Ge N‐Channel Ferroelectric FET Memory With Al<sub>2</sub>O<sub>3</sub>/AlN Interfacial Layer by Microwave Annealing

Abstract While n‐FeFET memory devices have shown promising characteristics for data storage and neuromorphic computing, implementing such devices with a Ge channel, which is expected to be adopted in advanced technology nodes, has never been reported due to the challenges in achieving desirable Ge interface quality. In this work, ferroelectric HfZrO x (HZO) is integrated with a high‐k Al 2 O 3 /AlN interfacial layer (IL), along with microwave annealing (MWA), to implement Ge n‐FeFET memory devices, and their memory and reliability characteristics, as well as their potential for neuromorphic applications, are extensively explored. A large memory window (MW) of 2.5 V is achieved by applying ±5 V for 5 µs while 3 bits/cell (triple‐level cell) operation is demonstrated. By using a recovery scheme, excellent 1‐bit/cell (single‐level cell) characteristics up to 10 8 cycles are also obtained. The proposed IL and low thermal budget of MWA alleviate element diffusion and reduce oxygen vacancies, marking the first demonstration of Ge n‐FeFET memory devices controlled by dipoles. Furthermore, short‐term synaptic plasticity, such as excitatory/inhibitory postsynaptic currents (EPSC/IPSC), which are essential for neuromorphic computing is also achieved. These findings suggest that Ge n‐FeFET memory devices could pave the way for high‐density embedded memory applications and could further be integrated with existing Ge p‐FeFET memory devices to form Ge‐based FeCMOS, enabling more versatile circuit functionalities.

Authors

Institutions

Publication Details

Journal
Advanced Electronic Materials
Published
2025-03-06
DOI
https://doi.org/10.1002/aelm.202400841
Citations
2
Primary Topic
Ferroelectric and Negative Capacitance Devices
Type
article
Field-Weighted Citation Impact
1.46

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ge N‐Channel Ferroelectric FET Memory With Al2O3/AlN Interfacial Layer by Microwave Annealing

Yung‐Hsien Wu, Y.-N. Chen, Sheng‐Yen Zheng, Wei‐Ning Kao
2 citations
Advanced Electronic Materials
Ferroelectric and Negative Capacitance Devices
1.46
article

Ge N‐Channel Ferroelectric FET Memory With Al2O3/AlN Interfacial Layer by Microwave Annealing

Yung‐Hsien Wu, Y.-N. Chen, Sheng‐Yen Zheng, Wei‐Ning Kao
article en
2 citations

Abstract

Abstract While n‐FeFET memory devices have shown promising characteristics for data storage and neuromorphic computing, implementing such devices with a Ge channel, which is expected to be adopted in advanced technology nodes, has never been reported due to the challenges in achieving desirable Ge interface quality. In this work, ferroelectric HfZrO x (HZO) is integrated with a high‐k Al 2 O 3 /AlN interfacial layer (IL), along with microwave annealing (MWA), to implement Ge n‐FeFET memory devices, and their memory and reliability characteristics, as well as their potential for neuromorphic applications, are extensively explored. A large memory window (MW) of 2.5 V is achieved by applying ±5 V for 5 µs while 3 bits/cell (triple‐level cell) operation is demonstrated. By using a recovery scheme, excellent 1‐bit/cell (single‐level cell) characteristics up to 10 8 cycles are also obtained. The proposed IL and low thermal budget of MWA alleviate element diffusion and reduce oxygen vacancies, marking the first demonstration of Ge n‐FeFET memory devices controlled by dipoles. Furthermore, short‐term synaptic plasticity, such as excitatory/inhibitory postsynaptic currents (EPSC/IPSC), which are essential for neuromorphic computing is also achieved. These findings suggest that Ge n‐FeFET memory devices could pave the way for high‐density embedded memory applications and could further be integrated with existing Ge p‐FeFET memory devices to form Ge‐based FeCMOS, enabling more versatile circuit functionalities.

Advanced Electronic MaterialsVol. 11(9)
National Tsing Hua University (TW)
Ministry of Science and Technology, Taiwan
Openalex Percentile: Top 19%
Ferroelectric and Negative Capacitance Devices
1.46
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.