2019
DOI: 10.1021/acsami.9b16231
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Junctionless Poly-GeSn Ferroelectric Thin-Film Transistors with Improved Reliability by Interface Engineering for Neuromorphic Computing

Abstract: Ferroelectric HfZrO x (Fe-HZO) with a larger remnant polarization (P r) is achieved by using a poly-GeSn film as a channel material as compared with a poly-Ge film because of the lower thermal expansion that induces higher stress. Then two-stage interface engineering of junctionless poly-GeSn (Sn of ∼5.1%) ferroelectric thin-film transistors (Fe-TFTs) based on HZO was employed to improve the reliability characteristics. With stage I of NH3 plasma treatment on poly-GeSn and subsequent stage II of Ta2O5 interfa… Show more

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Cited by 40 publications
(23 citation statements)
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“…The transistor showed linear weight update characteristics with 64 states and dynamic range of 14.4. A HfZrO x -based ferroelectric transistor with a poly-GeSn channel was also proposed as a synaptic transistor ( Figure 5 E) ( Chou et al., 2020 ). In this device, NH 3 plasma treatment of poly-GeSn and the interfacial layer was used to improve the endurance and retention characteristics.…”
Section: Artificial Synapses Based On Emerging Materialsmentioning
confidence: 99%
See 2 more Smart Citations
“…The transistor showed linear weight update characteristics with 64 states and dynamic range of 14.4. A HfZrO x -based ferroelectric transistor with a poly-GeSn channel was also proposed as a synaptic transistor ( Figure 5 E) ( Chou et al., 2020 ). In this device, NH 3 plasma treatment of poly-GeSn and the interfacial layer was used to improve the endurance and retention characteristics.…”
Section: Artificial Synapses Based On Emerging Materialsmentioning
confidence: 99%
“… (F and G) (F) Potentiation and (G) depression characteristics of devices using HfZrO x . Reproduced with permission ( Chou et al, 2020 ). Copyright 2020, American Chemical Society.…”
Section: Artificial Synapses Based On Emerging Materialsmentioning
confidence: 99%
See 1 more Smart Citation
“…One of the leading directions is utilizing the brain‐inspired parallel computing systems based on artificial synapses, i.e., artificial neural systems. [ 1,6–11 ] Just like the information transmission between the two neurons in the biological neural network, the artificial synapse provides an effective approach for data‐processing depends on biomimetic synaptic processes, which could realize a specific logic function through one individual component. [ 1,12–14 ] Through transforming presynaptic stimuli into postsynaptic responses, an artificial synaptic device could mimic the perception, learning, and memory functions of synapses in the human brain.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, Chou et al. [ 142 ] studied the three‐terminal ferroelectric memory device and adopted it in synaptic applications based on the ferroelectric material of HfZrO x (Fe‐HZO) and the semiconductor material of poly‐GeSn. First, the interface between Fe‐HZO and poly‐GeSn was treated by NH 3 plasma and was improved since the dangling bonds and trap states coming from the N/H radicals were passivated.…”
Section: Interface Engineering In Synaptic Applicationsmentioning
confidence: 99%