HfAlOx-based ferroelectric memristor for nociceptor and synapse functions
- Authors
- Ju, Dongyeol; Park, Yongjin; Noh, Minseo; Koo, Minsuk; Kim, Sungjun
- Issue Date
- Aug-2024
- Publisher
- AIP Publishing
- Keywords
- Hafnium; Hafnium; Hafnium Oxides; Metal Insulator Boundaries; Semiconductor Insulator Boundaries; Tin Compounds; Dorsal Root Ganglions; External Stimulus; Hebbian Learning; Hyperalgesia; Learning Rules; Memristor; Metal Ferroelectric Insulator Semiconductors; Nociceptor; Potential Harm; Sensitisation; Memristors; Hafnium; Chemistry; Human; Pain Receptor; Physiology; Semiconductor; Synapse; Hafnium; Humans; Nociceptors; Semiconductors; Synapses
- Citation
- The Journal of Chemical Physics, v.161, no.8, pp 1 - 12
- Pages
- 12
- Indexed
- SCIE
SCOPUS
- Journal Title
- The Journal of Chemical Physics
- Volume
- 161
- Number
- 8
- Start Page
- 1
- End Page
- 12
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/23007
- DOI
- 10.1063/5.0224896
- ISSN
- 0021-9606
1089-7690
- Abstract
- Efficient data processing is heavily reliant on prioritizing specific stimuli and categorizing incoming information. Within human biological systems, dorsal root ganglions (particularly nociceptors situated in the skin) perform a pivotal role in detecting external stimuli. These neurons send warnings to our brain, priming it to anticipate potential harm and prevent injury. In this study, we explore the potential of using a ferroelectric memristor device structured as a metal-ferroelectric-insulator-semiconductor as an artificial nociceptor. The aim of this device is to electrically receive external damage and interpret signals of danger. The TiN/HfAlOx (HAO)/HfSiOx (HSO)/n+ Si configuration of this device replicates the key functions of a biological nociceptor. The emulation includes crucial aspects, such as threshold reactivity, relaxation, no adaptation, and sensitization phenomena known as “allodynia” and “hyperalgesia.” Moreover, we propose establishing a connection between nociceptors and synapses by training the Hebbian learning rule. This involves exposing the device to injurious stimuli and using this experience to enhance its responsiveness, replicating synaptic plasticity. © 2024 Author(s).
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Collections - College of Engineering > Department of Electronics and Electrical Engineering > 1. Journal Articles

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