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 …

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 …

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

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

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 …

Ferroelectric materials are promising candidates for synaptic weight elements in neural
network hardware because of their nonvolatile multilevel memory effect. This feature is …

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

Biomimetic eyes, with their excellent imaging functions such as large fields of view and low
aberrations, have shown great potentials in the fields of visual prostheses and robotics …

The global demand for data storage and processing is increasing exponentially. To deal
with this challenge, massive efforts have been devoted to the development of advanced …