Results 71 to 80 of about 1,280 (239)

FeFET-Based MirrorBit Cell for High-Density NVM Storage

open access: yes
The HfO2-based ferroelectric field-effect transistor (FeFET) has become a center of attraction for nonvolatile memory application because of their low power, fast switching speed, high scalability, and CMOS compatibility.
Srinu, Rowtu   +8 more
core   +1 more source

Demonstration of Differential Mode FeFET-Array for multi-precision storage and IMC applications

open access: yes, 2023
Harnessing multibit precision in non-volatile memory (NVM) based synaptic core can accelerate multiply and accumulate (MAC) operation of deep neural network (DNN).
Raffel, Yannick   +13 more
core   +1 more source

Crystallized Domain Walls in HfO2 Enable Chessboard‐Type Ultra‐High‐Dense Ferroelectric Memory

open access: yesAdvanced Science, EarlyView.
In general, DWs in ferroelectrics stabilize within a widely spread transition region between two oppositely polarized domains, which severely limits the achievable memory density. Here, the reported DWs in HfO2 constitute perfect crystalline structures along arbitrary crystallographic directions, enabling the formation of the narrowest square‐shaped ...
Pawan Kumar   +4 more
wiley   +1 more source

Integration of BEoL Compatible 1T1C FeFET Memory Into an Established CMOS Technology

open access: yes, 2022
8184Recently, hafnium oxide based ferroelectric memories gained great attention due to good scalability, high speed operation, and low power consumption. In contrast to the FRAM concept, the FeFET offers non-destructive read-out. However, the integration
Mähne, H.   +15 more
core   +1 more source

Analysis and Design of FeFET Synapse With Stacked-Nanosheet Architecture Considering Cycle-to-Cycle Variations for Neuromorphic Applications

open access: yesIEEE Open Journal of Nanotechnology
Using extensive Monte-Carlo simulations with a nucleation-limited-switching (NLS) ferroelectric model and considering cycle-to-cycle variations, this paper constructs and analyzes the intrinsic conductance (GDS) response of stacked-nanosheet FeFET ...
Heng Li Lin, Pin Su
doaj   +1 more source

Embedding hafnium oxide based FeFETs in the memory landscape

open access: yes2018 International Conference on IC Design & Technology (ICICDT), 2018
During the last decade ferroelectrics based on doped hafnium oxide emerged as promising candidates for realization of ultra-low-power non-volatile memories. Two spontaneous polarization states occurring in the material that can be altered by applying electrical fields rather than forcing a current through and the materials compatibility to CMOS ...
Stefan Slesazeck   +2 more
openaire   +3 more sources

Mechanisms of Temperature‐Dependent Hysteresis in Freestanding BaTiO3/MoS2 Heterostructures

open access: yesAdvanced Science, EarlyView.
Freestanding ferroelectric BaTiO3 membranes are combined with monolayer MoS2 into 2D field‐effect transistors. At room temperature they provide ultrahigh‐κ gating with steep subthreshold swing and minimal hysteresis. Upon cooling, strong ferroelectric switching produces two stable memory states with long retention times.
Thomas Pucher   +7 more
wiley   +1 more source

Robust and Compatible Ferroelectric Memories with Polycrystalline TiO2 Channel for 3D Integration

open access: yesAdvanced Electronic Materials, EarlyView.
Robust and monolithic 3D compatible ferroelectric memories are realized using the polycrystalline TiO2 channel‐based FeFET. The review covers physical mechanisms of the TiO2 channel FeFET, quantitative benchmarking, and advanced planar/vertical architectures for monolithic 3D integration based on HfO2‐TiO2 gate stack, offering a roadmap for reliable ...
Xujin Song   +10 more
wiley   +1 more source

Substrate-voltage-controlled temporal nonlinearity in ferroelectric FET-based reservoir computing [PDF]

open access: yesAPL Machine Learning
Physical reservoir computing exploits inherent nonlinearity and short-term memory of physical dynamics to achieve efficient processing of time-series data with extremely-low training cost.
Eishin Nako   +4 more
doaj   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

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