Progressive and Stable Synaptic Plasticity with Femtojoule Energy Consumption by the Interface Engineering of a Metal/Ferroelectric/Semiconductor

Kim, Sohwi; Yoon, Chansoo; Oh, Gwangtaek; Lee, Young Woong; Shin, Mincheol; Kee, Eun Hee; Park, Bae Ho; Lee, Ji Hye; Park, Sang‐Hyun; Kang, Bo Soo; Kim, Young Heon

doi:10.1002/advs.202201502

Cited by 11 publications

(3 citation statements)

References 52 publications

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“…has not been reported for previous ferroelectric and multiferroic materials, which is important for the application of memristor in the IoT nodes. We also notice that the recently proposed Ag/PZT/Nb:SrTiO 3 FTJ, [31] Ni/PZT/Nb-doped SrTiO 3 heterojunction [32] and Au/BaTiO 3 /La 0.75 Sr 0.25 MnO 3 multiferroic structure [39] could provide obviously higher on-off ratios than that of proposed multiferroic memristor, since the FTJ usually utilizes the tunneling effect of ultrathin ferroelectric film, while the thickness of ferroelectric layer in this study is several orders of magnitude larger. By decreasing the thickness of PZTM layer and integrating the FTJ with proposed multiferroic heterostructure, the on-off ratio can be improved significantly.…”

Section: Wireless Transmission Of Stored Informationmentioning

confidence: 67%

“…[8] Such multilevel polarization switching was also observed in the ultrathin epitaxial PbZr 0.52 Ti 0.48 O 3 (PZT) films by driving the system toward the instability at the morphotropic phase boundary. [30] And Ferroelectric domain switching of Ag/PZT/Nb:SrTiO 3 ferroelectric tunnel junction (FTJ) [31] and Ni/PZT/Nb-doped SrTiO 3 heterojunction [32] were also explored for the high-precision and liner weight updates of neuro-inspired computing application. However, coupling electrically modulated GMI of magnetostrictive material with impedance of piezoelectric layer for the memristor application has not been reported yet.…”

Section: Multiferroic Memristormentioning

confidence: 99%

“…The other one is to utilize the multilevel polarization switching of ultrathin piezoelectric film. [30,31] Additionally other multiferroic memristors based on FTJ [32] and resistive switching [39] have been also investigated recently.…”

Section: Wireless Transmission Of Stored Informationmentioning

confidence: 99%

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Wireless Multiferroic Memristor with Coupled Giant Impedance and Artificial Synapse Application

Wang

Xiao

et al. 2022

Adv Elect Materials

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estimated that more than 30 billion of IoT nodes, [1] such as sensors, radio-frequency identification (RFID) tags, and smart phones etc., will realize the network connection by 2025. Usually the IoT nodes are required to sense the environment, process the sensed data locally and transmit preconditioned data wirelessly; however, their power budgets are severely tight since the IoT nodes are usually powered by the battery or energy harvester. Correspondingly in order to realize the multifunction of IoT nodes with limited power budgets, the researchers have tried to integrate the microprocessor, memory, and graphic processor on a chip to realize the parallel processing of multiple tasks. For example, Kim proposed memory mapping technologies [2] to save the energy consumption of ferroelectric random access memory (FeRAM) based IoT nodes. Engel studied the low power consumed particle algorithm [3] to optimize the data transfer among storage, computing, sensing, and wireless communication units. However, the power consumption and computation speed of IoT nodes are still hindered by the von Neumann computing architecture with physically separated memory and processing units. Furthermore the current IoT nodes [1][2][3] usually implement the separated wireless communication modules (e.g., Bluetooth and RFID) to transmit and receive information of the memory and computation units, which impede the integration of chip and further increase the power consumption due to the large amount of data transferred among different units.In order to break the bottleneck of von Neumann computing architecture, various memristors [4][5][6][7][8][9][10][11][12] have been studied to construct the energy and computation speed efficient computing system (e.g., neuromorphic computing system) by integrating the memory and computation functions in a single device. Specifically the neuromorphic computing system is inspired by the human brain, which enables parallel signal storage and processing with much lower energy consumption. It is known that human brain comprises ≈10 11 neurons interconnected with 10 15 synapses, [4] whose connection strength can be regulated in response to neural stimuli. Since the conduction of memristor varies depending on the history of electrical stimuli, it can be utilized to mimic the plasticity of synapses (i.e., synaptic weight) and modulate the strength of connection between neighboring neurons. Recently various memristor-based synapse devices Internet of things (IoT) becomes part of everyday life across the globe, whose nodes are able to sense, store, and transmit information wirelessly. However, the IoT nodes based on von Neumann architectures realize the memory, computing and communication functions with physical separated devices, which result in severe power consumption and computation latency. In this study, a wireless multiferroic memristor consisting of Metglas/Pb(Zr 0.3 Ti 0.7 ) O 3 -1 mol% Mn/Metglas laminate is proposed, which integrates the storage, processing, and wireless communication of information i...

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Section: Wireless Transmission Of Stored Informationmentioning

confidence: 67%

Section: Multiferroic Memristormentioning

confidence: 99%

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Wireless Multiferroic Memristor with Coupled Giant Impedance and Artificial Synapse Application

Wang

Xiao

et al. 2022

Adv Elect Materials

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Progressive and Stable Synaptic Plasticity with Femtojoule Energy Consumption by the Interface Engineering of a Metal/Ferroelectric/Semiconductor

Kim

Yoon

et al. 2022

Advanced Science

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In the era of “big data,” the cognitive system of the human brain is being mimicked through hardware implementation of highly accurate neuromorphic computing by progressive weight update in synaptic electronics. Low‐energy synaptic operation requires both low reading current and short operation time to be applicable to large‐scale neuromorphic computing systems. In this study, an energy‐efficient synaptic device is implemented comprising a Ni/Pb(Zr 0.52 Ti 0.48 )O 3 (PZT)/0.5 wt.% Nb‐doped SrTiO 3 (Nb:STO) heterojunction with a low reading current of 10 nA and short operation time of 20–100 ns. Ultralow femtojoule operation below 9 fJ at a synaptic event, which is comparable to the energy required for synaptic events in the human brain (10 fJ), is achieved by adjusting the Schottky barrier between the top electrode and ferroelectric film. Moreover, progressive domain switching in ferroelectric PZT successfully induces both low nonlinearity/asymmetry and good stability of the weight update. The synaptic device developed here can facilitate the development of large‐scale neuromorphic arrays for artificial neural networks with low energy consumption and high accuracy.

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Low‐Temperature Nanosecond Laser Process of HZO‐IGZO FeFETs toward Monolithic 3D System on Chip Integration

Kim,

Jeong,

Pyo

et al. 2024

Advanced Science

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Ferroelectric field‐effect transistors (FeFETs) are increasingly important for in‐memory computing and monolithic 3D (M3D) integration in system‐on‐chip (SoC) applications. However, the high‐temperature processing required by most ferroelectric memories can lead to thermal damage to the underlying device layers, which poses significant physical limitations for 3D integration processes. To solve this problem, the study proposes using a nanosecond pulsed laser for selective annealing of hafnia‐based FeFETs, enabling precise control of heat penetration depth within thin films. Sufficient thermal energy is delivered to the IGZO oxide channel and HZO ferroelectric gate oxide without causing thermal damage to the bottom layer, which has a low transition temperature (<250 °C). Using optimized laser conditions, a fast response time (<1 µs) and excellent stability (cycle > 106, retention > 106 s) are achieved in the ferroelectric HZO film. The resulting FeFET exhibited a wide memory window (>1.7 V) with a high on/off ratio (>105). In addition, moderate ferroelectric properties (2·Pr of 14.7 µC cm−2) and pattern recognition rate‐based linearity (potentiation: 1.13, depression: 1.6) are obtained. These results demonstrate compatibility in HZO FeFETs by specific laser annealing control and thin‐film layer design for various structures (3D integrated, flexible) with neuromorphic applications.

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Progressive and Stable Synaptic Plasticity with Femtojoule Energy Consumption by the Interface Engineering of a Metal/Ferroelectric/Semiconductor

Cited by 11 publications

References 52 publications

Wireless Multiferroic Memristor with Coupled Giant Impedance and Artificial Synapse Application

Wireless Multiferroic Memristor with Coupled Giant Impedance and Artificial Synapse Application

Progressive and Stable Synaptic Plasticity with Femtojoule Energy Consumption by the Interface Engineering of a Metal/Ferroelectric/Semiconductor

Low‐Temperature Nanosecond Laser Process of HZO‐IGZO FeFETs toward Monolithic 3D System on Chip Integration

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