Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

Physics is a field of science that has traditionally used the scientific method to answer
questions about why natural phenomena occur and to make testable models that explain the …

Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic
chips with high energy efficiency by introducing neural dynamics and spike properties. As …

By mimicking the neurons and synapses of the human brain and employing spiking neural
networks on neuromorphic chips, neuromorphic computing offers a promising energy …

Biointegrated neuromorphic hardware holds promise for new protocols to record/regulate
signalling in biological systems. Making such artificial neural circuits successful requires …

The brain is the perfect place to look for inspiration to develop more efficient neural
networks. The inner workings of our synapses and neurons provide a glimpse at what the …

Many in-memory computing frameworks demand electronic devices with specific switching
characteristics to achieve the desired level of computational complexity. Existing memristive …

Fine-tuned ion transport across nanoscale pores is key to many biological processes,
including neurotransmission. Recent advances have enabled the confinement of water and …

It is widely believed the brain-inspired spiking neural networks have the capability of
processing temporal information owing to their dynamic attributes. However, how to …

Over the last few decades, the research on ferroelectric memories has been limited due to
their dimensional scalability and incompatibility with complementary metal‐oxide …