Nano-Memristors with 4 mV Switching Voltage Based on Surface-Modified Copper Nanoparticles

Peisong Liu; Fei Hui; Fernando Aguirre; Fernan Saiz; Lulu Tian; Tingting Han; Zhijun Zhang; Enrique Miranda; Mario Lanza

doi:10.1002/adma.202201197

Nano-Memristors with 4 mV Switching Voltage Based on Surface-Modified Copper Nanoparticles

Peisong Liu, Fei Hui, Fernando Aguirre, Fernan Saiz, Lulu Tian, Tingting Han, Zhijun Zhang, Enrique Miranda, Mario Lanza^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

The development of memristors operating at low switching voltages <50 mV can be very useful to avoid signal amplification in many types of circuits, such as those used in bioelectronic applications to interact with neurons and nerves. Here, it is reported that 400 nm-thick films made of dalkyl-dithiophosphoric (DDP) modified copper nanoparticles (CuNPs) exhibit volatile threshold-type resistive switching (RS) at ultralow switching voltage of ≈4 mV. The RS is observed in small nanocells with a lateral size of <50 nm^–2, during hundreds of cycles, and with an ultralow variability. Atomistic calculations reveal that the switching mechanism is related to the modification of the Schottky barriers and insulator-to-metal transition when ionic movement is induced via external bias. The devices are also used to model integrate-and-fire neurons for spiking neural networks and it is concluded that circuits employing DDP-CuNPs consume around ten times less power than similar neurons implemented with a memristor that switches at 40 mV.

Original language	English (US)
Article number	2201197
Journal	Advanced Materials
Volume	34
Issue number	20
DOIs	https://doi.org/10.1002/adma.202201197
State	Published - May 19 2022

Bibliographical note

Funding Information:
P.L. and F.H. contributed equally to this work. This work was supported by the Ministry of Science and Technology of China (grants no. 2019YFE0124200 and 2018YFE0100800), and the National Natural Science Foundation of China (grants no. 61874075), the Science and Technology Planning Project of Henan Province (212102210466), the first‐class subject cultivation project of Henan University (2019YLZDJL12), as well as by the generous Baseline funding program of the King Abdullah University of Science and Technology.

Funding Information:
P.L. and F.H. contributed equally to this work. This work was supported by the Ministry of Science and Technology of China (grants no. 2019YFE0124200 and 2018YFE0100800), and the National Natural Science Foundation of China (grants no. 61874075), the Science and Technology Planning Project of Henan Province (212102210466), the first-class subject cultivation project of Henan University (2019YLZDJL12), as well as by the generous Baseline funding program of the King Abdullah University of Science and Technology.

Publisher Copyright:
© 2022 Wiley-VCH GmbH.

Keywords

copper nanoparticles
density functional theory
memristors
resistive switching
spiking neural networks

ASJC Scopus subject areas

General Materials Science
Mechanics of Materials
Mechanical Engineering

Access to Document

10.1002/adma.202201197

Cite this

@article{bb316fdc4a844487b0fdbe6cbae8f13f,

title = "Nano-Memristors with 4 mV Switching Voltage Based on Surface-Modified Copper Nanoparticles",

abstract = "The development of memristors operating at low switching voltages <50 mV can be very useful to avoid signal amplification in many types of circuits, such as those used in bioelectronic applications to interact with neurons and nerves. Here, it is reported that 400 nm-thick films made of dalkyl-dithiophosphoric (DDP) modified copper nanoparticles (CuNPs) exhibit volatile threshold-type resistive switching (RS) at ultralow switching voltage of ≈4 mV. The RS is observed in small nanocells with a lateral size of <50 nm–2, during hundreds of cycles, and with an ultralow variability. Atomistic calculations reveal that the switching mechanism is related to the modification of the Schottky barriers and insulator-to-metal transition when ionic movement is induced via external bias. The devices are also used to model integrate-and-fire neurons for spiking neural networks and it is concluded that circuits employing DDP-CuNPs consume around ten times less power than similar neurons implemented with a memristor that switches at 40 mV.",

keywords = "copper nanoparticles, density functional theory, memristors, resistive switching, spiking neural networks",

author = "Peisong Liu and Fei Hui and Fernando Aguirre and Fernan Saiz and Lulu Tian and Tingting Han and Zhijun Zhang and Enrique Miranda and Mario Lanza",

note = "Funding Information: P.L. and F.H. contributed equally to this work. This work was supported by the Ministry of Science and Technology of China (grants no. 2019YFE0124200 and 2018YFE0100800), and the National Natural Science Foundation of China (grants no. 61874075), the Science and Technology Planning Project of Henan Province (212102210466), the first‐class subject cultivation project of Henan University (2019YLZDJL12), as well as by the generous Baseline funding program of the King Abdullah University of Science and Technology. Funding Information: P.L. and F.H. contributed equally to this work. This work was supported by the Ministry of Science and Technology of China (grants no. 2019YFE0124200 and 2018YFE0100800), and the National Natural Science Foundation of China (grants no. 61874075), the Science and Technology Planning Project of Henan Province (212102210466), the first-class subject cultivation project of Henan University (2019YLZDJL12), as well as by the generous Baseline funding program of the King Abdullah University of Science and Technology. Publisher Copyright: {\textcopyright} 2022 Wiley-VCH GmbH.",

year = "2022",

month = may,

day = "19",

doi = "10.1002/adma.202201197",

language = "English (US)",

volume = "34",

journal = "Advanced Materials",

issn = "0935-9648",

publisher = "WILEY-V C H VERLAG GMBH",

number = "20",

}

TY - JOUR

T1 - Nano-Memristors with 4 mV Switching Voltage Based on Surface-Modified Copper Nanoparticles

AU - Liu, Peisong

AU - Hui, Fei

AU - Aguirre, Fernando

AU - Saiz, Fernan

AU - Tian, Lulu

AU - Han, Tingting

AU - Zhang, Zhijun

AU - Miranda, Enrique

AU - Lanza, Mario

N1 - Funding Information: P.L. and F.H. contributed equally to this work. This work was supported by the Ministry of Science and Technology of China (grants no. 2019YFE0124200 and 2018YFE0100800), and the National Natural Science Foundation of China (grants no. 61874075), the Science and Technology Planning Project of Henan Province (212102210466), the first‐class subject cultivation project of Henan University (2019YLZDJL12), as well as by the generous Baseline funding program of the King Abdullah University of Science and Technology. Funding Information: P.L. and F.H. contributed equally to this work. This work was supported by the Ministry of Science and Technology of China (grants no. 2019YFE0124200 and 2018YFE0100800), and the National Natural Science Foundation of China (grants no. 61874075), the Science and Technology Planning Project of Henan Province (212102210466), the first-class subject cultivation project of Henan University (2019YLZDJL12), as well as by the generous Baseline funding program of the King Abdullah University of Science and Technology. Publisher Copyright: © 2022 Wiley-VCH GmbH.

PY - 2022/5/19

Y1 - 2022/5/19

N2 - The development of memristors operating at low switching voltages <50 mV can be very useful to avoid signal amplification in many types of circuits, such as those used in bioelectronic applications to interact with neurons and nerves. Here, it is reported that 400 nm-thick films made of dalkyl-dithiophosphoric (DDP) modified copper nanoparticles (CuNPs) exhibit volatile threshold-type resistive switching (RS) at ultralow switching voltage of ≈4 mV. The RS is observed in small nanocells with a lateral size of <50 nm–2, during hundreds of cycles, and with an ultralow variability. Atomistic calculations reveal that the switching mechanism is related to the modification of the Schottky barriers and insulator-to-metal transition when ionic movement is induced via external bias. The devices are also used to model integrate-and-fire neurons for spiking neural networks and it is concluded that circuits employing DDP-CuNPs consume around ten times less power than similar neurons implemented with a memristor that switches at 40 mV.

AB - The development of memristors operating at low switching voltages <50 mV can be very useful to avoid signal amplification in many types of circuits, such as those used in bioelectronic applications to interact with neurons and nerves. Here, it is reported that 400 nm-thick films made of dalkyl-dithiophosphoric (DDP) modified copper nanoparticles (CuNPs) exhibit volatile threshold-type resistive switching (RS) at ultralow switching voltage of ≈4 mV. The RS is observed in small nanocells with a lateral size of <50 nm–2, during hundreds of cycles, and with an ultralow variability. Atomistic calculations reveal that the switching mechanism is related to the modification of the Schottky barriers and insulator-to-metal transition when ionic movement is induced via external bias. The devices are also used to model integrate-and-fire neurons for spiking neural networks and it is concluded that circuits employing DDP-CuNPs consume around ten times less power than similar neurons implemented with a memristor that switches at 40 mV.

KW - copper nanoparticles

KW - density functional theory

KW - memristors

KW - resistive switching

KW - spiking neural networks

UR - http://www.scopus.com/inward/record.url?scp=85127977744&partnerID=8YFLogxK

U2 - 10.1002/adma.202201197

DO - 10.1002/adma.202201197

M3 - Article

C2 - 35320590

AN - SCOPUS:85127977744

SN - 0935-9648

VL - 34

JO - Advanced Materials

JF - Advanced Materials

IS - 20

M1 - 2201197

ER -