On the strong coupling of polarization and charge trapping in HfO2/Si-based ferroelectric field-effect transistors: overview of device operation and reliability
Ferroelectric field-effect transistors (FeFETs) have become an attractive technology for
memory and emerging applications on a silicon electronic platform after the discovery of the …
memory and emerging applications on a silicon electronic platform after the discovery of the …
Towards efficient in-memory computing hardware for quantized neural networks: state-of-the-art, open challenges and perspectives
O Krestinskaya, L Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The amount of data processed in the cloud, the development of Internet-of-Things (IoT)
applications, and growing data privacy concerns force the transition from cloud-based to …
applications, and growing data privacy concerns force the transition from cloud-based to …
Reservoir computing on a silicon platform with a ferroelectric field-effect transistor
K Toprasertpong, E Nako, Z Wang, R Nakane… - Communications …, 2022 - nature.com
Reservoir computing offers efficient processing of time-series data with exceptionally low
training cost for real-time computing in edge devices where energy and hardware resources …
training cost for real-time computing in edge devices where energy and hardware resources …
Comprehending in-memory computing trends via proper benchmarking
NR Shanbhag, SK Roy - 2022 IEEE Custom Integrated Circuits …, 2022 - ieeexplore.ieee.org
Since its inception in 2014 [1], the modern version of in-memory computing (IMC) has
become an active area of research in integrated circuit design globally for realizing artificial …
become an active area of research in integrated circuit design globally for realizing artificial …
Benchmarking in-memory computing architectures
NR Shanbhag, SK Roy - IEEE Open Journal of the Solid-State …, 2022 - ieeexplore.ieee.org
In-memory computing (IMC) architectures have emerged as a compelling platform to
implement energy-efficient machine learning (ML) systems. However, today, the energy …
implement energy-efficient machine learning (ML) systems. However, today, the energy …
Power-delay area-efficient processing-in-memory based on nanocrystalline Hafnia ferroelectric field-effect transistors
Ferroelectric field-effect transistors (FeFETs) have attracted enormous attention for low-
power and high-density nonvolatile memory devices in processing-in-memory (PIM) …
power and high-density nonvolatile memory devices in processing-in-memory (PIM) …
In-memory computing for machine learning and deep learning
In-memory computing (IMC) aims at executing numerical operations via physical processes,
such as current summation and charge collection, thus accelerating common computing …
such as current summation and charge collection, thus accelerating common computing …
Breakdown-limited endurance in HZO FeFETs: Mechanism and improvement under bipolar stress
Breakdown is one of main failure mechanisms that limit write endurance of ferroelectric
devices using hafnium oxide-based ferroelectric materials. In this study, we investigate the …
devices using hafnium oxide-based ferroelectric materials. In this study, we investigate the …
Ferroelectric source follower for voltage-sensing nonvolatile memory and computing-in-memory
Memory arrays and computing-in-memory architecture based on emerging nonvolatile
memory devices with a current-sensing scheme face several challenges when implemented …
memory devices with a current-sensing scheme face several challenges when implemented …
Low-power vertically stacked one time programmable multibit IGZO-based BEOL compatible ferroelectric TFT memory devices with lifelong retention for monolithic 3D …
This article demonstrates indium gallium zinc oxide-based onetime programmable
ferroelectric memory devices with multilevel coding and lifelong retention capability. The …
ferroelectric memory devices with multilevel coding and lifelong retention capability. The …