Memristive devices, which combine a resistor with memory functions such that voltage
pulses can change their resistance (and hence their memory state) in a nonvolatile manner …

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

The rapid increase in information in the big-data era calls for changes to information-
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …

Due to the voltage driven switching at low voltages combined with nonvolatility of the
achieved polarization state, ferroelectric materials have a unique potential for low power …

The artificial nervous system proves the great potential for the emulation of complex neural
signal transduction. However, a more bionic system design for bio‐signal transduction still …

Artificial synapses can boost neuromorphic computing to overcome the inherent limitations
of von Neumann architecture. As a promising memristor candidate, ferroelectric tunnel …

An urgent need for early detection and diagnosis of diseases continuously pushes the
advancements of imaging modalities and contrast agents. Current challenges remain for fast …

Neuromorphic computing is a brain-inspired computing paradigm that aims to construct
efficient, low-power, and adaptive computing systems by emulating the information …

Deep learning has become ubiquitous, touching daily lives across the globe. Today,
traditional computer architectures are stressed to their limits in efficiently executing the …

Nonvolatile memories are in strong demand due to the desire for miniaturization, high-speed
storage, and low energy consumption to fulfill the rapid developments of big data, the …