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• W2979687584 abstract "A novel nanocrystal-embedded-insulator (NEI) ferroelectric field-effect transistor (FeFET) is demonstrated to function as a synaptic device for analog neural network (NN) applications. The NEI layer (down to 3.6 nm in thickness) comprises ferroelectric nanocrystals embedded in amorphous Al <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sub> O <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>3</sub> , resulting in reduced operating voltages and depolarization effects as compared to conventional doped-HfO <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sub> films. With fixed-amplitude 100 ns potentiation/depression pulses, an NEI FeFET synapse achieves weight update with small non-linearity ( <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$alpha _{p}= {0.12}$ </tex-math></inline-formula> , <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$alpha _{text {d}}= -{0.09}$ </tex-math></inline-formula> ) and asymmetry factors, advantageous for analog-style NNs with online training. A convolutional NN is designed and emulated for an MNIST dataset, projecting an online training accuracy of 92%." @default.
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• W2979687584 date "2019-12-01" @default.
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• W2979687584 title "Nanocrystal-Embedded-Insulator (NEI) Ferroelectric Field-Effect Transistor Featuring Low Operating Voltages and Improved Synaptic Behavior" @default.
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• W2979687584 doi "https://doi.org/10.1109/led.2019.2947086" @default.
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