A comprehensive review of advanced trends: from artificial synapses to neuromorphic systems with consideration of non-ideal effects
A neuromorphic system is composed of hardware-based artificial neurons and synaptic
devices, designed to improve the efficiency of neural computations inspired by energy …
devices, designed to improve the efficiency of neural computations inspired by energy …
Nonvolatile capacitive synapse: device candidates for charge domain compute-in-memory
Compute-in-memory (CIM) has emerged as a compelling approach to address the ever-
increasing demand for energy-efficient computing for edge artificial intelligence (AI) …
increasing demand for energy-efficient computing for edge artificial intelligence (AI) …
Ferroelectric capacitive memories: devices, arrays, and applications
Ferroelectric capacitive memories (FCMs) utilize ferroelectric polarization to modulate
device capacitance for data storage, providing a new technological pathway to achieve two …
device capacitance for data storage, providing a new technological pathway to achieve two …
When in-memory computing meets spiking neural networks—A perspective on device-circuit-system-and-algorithm co-design
This review explores the intersection of bio-plausible artificial intelligence in the form of
spiking neural networks (SNNs) with the analog in-memory computing (IMC) domain …
spiking neural networks (SNNs) with the analog in-memory computing (IMC) domain …
Demonstration of Large MW and Prominent Endurance in a Hf0.5Zr0.5O2 FeFET with IGZO Channel Utilizing Postdeposition Annealing
With high potential for back-end-of-line (BEOL) integration, HfO2-based FeFETs with
amorphous oxide semiconductor (AOS) channels have shown impressive application …
amorphous oxide semiconductor (AOS) channels have shown impressive application …
From light sensing to adaptive learning: hafnium diselenide reconfigurable memcapacitive devices in neuromorphic computing
Advancements in neuromorphic computing have given an impetus to the development of
systems with adaptive behavior, dynamic responses, and energy efficiency characteristics …
systems with adaptive behavior, dynamic responses, and energy efficiency characteristics …
Ferroelectric capacitors and field-effect transistors as in-memory computing elements for machine learning workloads
This study discusses the feasibility of Ferroelectric Capacitors (FeCaps) and Ferroelectric
Field-Effect Transistors (FeFETs) as In-Memory Computing (IMC) elements to accelerate …
Field-Effect Transistors (FeFETs) as In-Memory Computing (IMC) elements to accelerate …
A cross-layer framework for design space and variation analysis of non-volatile ferroelectric capacitor-based compute-in-memory accelerators
Using non-volatile “capacitive” crossbar arrays for compute-in-memory (CIM) offers higher
energy and area efficiency compared to “resistive” crossbar arrays. However, the impact of …
energy and area efficiency compared to “resistive” crossbar arrays. However, the impact of …
Small Signal Capacitance in Ferroelectric Hafnium Zirconium Oxide: Mechanisms and Physical Insights
This study presents a theoretical investigation of the physical mechanisms governing small
signal capacitance in ferroelectrics, focusing on Hafnium Zirconium Oxide (Hf0. 5Zr0. 5O2 …
signal capacitance in ferroelectrics, focusing on Hafnium Zirconium Oxide (Hf0. 5Zr0. 5O2 …
Reliability assesement of ferroelectric nvCAP for small-signal capacitive read-out
Unlike the conventional way to use drain current as the read-out mechanism, ferroelectric
field effect transistor (FeFET) can be read-out in a capacitive manner, namely non-volatile …
field effect transistor (FeFET) can be read-out in a capacitive manner, namely non-volatile …