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Yuriy V. Pershin
Researcher at University of South Carolina
Publications - 192
Citations - 13330
Yuriy V. Pershin is an academic researcher from University of South Carolina. The author has contributed to research in topics: Memristor & Spin polarization. The author has an hindex of 41, co-authored 182 publications receiving 11997 citations. Previous affiliations of Yuriy V. Pershin include Russian Academy of Sciences & Clarkson University.
Papers
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Journal ArticleDOI
The Potential and Challenges of Nanopore Sequencing
Daniel Branton,David W. Deamer,Andre Marziali,Hagan Bayley,Steven A. Benner,Thomas Z. Butler,Massimiliano Di Ventra,Slaven Garaj,Andrew Hibbs,Xiaohua Huang,Stevan B Jovanovich,Predrag S Krstic,Stuart Lindsay,Xinsheng Sean Ling,Carlos H. Mastrangelo,Amit Meller,John S. Oliver,Yuriy V. Pershin,J. Michael Ramsey,Robert Riehn,Gautam V. Soni,Vincent Tabard-Cossa,Meni Wanunu,Matthew Wiggin,Jeffery A. Schloss +24 more
TL;DR: A nanopore-based device provides single-molecule detection and analytical capabilities that are achieved by electrophoretically driving molecules in solution through a nano-scale pore, a unique analytical capability that makes inexpensive, rapid DNA sequencing a possibility.
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Circuit Elements With Memory: Memristors, Memcapacitors, and Meminductors
TL;DR: It is argued that capacitive and inductive elements, namely, capacitors and inductors whose properties depend on the state and history of the system, are common at the nanoscale, where the dynamical properties of electrons and ions are likely to depend upon the history ofThe system, at least within certain time scales.
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Experimental demonstration of associative memory with memristive neural networks
TL;DR: This work has demonstrated experimentally the formation of associative memory in a simple neural network consisting of three electronic neurons connected by two memristor-emulator synapses and opens up new possibilities in the understanding of neural processes using memory devices.
Circuit Elements With Memory: Memristors, Memcapacitors, and Meminductors Nanoscale devices, that store information without need for a power source, can be used for non-volatile memory, and promise to allow simulation of learning, adaptation and spontaneous behavior.
TL;DR: In this paper, the authors extend the notion of memristive systems to capacitive and inductive elements, namely, capacitors and in- ductors whose properties depend on the state and history of the system.
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Memory effects in complex materials and nanoscale systems
TL;DR: The memory properties of various materials and systems which appear most strikingly in their non-trivial, time-dependent resistive, capacitative and inductive characteristics are described within the framework of memristors, memcapacitors and meminductors.