Ferroelectric HfO2-based synaptic devices: recent trends and prospects. (20th September 2021)
- Record Type:
- Journal Article
- Title:
- Ferroelectric HfO2-based synaptic devices: recent trends and prospects. (20th September 2021)
- Main Title:
- Ferroelectric HfO2-based synaptic devices: recent trends and prospects
- Authors:
- Yu, Shimeng
Hur, Jae
Luo, Yuan-Chun
Shim, Wonbo
Choe, Gihun
Wang, Panni - Abstract:
- Abstract: Neuro-inspired deep learning algorithms have shown promising futures in artificial intelligence. Despite the remarkable progress in software-based neural networks, the traditional von-Neumann hardware architecture has suffered from limited energy efficiency while facing unprecedented large amounts of data. To meet the performance requirements of neuro-inspired computing, large-scale vector-matrix multiplication is preferred to be performed in situ, namely compute-in-memory. Non-volatile memory devices with different materials have been proposed for weight storage as synaptic devices. Among them, HfO2 -based ferroelectric devices have attracted great attention because of their low energy consumption, good complementary-metal-oxide-semiconductor (CMOS) compatibility and multi-bit per cell potential. In this review, recent trends and prospects of the ferroelectric synaptic devices are surveyed. First, we present the three-terminal synaptic devices based on the ferroelectric field effect transistor (FeFET), and discuss the switching physics of the intermediate states, the back-end-of-line integration and the 3D NAND architecture design. Then, we introduce a hybrid precision synapse concept that leverages the volatile charges on the gate capacitor of the FeFET and the non-volatile polarization on the gate dielectric of the FeFET. Lastly, we review two-terminal synaptic devices using the ferroelectric tunnel junction (FTJ) and ferroelectric capacitor (FeCAP). The designAbstract: Neuro-inspired deep learning algorithms have shown promising futures in artificial intelligence. Despite the remarkable progress in software-based neural networks, the traditional von-Neumann hardware architecture has suffered from limited energy efficiency while facing unprecedented large amounts of data. To meet the performance requirements of neuro-inspired computing, large-scale vector-matrix multiplication is preferred to be performed in situ, namely compute-in-memory. Non-volatile memory devices with different materials have been proposed for weight storage as synaptic devices. Among them, HfO2 -based ferroelectric devices have attracted great attention because of their low energy consumption, good complementary-metal-oxide-semiconductor (CMOS) compatibility and multi-bit per cell potential. In this review, recent trends and prospects of the ferroelectric synaptic devices are surveyed. First, we present the three-terminal synaptic devices based on the ferroelectric field effect transistor (FeFET), and discuss the switching physics of the intermediate states, the back-end-of-line integration and the 3D NAND architecture design. Then, we introduce a hybrid precision synapse concept that leverages the volatile charges on the gate capacitor of the FeFET and the non-volatile polarization on the gate dielectric of the FeFET. Lastly, we review two-terminal synaptic devices using the ferroelectric tunnel junction (FTJ) and ferroelectric capacitor (FeCAP). The design margins of the crossbar array with FTJ and FeCAP analyzed. … (more)
- Is Part Of:
- Semiconductor science and technology. Volume 36:Number 10(2021)
- Journal:
- Semiconductor science and technology
- Issue:
- Volume 36:Number 10(2021)
- Issue Display:
- Volume 36, Issue 10 (2021)
- Year:
- 2021
- Volume:
- 36
- Issue:
- 10
- Issue Sort Value:
- 2021-0036-0010-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-09-20
- Subjects:
- ferroelectricity -- HfO2 ferroelectrics -- ferroelectric field effect transistor (FeFET) -- ferroelectric tunnel junction (FTJ) -- back-end-of-line (BEOL) -- 3D NAND -- compute-in-memory (CIM)
Semiconductors -- Periodicals
621.38152 - Journal URLs:
- http://iopscience.iop.org/0268-1242/1 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1361-6641/ac1b11 ↗
- Languages:
- English
- ISSNs:
- 0268-1242
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 19040.xml