Owing to its close resemblance to biological systems and materials, soft matter has been
successfully implemented in numerous bioelectronic and biosensing applications, as well as …

Ion migration as well as electron transfer and coupling in resistive switching materials
endow memristors with a physically tunable conductance to resemble synapses, neurons …

Brain-inspired computing hardware aims to emulate the structure and working principles of
the brain and could be used to address current limitations in artificial intelligence …

In-memory computing provides an opportunity to meet the growing demands of large data-
driven applications such as machine learning, by colocating logic operations and data …

Memristors, promising nanoelectronic devices with in-memory resistive switching behavior
that is assembled with a physically integrated core processing unit (CPU) and memory unit …

High‐performance organic neuromorphic devices with miniaturized device size and
computing capability are essential elements for developing brain‐inspired humanoid …

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 …

The growth of machine learning, combined with the approaching limits of conventional
digital computing, are driving a search for alternative and complementary forms of …

Photonic in-memory computing exhibits promising potential to address the inherent
limitations of traditional von Neumann architecture. In this study, we demonstrate a tantalum …

During the release and propagation of intracellular and extracellular ions, electromagnetic
field is induced accompanying with propagation of energy flow. The firing mode is …