Van der Waals Ferroelectric Semiconductor Field Effect Transistor for In-Memory Computing

Liao, Junyi; Wen, Wen; Wu, Juanxia; Zhou, Yaming; Hussain, Sabir; Hu, Haowen; Li, Jiawei; Liaqat, Adeel; Zhu, Hongwei; Jiao, Liying; Zheng, Qiang; Xie, Liming

doi:10.1021/acsnano.3c01198

Cited by 27 publications

(16 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to the memory application, the vdW ferroelectric semiconductor field-effect transistor shows great potential for in-memory computing. For example, Liao et al [77] constructed an InSe-based metal-oxide-ferroelectric semiconductor field-effect transistor that integrates memory and logic functions in the same ferroelectric material. The OOP ferroelectric polarization in InSe enables data storage and the semiconducting property was adopted for the logic computation; inverter, programmable NAND and NOR Boolean logic operations with non-volatile storage of the results have all been demonstrated nicely.…”

Section: Ferroelectric Semiconductor Field-effect Transistorsmentioning

confidence: 99%

Recent progress on two-dimensional ferroelectrics: Material systems and device applications

Fan 范,

Qu 渠,

Wang 王

et al. 2023

Chinese Phys. B

View full text Add to dashboard Cite

Ferroelectrics are a kind of material with polar structure and the polarization direction can be inverted reversibly by applying electric field. They have attracted tremendous attention for their extensive applications in nonvolatile memory, sensors and neuromorphic computing. However, the conventional ferroelectric materials face insulating and interfacial issues in the commercialization process. In contrast, two-dimensional (2D) ferroelectric materials usually have excellent semiconductor performance, clean van der Waals interfaces and robust ferroelectric order in atom-thick layers, which holds greater promise for constructing multifunctional ferroelectric optoelectronic devices and nondestructive ultra-high-density memory. Recently, 2D ferroelectrics have obtain impressive breakthroughs, showing overwhelming superiority. Herein, firstly, the progress of experimental research on 2D ferroelectric materials is reviewed. Then, the preparation of 2D ferroelectric devices and their applications are discussed. Finally, the future development trend of 2D ferroelectrics is prospected.

show abstract

Section: Ferroelectric Semiconductor Field-effect Transistorsmentioning

confidence: 99%

Recent progress on two-dimensional ferroelectrics: Material systems and device applications

Fan 范,

Qu 渠,

Wang 王

et al. 2023

Chinese Phys. B

View full text Add to dashboard Cite

show abstract

“…This process induces an obvious change in the energy band structure. For instance, MoS 2 has four different crystal structures, whereas MXenes have three predicted structures through theoretical calculations [53][54][55][86][87][88][89]. Ferroelectric insulators are typically used as the gate dielectric in FeFETs, where the conductance of the device channel can be used to determine the polarization direction of the ferroelectric gate material.…”

Section: Ferroelectric Channel Polarizationmentioning

confidence: 99%

“…In addition, in the latest study conducted by Xie et al, an FeS-FET was fabricated with an InSe ferroelectric channel that can also be used as NVM [55]. The researchers proved that InSe crystals undergo a change when polarized through high-angle annular dark-field scanning transmission electron microscopy.…”

Section: Ferroelectric Channel Polarizationmentioning

confidence: 99%

A review on advanced band-structure engineering with dynamic control for nonvolatile memory based 2D transistors

Zhang,

Ning,

Wang

et al. 2023

Nanotechnology

View full text Add to dashboard Cite

With advancements in information technology, an enormous amount of data is being generated that must be quickly accessible. However, conventional Si memory cells are approaching their physical limits and will be unable to meet the requirements of intense applications in the future. Notably, 2D atomically thin materials have demonstrated multiple novel physical and chemical properties that can be used to investigate next-generation electronic devices and breakthrough physical limits to continue Moore’s Law. Band structure is an important semiconductor parameter that determines their electrical and optical properties. In particular, 2D materials have highly tunable bandgaps and Fermi levels that can be achieved through band structure engineering methods such as heterostructure, substrate engineering, chemical doping, intercalation, and electrostatic doping. In particular, dynamic control of band structure engineering can be used in recent advancements in 2D devices to realize nonvolatile storage performance. This study examines recent advancements in 2D memory devices that utilize band structure engineering. The operational mechanisms and memory characteristics are described for each band structure engineering method. Band structure engineering provides a platform for developing new structures and realizing superior performance with respect to nonvolatile memory.

show abstract

“…As very large amounts of data processing become more frequent with data transfer between the memory and processor, bottlenecks occur in the traditional von Neumann computing architecture, where the memory and processor are separated. In order to solve such bottlenecks, in-memory computing structures that perform operations during memory access have been proposed as alternatives. − In-memory computing not only consolidates memory and processors to reduce the power used for data transfer but also enables parallel computing, enabling high throughput. However, due to a large amount of data and computation, there are still limitations that require huge power consumption and a very large chip size as well as being unusable for mobile and edge computing.…”

Section: Introductionmentioning

confidence: 99%

Monolithically Integrated Complementary Ferroelectric FET XNOR Synapse for the Binary Neural Network

Hwang,

Joh,

Kim

et al. 2024

ACS Appl. Mater. Interfaces

View full text Add to dashboard Cite

Neuromorphic computing, which mimics the structure and principles of the human brain, has the potential to facilitate the hardware implementation of next-generation artificial intelligence systems and process large amounts of data with very low power consumption. Among them, the XNOR synapse-based Binary Neural Network (BNN) has been attracting attention due to its compact neural network parameter size and low hardware cost. The previous XNOR synapse has drawbacks, such as a trade-off between cell density and accuracy. In this work, we show nonvolatile XNOR synapses with high density and accuracy using a monolithically stacked complementary ferroelectric field-effect transistor (C-FeFET) composed of a p-type Si MFMIS-FeFET at the bottom and a 3D stackable n-type Al:IZTO MFS-FeTFT, achieving 60F 2 per cell (2C-FeFET). For adjusting the threshold voltage and improving the switching speed (100 ns) of n-type ferroelectric TFT, we employed a dual-gate configuration and a unique operation scheme, making it comparable to those of Si-based FeFETs. We performed array-level simulation with a 512 × 512 subarray size and a 3-bit flash ADC, demonstrating that the image recognition accuracies using the MNIST and CIFAR-10 data sets were increased by 3.17 and 14.07%, respectively, in comparison to other nonvolatile XNOR synapses. In addition, we performed system-level analysis on a 512 × 512 XNOR C-FeFET, exhibiting an outstanding throughput of 717.37 GOPS and an energy efficiency of 196.7 TOPS/W. We expect that our approach would contribute to the high-density memory systems, logic-in-memory technology, and hardware implementation of neural networks.

show abstract

Van der Waals Ferroelectric Semiconductor Field Effect Transistor for In-Memory Computing

Cited by 27 publications

References 63 publications

Recent progress on two-dimensional ferroelectrics: Material systems and device applications

Recent progress on two-dimensional ferroelectrics: Material systems and device applications

A review on advanced band-structure engineering with dynamic control for nonvolatile memory based 2D transistors

Monolithically Integrated Complementary Ferroelectric FET XNOR Synapse for the Binary Neural Network

Contact Info

Product

Resources

About