The volume, veracity, variability, and velocity of data produced from the ever increasing
network of sensors connected to Internet pose challenges for power management …

In this review, a comprehensive survey of different oxide-based resistive random-access
memories (RRAMs) for neuromorphic computing is provided. We begin with the history of …

This article provides a review of current development and challenges in brain-inspired
computing with memristors. We review the mechanisms of various memristive devices that …

Neuromorphic computing is a brain-inspired computing paradigm that aims to construct
efficient, low-power, and adaptive computing systems by emulating the information …

Emerging brain-inspired architectures call for devices that can emulate the functionality of
biological synapses in order to implement new efficient computational schemes able to …

Neuromorphic computing can process large amounts of information in parallel and provides
a powerful tool to solve the von Neumann bottleneck. Constructing an artificial neural …

We investigate the emerging chemical states of TiN/HfO 2/TiN capacitors and focus
especially on the identification of vacancies and impurities in the ferroelectric HfO 2 layers …

As memristor-simulating synaptic devices have become available in recent years, the
optimization on non-linearity degree (NL, related to adjacent conductance values) is …

Flexible memristor is one of the most promising wearable devices for abundant data storage
and processing. In this work, interface engineering by inserting the Al 2 O 3 barrier layer is …

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 …