Transient Investigation of Metal-oxide based, CMOS-compatible ECRAM

Solomon, P. M.; Bishop, Douglas M.; Todorov, Teodor K.; Dawes, Simon; Farmer, Damon B.; Copel, M.; Lee, Ko-Tao; Collins, John Leslie; Rozen, John

doi:10.1109/irps46558.2021.9405156

Cited by 13 publications

(16 citation statements)

References 19 publications

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“…A structure that efficiently generates heat and confines it in the ECRAM can promotes ion movement, resulting in faster switching speed. To date, physics-based modeling [ 42 ] has rarely been studied except for the equivalent circuit model [ 43 ]. A model that fits well with the experimental results will not only allow the design exploration of the synaptic devices for further improvement but also extrapolate the reliability perspective of ECRAMs.…”

Section: Discussionmentioning

confidence: 99%

Ion-Driven Electrochemical Random-Access Memory-Based Synaptic Devices for Neuromorphic Computing Systems: A Mini-Review

et al. 2022

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To enhance the computing efficiency in a neuromorphic architecture, it is important to develop suitable memory devices that can emulate the role of biological synapses. More specifically, not only are multiple conductance states needed to be achieved in the memory but each state is also analogously adjusted by consecutive identical pulses. Recently, electrochemical random-access memory (ECRAM) has been dedicatedly designed to realize the desired synaptic characteristics. Electric-field-driven ion motion through various electrolytes enables the conductance of the ECRAM to be analogously modulated, resulting in a linear and symmetric response. Therefore, the aim of this study is to review recent advances in ECRAM technology from the material and device engineering perspectives. Since controllable mobile ions play an important role in achieving synaptic behavior, the prospect and challenges of ECRAM devices classified according to mobile ion species are discussed.

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Section: Discussionmentioning

confidence: 99%

Ion-Driven Electrochemical Random-Access Memory-Based Synaptic Devices for Neuromorphic Computing Systems: A Mini-Review

et al. 2022

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“…Therefore, it is very difficult to uniformly control atomic-level changes in local filaments by applying identical voltage pulses. To solve this problem, three-terminal (3-T)-based electrochemical RAM (ECRAM) devices have been developed in which conductance is linearly changed by the bulk channel region. − In early ECRAM studies, channel conductivity was changed by using protons and lithium ions. − Excellent synaptic properties were achieved through facile ion migration based on a small ion mass. However, the main disadvantage is that conventional complementary metal–oxide–semiconductor (CMOS) processes cannot be used because a polymer- or lithium-ion-battery-based material is used as both the channel and electrolyte materials. , Moreover, because a battery stack is used as a memory device, lithium-ion-based ECRAM devices require a selector device because of open-circuit potentials …”

Section: Introductionmentioning

confidence: 99%

“…To overcome these limitations, oxygen-based ECRAM (O-ECRAM) devices are being studied as next-generation synaptic devices. − O-ECRAM devices have advantages such as CMOS compatibility and improved retention. Because RRAM-based materials are used as both electrolytes and channels in O-ECRAM devices, conventional CMOS processes can be utilized .…”

Section: Introductionmentioning

confidence: 99%

Strategies to Improve the Synaptic Characteristics of Oxygen-Based Electrochemical Random-Access Memory Based on Material Parameters Optimization

Lee

Nikam

Kwak

et al. 2022

ACS Appl. Mater. Interfaces

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Oxygen-based electrochemical random-access memories (O-ECRAMs) are promising synaptic devices for neuromorphic applications because of their near-ideal synaptic characteristics and compatibility with complementary metal–oxide–semiconductor processes. However, the correlation between material parameters and synaptic properties of O-ECRAM devices has not yet been elucidated. Here, we propose the critical design parameters to fabricate an ideal ECRAM device. Based on the experimental data and simulation results, it is revealed that consistent ion supply from the electrolyte and rapid ion diffusion in the channel are critical factors for ideal synaptic characteristics. To optimize these parameters, crystalline WO2.7 exhibiting fast ion diffusivity and ZrO1.7 exhibiting an appropriate ion conduction energy barrier (1.1 eV) are used as a channel and an electrolyte, respectively. As a result, synaptic characteristics with near-ideal weight-update linearity in the nanosiemens conductance range are achieved. Finally, a selector-less O-ECRAM device is integrated into a 2 × 2 array, and high recognition accuracy (94.83%) of the Modified National Institute of Standards and Technology pattern is evaluated.

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“…[ 32 ] In the latter case, the device conductance requires a certain time, called write‐read delay, to converge to a stable conductance state due to the redistribution of ions in the electrolyte. [ 16,33 ] It is believed that the ions migrating toward the channel will not completely transform into the non‐volatile conductance of EGT, and the diffusion of excess ions is the origin of the write‐read delay of EGT. [ 16,33 ] Compared with the high speed of ions under the high electric field generated by external voltage, the diffusion of ions under the internal electric field and concentration gradient features a significantly slower process.…”

Section: Introductionmentioning

confidence: 99%

“…[16,33] It is believed that the ions migrating toward the channel will not completely transform into the non-volatile conductance of EGT, and the diffusion of excess ions is the origin of the write-read delay of EGT. [16,33] Compared with the high speed of ions under the high electric field generated by external voltage, the diffusion of ions under the internal electric field and concentration gradient features a significantly slower process. [34,35] Since a stable conductance state is the prerequisite for hardware ANNs to perform vector-matrix multiplication, the write-read delay of EGTs will severely impact the acceleration performance of ANNs, although oxide-based EGTs have achieved write pulse widths of nanosecond.…”

Section: Introductionmentioning

confidence: 99%

Li‐Ion‐Based Electrolyte‐Gated Transistors with Short Write‐Read Delay for Neuromorphic Computing

Han

Fang

et al. 2022

Adv Elect Materials

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The hardware implementation of artificial neural networks requires synaptic devices with linear and high‐speed weight modulation. Memristors as a candidate suffer from excessive write variation and asymmetric resistance modulation that inherently rooted in their stochastic mechanisms. Thanks to a controllable ion intercalation/deintercalation mechanism, electrolyte‐gated transistors (EGTs) hold prominent switching linearity and low write variation, and thus have been the promising alternative for synaptic devices. However, the operation frequency of EGTs is seriously limited by the time that is required for the state stabilization, that is, the write‐read delay after each set/reset operation. Here, a Li‐ion‐based EGT (Li‐EGT) with write‐read delay of 3 ms along with multistates, low energy consumption, and quasi‐linear weight update is introduced. The origin of the short write‐read delay of the device is attributed to the permeable interface between electrolyte and gate electrode. Leveraging the Li‐EGT characteristic, near‐ideal accuracy (≈94%) on handwritten digital image data set has been achieved by the corresponding neural network simulation. These results provide an insight into the development of Li‐EGTs for high‐speed neuromorphic computing.

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Transient Investigation of Metal-oxide based, CMOS-compatible ECRAM

Cited by 13 publications

References 19 publications

Ion-Driven Electrochemical Random-Access Memory-Based Synaptic Devices for Neuromorphic Computing Systems: A Mini-Review

Ion-Driven Electrochemical Random-Access Memory-Based Synaptic Devices for Neuromorphic Computing Systems: A Mini-Review

Strategies to Improve the Synaptic Characteristics of Oxygen-Based Electrochemical Random-Access Memory Based on Material Parameters Optimization

Li‐Ion‐Based Electrolyte‐Gated Transistors with Short Write‐Read Delay for Neuromorphic Computing

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