Optimization Method for Conductance Modulation in Ferroelectric Transistor for Neuromorphic Computing (Adv. Electron. Mater. 5/2024)

Ferroelectric Transistors for Neuromorphic Computing This cover image depicts a ferroelectric transistor, illustrating how the conductive path within the channel layer mirrors the ferroelectric domain structure above. Voltage‐induced polarization switching induces conductive clusters in the channel...

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Published inAdvanced electronic materials Vol. 10; no. 5
Main Authors Kim, Cheol Jun, Lee, Jae Yeob, Ku, Minkyung, Kim, Tae Hoon, Noh, Taehee, Lee, Seung Won, Ahn, Ji‐Hoon, Kang, Bo Soo
Format Journal Article
LanguageEnglish
Published 01.05.2024
Online AccessGet full text
ISSN2199-160X
2199-160X
DOI10.1002/aelm.202470019

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Abstract Ferroelectric Transistors for Neuromorphic Computing This cover image depicts a ferroelectric transistor, illustrating how the conductive path within the channel layer mirrors the ferroelectric domain structure above. Voltage‐induced polarization switching induces conductive clusters in the channel layer, providing multiple conductance levels used as weight values. The study by Bo Soo Kang and co‐workers (article number 2300698) highlights the application of Landau–Ginzburg–Devonshire simulations for optimizing conductance modulation in these transistors, thereby advancing efficiency in neuromorphic computing.
AbstractList Ferroelectric Transistors for Neuromorphic Computing This cover image depicts a ferroelectric transistor, illustrating how the conductive path within the channel layer mirrors the ferroelectric domain structure above. Voltage‐induced polarization switching induces conductive clusters in the channel layer, providing multiple conductance levels used as weight values. The study by Bo Soo Kang and co‐workers (article number 2300698) highlights the application of Landau–Ginzburg–Devonshire simulations for optimizing conductance modulation in these transistors, thereby advancing efficiency in neuromorphic computing.
Author Kim, Cheol Jun
Kang, Bo Soo
Ku, Minkyung
Ahn, Ji‐Hoon
Noh, Taehee
Kim, Tae Hoon
Lee, Jae Yeob
Lee, Seung Won
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