The conventional computing architecture faces substantial challenges, including high
latency and energy consumption between memory and processing units. In response, in …

Multifunctional neuromorphic devices to tackle complex tasks are highly desirable for the
development of artificial neural networks. Threshold switching (TS) memory, which exhibits …

Neurons, which are made of biological tissue, exhibit cognitive properties that can be
replicated in various material substrates. To create brain-inspired computational artificial …

Memristive devices with threshold switching characteristics can be effectively utilized to
mimic biological neurons acting as one of the key building blocks for constructing advanced …

Rapid advancements in artificial intelligence (AI) and the Internet of Things (IoT) demand
more efficient data processing than conventional von Neumann architectures offer. In-sensor …

A fully depleted silicon‐on‐insulator (FDSOI) metal‐oxide‐semiconductor field‐effect
transistors (MOSFETs) device is investigated as for an electronic synapse emulating the …

Neuromorphic computing (NC), considered as a promising candidate for future computer
architecture, can facilitate more biomimetic intelligence while reducing energy consumption …

Employing suitable materials and device engineering is one of the crucial methods toward
the realization of multifunctional memristive devices for constructing bioinspired …

Diffusive memristors, characterized by their nonlinear dynamic conductance changes in
response to stimulations, enable effective and efficient hardware implementation of various …

The stable and threshold-friendly electrochemical-metallization-based threshold switching
(TS) memristors are promising candidates to build artificial leaky integrate-and-fire (LIF) …