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

Quantum effects in novel functional materials and new device concepts represent a potential
breakthrough for the development of new information processing technologies based on …

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 …

The booming development of artificial intelligence (AI) requires faster physical processing
units as well as more efficient algorithms. Recently, reservoir computing (RC) has emerged …

Current efforts to achieve neuromorphic computation are focused on highly organized
architectures, such as integrated circuits and regular arrays of memristors, which lack the …

Nanowire networks represent a unique class of neuromorphic systems. Their self-assembly
confers a complex structure to their network circuitry, embedding a higher interconnectivity of …

The imitative modelling of processes in the brain of living beings is an ambitious task.
However, advances in the complexity of existing hardware brain models are limited by their …

Self-assembled networks of nanoparticles and nanowires have recently emerged as
promising systems for brain-like computation. Here, we focus on percolating networks of …

A Ag2S-island network is fabricated with surrounding electrodes to enable it to be used as a
reservoir for unconventional computing. Local conductance change occurs due to the …

Neurobiology‐inspired phenomena such as winner‐takes‐all competition and critical
dynamics have been recently reported to arise in neuromorphic nanowire networks. These …