BEOL-Compatible Superlattice FEFET Analog Synapse With Improved Linearity and Symmetry of Weight Update

Aabrar, Khandker Akif; Kirtania, Sharadindu Gopal; Liang, Fu-Xiang; Gomez, Jorge; Jose, Matthew San; Luo, Yandong; Ye, Huacheng; Dutta, Sourav; Ravikumar, Priyankka G.; Ravindran, Prasanna Venkatesan; Khan, Asif Islam; Yu, Shimeng; Datta, Suman

doi:10.1109/ted.2022.3142239

Cited by 30 publications

(26 citation statements)

References 31 publications

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“…Although a critical nuclei size in conventional ferroelectric materials of a few nanometers was reported, research on the critical nuclei size in fluorite‐structured ferroelectrics is lacking 218 . Recently, it has been reported that the implementation of nanolaminates by inserting a dielectric interlayer could be an effective way for tailoring the domain density 222 . The E dep from a dielectric interlayer causes the decomposition of the ferroelectric domain and broadening of the E c distribution of the domains, resulting in the increase of multi‐level states with greater linearity 222 .…”

Section: Neuromorphic Computing Systems Based On Fluorite‐structured ...mentioning

confidence: 99%

“…218 Recently, it has been reported that the implementation of nanolaminates by inserting a dielectric interlayer could be an effective way for tailoring the domain density. 222 The E dep from a dielectric interlayer causes the decomposition of the ferroelectric domain and broadening of the E c distribution of the domains, resulting in the increase of multi-level states with greater linearity. 222 Another approach to achieve gradual polarization switching has been experimentally demonstrated.…”

Section: Three-terminal Devicesmentioning

confidence: 99%

“…222 The E dep from a dielectric interlayer causes the decomposition of the ferroelectric domain and broadening of the E c distribution of the domains, resulting in the increase of multi-level states with greater linearity. 222 Another approach to achieve gradual polarization switching has been experimentally demonstrated. By increasing the Si doping content in HfO 2 , the fraction of non-FE phase increases, which induces inhomogeneity in the E c distribution and enhances polarization switching dispersion in the ferroelectric layer.…”

Section: Three-terminal Devicesmentioning

confidence: 99%

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Neuromorphic devices based on fluorite‐structured ferroelectrics

Lee

Park

Kim

et al. 2022

InfoMat

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A continuous exponential rise has been observed in the storage and processing of the data that may not curtail in the foreseeable future. The required data processing speed and power consumption are restricted by the buses between the logic and memory devices that are characteristic of the von Neumann computing architecture. Bio-mimicking neuromorphic computing has garnered considerable academic and industrial interest to resolve these challenges.Additionally, devices based on emerging nonvolatile memories capable of mimicking the behaviors of synapses and neurons, which are the main elements in biological computing systems (brains), are attracting significant interest from the device community. With the discovery of ferroelectricity in fluorite-structured oxides, such as HfO 2 and ZrO 2 , which are compatible with the state-of-the-art complementary-metal-oxide-semiconductor processes, ferroelectric devices have rapidly evolved as the main direction of these research and development activities. Fundamental science related to fluorite-structured ferroelectrics has been intensively studied over the last decade. At present, the focus is gradually moving to practical applications, including neuromorphic computing and advanced classical processing or memory units in the conventional von Neumann architecture. However, despite its rapid development, the wealth of recent progress in neuromorphic computing devices based on fluorite-structured ferroelectrics has not been reviewed and systemized. This progress report comprehensively reviews and systemizes the recent progress in artificial synaptic and spiking neuron devices for neuromorphic computing based on fluorite-structured ferroelectrics.

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Section: Neuromorphic Computing Systems Based On Fluorite‐structured ...mentioning

confidence: 99%

Section: Three-terminal Devicesmentioning

confidence: 99%

Section: Three-terminal Devicesmentioning

confidence: 99%

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Neuromorphic devices based on fluorite‐structured ferroelectrics

Lee

Park

Kim

et al. 2022

InfoMat

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“…Also, extra circuit selectors are needed when implemented as a synapse array. − As an alternative to solving such problems, three-terminal devices have been identified as promising candidates for artificial synaptic devices because of their good controllability, stability, and great CMOS compatibility. Three-terminal synaptic devices can be made using a variety of materials, such as floating-gate synaptic transistors, − ferroelectric-gate synaptic transistors, − and electrolyte-gate synaptic transistors. − Among these various analog three-terminal synaptic devices, the charge trap flash (CTF) memory-based synaptic device can be one of the most promising candidates because of its great proven CMOS compatibility and product-level excellent reliability, which is good for an inference operation. However, there are known disadvantages of flash-type memory such as nonlinear synaptic weight update, and limited endurance, which restricts the use of CTF devices for the application that requires active training.…”

mentioning

confidence: 99%

Dielectric-Engineered High-Speed, Low-Power, Highly Reliable Charge Trap Flash-Based Synaptic Device for Neuromorphic Computing beyond Inference

Kim

Park

et al. 2023

Nano Lett.

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The coming of the big-data era brought a need for power-efficient computing that cannot be realized in the Von Neumann architecture. Neuromorphic computing which is motivated by the human brain can greatly reduce power consumption through matrix multiplication, and a device that mimics a human synapse plays an important role. However, many synaptic devices suffer from limited linearity and symmetry without using incremental step pulse programming (ISPP). In this work, we demonstrated a charge-trap flash (CTF)-based synaptic transistor using trap-level engineered Al 2 O 3 /Ta 2 O 5 /Al 2 O 3 gate stack for successful neuromorphic computing. This novel gate stack provided precise control of the conductance with more than 6 bits. We chose the appropriate bias for highly linear and symmetric modulation of conductance and realized it with very short (25 ns) identical pulses at low voltage, resulting in low power consumption and high reliability. Finally, we achieved high learning accuracy in the training of 60000 MNIST images.

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“…Recently, oxide semiconductors (OSs) have attracted great attention as the channel materials of Fe-FETs [14], [15], [16], [17], [18], [19], [20], [21], [22], [23]. Compared to the amorphous Si FETs, OS FETs generally have higher mobilities (>10 cm 2 •V −1 •s −1 ) while keeping a back-end-ofline (BEOL)-compatible process thermal budget for monolithic 3-D integration [24], [25].…”

mentioning

confidence: 99%

Back-End-of-Line-Compatible Fin-Gate ZnO Ferroelectric Field-Effect Transistors

Kong

Liu

Zheng

et al. 2023

IEEE Trans. Electron Devices

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We report the back-end-of-line (BEOL)compatible 3-D oxide semiconductor (OS) fin-gate ferroelectric field-effect transistors (Fe-FETs) featuring atomic layer deposition (ALD)-grown zinc oxide (ZnO) channel and Zr-doped HfO 2 (HZO) ferroelectric dielectric. Both ZnO and HZO are able to conformally cover the fin-shaped tungsten (W) metal gate with uniform thickness on all surfaces. With the optimization of ALD for the growth of the ZnO channel film and extensive gatestack engineering, our ZnO Fe-FETs show excellent electrical characteristics, including memory windows (MWs) of 1.9 and 1.5 V with the channel length (L ch ) of 1 µm and 50 nm, respectively, the high endurance of 10 8 cycles, long-term retention of more than ten years at room temperature, robust ON/OFF ratio of more than six orders, and good linearity of the multistate conductance characteristics. Together with the capability to suppress the device-to-device threshold voltage (V th ) variation due to the unique fin-gate structure, our devices demonstrate tremendous potential for future ultrahigh-density 3-D integrated computing applications.

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BEOL-Compatible Superlattice FEFET Analog Synapse With Improved Linearity and Symmetry of Weight Update

Cited by 30 publications

References 31 publications

Neuromorphic devices based on fluorite‐structured ferroelectrics

Neuromorphic devices based on fluorite‐structured ferroelectrics

Dielectric-Engineered High-Speed, Low-Power, Highly Reliable Charge Trap Flash-Based Synaptic Device for Neuromorphic Computing beyond Inference

Back-End-of-Line-Compatible Fin-Gate ZnO Ferroelectric Field-Effect Transistors

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