Proton‐Modulated Resistive Switching in a Synapse‐Like Tyrosine‐Rich Peptide‐Based Memristor

Abstract Artificial intelligence has become an essential part of the daily lives and has revolutionized various sectors, including healthcare, finance, transportation, and entertainment. With a substantial increase in processed data, neuromorphic devices that replicate the operation of the human brain have been emphasized owing to their superior efficiency. Typical neuromorphic devices focus on constructing synapse‐like structures. However, biological synapses have more complex mechanisms for efficient data processing. One of the most prominent mechanisms is proton activation, which forms an ion concentration gradient prior to the transmission of neurotransmitters and plays a key role in efficient computation. In this study, proton‐mediated signaling at biological synapses is successfully replicated by fabricating a proton‐modulated memristor device using a tyrosine‐rich peptide film. The ionic input of the memristor is controlled by applying a voltage to proton‐permeable PdH x contacts in a hydrogen atmosphere, thus successfully adjusting the resistive switching behavior. Remarkable improvements in resistive switching and computing performance are observed through proton injection, analogous to “proton‐mediated signaling” at the actual synapse. It is believed that this study proposes a new paradigm for designing biorealistic devices and provides inspiration for precisely controllable ion‐based neuromorphic devices.

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Publication Details

Journal
Advanced Functional Materials
Published
2024-11-05
DOI
https://doi.org/10.1002/adfm.202415222
Citations
10
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.09

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article

Proton‐Modulated Resistive Switching in a Synapse‐Like Tyrosine‐Rich Peptide‐Based Memristor

Min‐Kyu Song, Seok Daniel Namgung, Jang‐Yeon Kwon, Wooho Ham et al.
10 citations
Advanced Functional Materials
Advanced Memory and Neural Computing
2.09
article

Proton‐Modulated Resistive Switching in a Synapse‐Like Tyrosine‐Rich Peptide‐Based Memristor

Min‐Kyu Song, Seok Daniel Namgung, Jang‐Yeon Kwon, Wooho Ham, Jeongmin Park, Jeong-Min Park, Jeong Hyun Yoon
article en
10 citations

Abstract

Abstract Artificial intelligence has become an essential part of the daily lives and has revolutionized various sectors, including healthcare, finance, transportation, and entertainment. With a substantial increase in processed data, neuromorphic devices that replicate the operation of the human brain have been emphasized owing to their superior efficiency. Typical neuromorphic devices focus on constructing synapse‐like structures. However, biological synapses have more complex mechanisms for efficient data processing. One of the most prominent mechanisms is proton activation, which forms an ion concentration gradient prior to the transmission of neurotransmitters and plays a key role in efficient computation. In this study, proton‐mediated signaling at biological synapses is successfully replicated by fabricating a proton‐modulated memristor device using a tyrosine‐rich peptide film. The ionic input of the memristor is controlled by applying a voltage to proton‐permeable PdH x contacts in a hydrogen atmosphere, thus successfully adjusting the resistive switching behavior. Remarkable improvements in resistive switching and computing performance are observed through proton injection, analogous to “proton‐mediated signaling” at the actual synapse. It is believed that this study proposes a new paradigm for designing biorealistic devices and provides inspiration for precisely controllable ion‐based neuromorphic devices.

Advanced Functional MaterialsVol. 35(7)
Yonsei University (KR), Massachusetts Institute of Technology (US), Chung-Ang University (KR)
National Research Foundation, National Research Foundation of Korea, Ministry of Education, India, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 12%
Advanced Memory and Neural Computing
2.09
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