Artificial intelligence (AI) is accelerating the development of unconventional computing
paradigms inspired by the abilities and energy efficiency of the brain. The human brain …

Approaching limitations of digital computing technologies have spurred research in
neuromorphic and other unconventional approaches to computing. Here we argue that if we …

Neuromorphic computing aims at the realization of intelligent systems able to process
information similarly to our brain. Brain-inspired computing paradigms have been …

A sulfonated polyaniline (SPAN) organic electrochemical network device (OEND) is
fabricated using a simple drop‐casting method on multiple Au electrodes for use in reservoir …

Bioinspired computation systems can achieve artificial intelligence, bypassing fundamental
bottlenecks and cost constraints. Computational frameworks suited for temporal/sequential …

In-memory computing (IMC) has emerged as a new computing paradigm able to alleviate or
suppress the memory bottleneck, which is the major concern for energy efficiency and …

Abstract Nanowire Networks (NWNs) belong to an emerging class of neuromorphic systems
that exploit the unique physical properties of nanostructured materials. In addition to their …

General‐purpose computers usually use logic gate computing units based on
complementary metal oxide semiconductors (CMOS). Due to the separate memory and …

Memristive devices are able to store and process information, which offers several key
advantages over the transistor-based architectures. However, most of the two-terminal …

Neuromorphic networks are formed by random self-assembly of silver nanowires. Silver
nanowires are coated with a polymer layer after synthesis in which junctions between two …