A continuous exponential rise has been observed in the storage and processing of the data
that may not curtail in the foreseeable future. The required data processing speed and …

Development of unconventional computing architectures, including neuromorphic
computing, relies heavily on novel devices with properly engineered properties. This …

In‐memory computing, particularly neuromorphic computing, has emerged as a promising
solution to overcome the energy and time‐consuming challenges associated with the von …

The finding of the robust ferroelectricity in HfO 2-based thin films is fantastic from the view
point of both the fundamentals and the applications. In this review article, the current …

Neuro-inspired deep learning algorithms have shown promising futures in artificial
intelligence. Despite the remarkable progress in software-based neural networks, the …

This letter reports multi-level-cell (MLC) operation of ferroelectric FETs (FeFET) arranged in
AND-connected memory arrays with a bit-error rate (BER) of 4% when writing a random data …

In this article, we develop a Verilog-A implementable compact model for the dynamic
switching of ferroelectric FinFETs (Fe-FinFETs) for asymmetric nonperiodic input signals. We …

Nanoelectronic devices emulating neuro-synaptic functionalities through their intrinsic
physics at low operating energies are imperative toward the realization of brain-like …

Convolutional neural networks (CNNs) have become the state-of-the-art tool for image
classification, object detection, and segmentation. The max-pooling layer in the CNN …

Doped HfO2-based ferroelectric field-effect transistor (FeFET) is being actively explored as
an emerging nonvolatile memory device with the potential for in-memory computing. In this …