Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Qingzhou Wan"'
Autor:
Qingzhou Wan, Marco Rasetto, Mohammad T. Sharbati, John R. Erickson, Sridhar Reddy Velagala, Matthew T. Reilly, Yiyang Li, Ryad Benosman, Feng Xiong
Publikováno v:
Advanced Intelligent Systems, Vol 3, Iss 9, Pp n/a-n/a (2021)
Neuromorphic computing has the great potential to enable faster and more energy‐efficient computing by overcoming the von Neumann bottleneck. However, most emerging nonvolatile memory (NVM)‐based artificial synapses suffer from insufficient preci
Externí odkaz:
https://doaj.org/article/3a8cbac84ba24e5693c5e042951e93d8
Autor:
Qingzhou Wan, Peng Zhang, Qiming Shao, Mohammad T. Sharbati, John R. Erickson, Kang L. Wang, Feng Xiong
Publikováno v:
APL Materials, Vol 7, Iss 10, Pp 101107-101107-8 (2019)
Neuromorphic computing has recently emerged as a promising paradigm to overcome the von-Neumann bottleneck and enable orders of magnitude improvement in bandwidth and energy efficiency. However, existing complementary metal-oxide-semiconductor (CMOS)
Externí odkaz:
https://doaj.org/article/519c4a18ef8548e9a9c19651a478fb89
Autor:
Qingzhou Wan, Qian Chen, Mark A Freithaler, Sridhar Reddy Velagala, Yihan Liu, Albert C. To, Aman Mahajan, Ramakrishna Mukkamala, Feng Xiong
Publikováno v:
Advanced Healthcare Materials.
Publikováno v:
Optics express. 30(8)
Phase change chalcogenides such as Ge2Sb2Te5 (GST) have recently enabled advanced optical devices for applications such as in-memory computing, reflective displays, tunable metasurfaces, and reconfigurable photonics. However, designing phase change o
Autor:
Ziyan Yang, Qingzhou Wang, Huixin Yu, Qing Xu, Yuanyue Li, Minghui Cao, Rajendra Dhakal, Yang Li, Zhao Yao
Publikováno v:
Advanced Science, Vol 11, Iss 25, Pp n/a-n/a (2024)
Abstract Self‐powered pressure detection using smart wearable devices is the subject of intense research attention, which is intended to address the critical need for prolonged and uninterrupted operations. Current piezoelectric and triboelectric s
Externí odkaz:
https://doaj.org/article/03e75b94487c4b5bb3e42507c2b480a4
Autor:
Sridhar Reddy Velagala, Yiyang Li, Qingzhou Wan, Feng Xiong, Ryad Benosman, Mohammad Taghi Sharbati, Marco Rasetto, John R. Erickson, Matthew T. Reilly
Publikováno v:
Advanced Intelligent Systems, Vol 3, Iss 9, Pp n/a-n/a (2021)
Neuromorphic computing has the great potential to enable faster and more energy‐efficient computing by overcoming the von Neumann bottleneck. However, most emerging nonvolatile memory (NVM)‐based artificial synapses suffer from insufficient preci
Autor:
Qingzhou Wan, Kang L. Wang, Mohammad Taghi Sharbati, Peng Zhang, John R. Erickson, Feng Xiong, Qiming Shao
Publikováno v:
DRC
Neuromorphic computing has emerged as a new computing paradigm to tackle the von Neumann bottleneck and enable a more energy-efficient processing of today's large-scale datasets, especially for data-intensive applications such as image and pattern re
Autor:
Mostafa Bedewy, Joshua Schlea, Feng Xiong, Qingzhou Wan, Mohammad Taghi Sharbati, Golnaz Najaf Tomaraei, Se Youn Cho
Publikováno v:
DRC
Regenerated silk, a fibrous protein-based biopolymer, has attracted much research attention over the past decades due to its excellent mechanical properties and biological properties. Recently, silk fibroin has also been considered as potential candi
Autor:
Shuheng Dong, Dedong Guo, Qingzhou Wang, Huixin Yu, Qing Xu, Ho-Kun Sung, Zhao Yao, Yuanyue Li, Yang Li
Publikováno v:
Materials & Design, Vol 235, Iss , Pp 112439- (2023)
Flexible pressure sensors have found widespread application in medical diagnosis and human–computer interaction. These practical applications often require large-area pressure sensing arrays (PSAs) to explore spatial pressure distributions. However
Externí odkaz:
https://doaj.org/article/b205b8a4a8be40b49739a1341d23e249
Autor:
Feng Xiong, Qiming Shao, Mohammad Taghi Sharbati, Peng Zhang, John R. Erickson, Qingzhou Wan, Kang L. Wang
Publikováno v:
APL Materials, Vol 7, Iss 10, Pp 101107-101107-8 (2019)
Neuromorphic computing has recently emerged as a promising paradigm to overcome the von-Neumann bottleneck and enable orders of magnitude improvement in bandwidth and energy efficiency. However, existing complementary metal-oxide-semiconductor (CMOS)