Low-voltage driven I–V hysteresis loop in Ag/SrTiO3/Si heterostructure

Hysteresis loop is a vital feature in the study of electronic devices, like ferroelectric hysteresis loop in ferroelectric devices, magnetic hysteresis loop in spin-electronic devices, and current–voltage (I–V) loop in memristors. Here, we report a type of I–V loop observed in the Ag/SrTiO3/Si structure, which can be dynamically varied by purely electrical modulation. This phenomenon can be attributed to the capacitive effect based on the resistance–capacitance circuit model. Additionally, we further explore the carrier transport mechanism by establishing different modulation methods of I–V hysteresis loops. This work expands our understanding of the behavior of electronic devices.

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Publication Details

Journal
Applied Physics Letters
Published
2025-08-04
DOI
https://doi.org/10.1063/5.0275258
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73

Funders

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article

Low-voltage driven I–V hysteresis loop in Ag/SrTiO3/Si heterostructure

Yuhong Cao, Dehui Huang, Hui Wang, Kang’an Jiang et al.
1 citations
Applied Physics Letters
Advanced Memory and Neural Computing
0.73
article

Low-voltage driven I–V hysteresis loop in Ag/SrTiO3/Si heterostructure

Yuhong Cao, Dehui Huang, Hui Wang, Kang’an Jiang, Yuyang Zhang
article en
1 citations

Abstract

Hysteresis loop is a vital feature in the study of electronic devices, like ferroelectric hysteresis loop in ferroelectric devices, magnetic hysteresis loop in spin-electronic devices, and current–voltage (I–V) loop in memristors. Here, we report a type of I–V loop observed in the Ag/SrTiO3/Si structure, which can be dynamically varied by purely electrical modulation. This phenomenon can be attributed to the capacitive effect based on the resistance–capacitance circuit model. Additionally, we further explore the carrier transport mechanism by establishing different modulation methods of I–V hysteresis loops. This work expands our understanding of the behavior of electronic devices.

Applied Physics LettersVol. 127(5)
Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 25%
Advanced Memory and Neural Computing
0.73
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