represent multiple bits in a single cell can enable real-time data processing at low power in a small footprint. Therefore, employing ReRAM is the one of the very promising pathways to realize real-time processing in AI. In ReRAM, imperfection of the switching medium promotes filament formation, but it also leads to uncontrolled filament formation during each switching cycle. Therefore, the device exhibits non-uniform performance. Our group is working on a total new type of ReRAM devices to overcome the material limitations that have been holding back use of ReRAM arrays as an AI computing platform. Our current device uniformity is > 95% with the highest on-off ratio ever reported without utilizing selecting devices. Single-Crystalline Graphene Electronics We fabricate unprecedented wafer-scale single-crystalline graphene and study electron & hole transport in single-crystalline graphene. We also study unique nanoscale mechanics in two-dimensional materials like graphene for single-atom-thickness precision control. Advanced Photovoltaics Over the past few decades, the levelized cost of energy for solar cells has decreased rapidly leading to the global average solar module cost of ~1 $/W. However, despite these advances, grid parity remains a goal for the future. There is still a substantial room for improving the solar cell efficiency, as the performance gap between the best research cell and the Shockley–Queisser limit is still 20-50%. Our group investigate nanotechnology for reducing both this performance gap and the module cost by increasing the efficiency of low-cost solar cells. Our current interests are as following: i) Geometry modification for efficiency enhancement via constructing high aspect-ratio three-dimensional solar cells, ii) Work-function engineering of carbon-based transparent electrode via plasmonic gold nanodots, and iii) Monolithic integration of organic-inorganic hybrids

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Proceedings of the National Academy of Science, Vol. 114, 4082-4086 (2017) Unveiling the carrier transport mechanism in epitaxial graphene for forming wafer‐scale, single‐domain graphene Sang‐Hoon Bae, Xiaodong Zhou, Seyoung Kim, Yun Seog Lee, Samuel Cruz, Yunjo Kim, James B. Hannon, Yang Yang, Devendra K. Sadana, Frances M. Ross, Hongsik Park, and Jeehwan Kim* Advanced Materials, Published online (2017) Selective Nanoscale Mass Transport across Atomically Thin Single Crystalline Graphene Membranes Piran R. Kidambi, Michael S. Boutilier, Luda Wang, Doojon Jang, Jeehwan Kim, and Rohit Karnik Advanced Materials, Vol. 28, 5293–5299 (2016) Extremely Large Gate Modulation in Vertical Graphene/WSe2 Heterojunction Barristor Based on a Novel Transport Mechanism Jaewoo Shim, Hyo Seok Kim, Yoon Su Shim, Dong-Ho Kang, Hyung-Youl Park, Jaehyeong Lee, Jaeho Jeon, Seong Jun Jung, Young Jae Song, Woo-Shik Jung, Jaeho Lee, Seongjun Park, Jeehwan Kim, Sungjoo Lee, Yong-Hoon Kim, and Jin-Hong Park. Advanced Energy Materials, Vol. 6, 1600198 (2016) Atomic layer deposited aluminum oxide for interface passivation of Cu2ZnSn(S,Se)4 thin-film solar cells Yun Seog Lee, Talia Gershon, Teodor K. Todorov, Wei Wang, Mark T. Winkler, Marinus Hopstaken, Oki Gunawan, Jeehwan Kim*.