High performance vertically integrated double barrier AlN memristive nonvolatile resistive random-access memory

As one of the most promising high-speed nonvolatile memristors, aluminum nitride-based memristors have shown ultrafast switching at or even below nanoseconds. However, the on/off ratio, lifespan, and endurance of nitride memristors are very limited due to their intrinsic nitrogen vacancy conduction. Here, we demonstrate that memristors built on wide bandgap semiconductor aluminate nitride AlN possessed a representative prototypical digital memristive behavior through device structure optimization. The on/off ratio of the AlN memristors could be improved to 106 using one device cell, which consists of two memristors connected in parallel with a common bottom electrode. We identified space charge limited conduction in the low resistance state and Schottky emission in the high resistance state as the dominant conduction mechanisms. The AlN-based memristors could transform to volatile memory by reducing the interfacial barrier height. We further designed and fabricated a vertically integrated double barrier AlN memristor as a nonvolatile ReRAM on 2-in. sapphire and silicon wafers. These integrated double barrier AlN memristors possess high performance with an endurance of 104, a retention of 105 s, and clear switching threshold voltages, indicating a promising nonvolatile memory.

Authors

Institutions

Publication Details

Journal
Applied Physics Letters
Published
2025-09-08
DOI
https://doi.org/10.1063/5.0267634
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High performance vertically integrated double barrier AlN memristive nonvolatile resistive random-access memory

Shengrui Xu, Haijiao Harsan, Yueying Zhang, Jincheng Zhang et al.
1 citations
Applied Physics Letters
Advanced Memory and Neural Computing
0.73
article

High performance vertically integrated double barrier AlN memristive nonvolatile resistive random-access memory

Shengrui Xu, Haijiao Harsan, Yueying Zhang, Jincheng Zhang, Yue Hao, Lei Wang, Yue-Qi Wang, Haonan Li, Yan Cao, Yi-Xing He, Chunping Jiang, Xian-Qin Liu, Zhu Jiang, Siwen Zhang
article en
1 citations

Abstract

As one of the most promising high-speed nonvolatile memristors, aluminum nitride-based memristors have shown ultrafast switching at or even below nanoseconds. However, the on/off ratio, lifespan, and endurance of nitride memristors are very limited due to their intrinsic nitrogen vacancy conduction. Here, we demonstrate that memristors built on wide bandgap semiconductor aluminate nitride AlN possessed a representative prototypical digital memristive behavior through device structure optimization. The on/off ratio of the AlN memristors could be improved to 106 using one device cell, which consists of two memristors connected in parallel with a common bottom electrode. We identified space charge limited conduction in the low resistance state and Schottky emission in the high resistance state as the dominant conduction mechanisms. The AlN-based memristors could transform to volatile memory by reducing the interfacial barrier height. We further designed and fabricated a vertically integrated double barrier AlN memristor as a nonvolatile ReRAM on 2-in. sapphire and silicon wafers. These integrated double barrier AlN memristors possess high performance with an endurance of 104, a retention of 105 s, and clear switching threshold voltages, indicating a promising nonvolatile memory.

Applied Physics LettersVol. 127(10)
Xidian University (CN), Suzhou Institute of Nano-tech and Nano-bionics (CN)
Openalex Percentile: Top 23%
Advanced Memory and Neural Computing
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.