The discovery and control of new phases of matter is a central endeavour in materials
research. The emergence of atomically thin 2D materials, such as transition-metal …

With the need for artificial intelligence and distributed energy, to power all electronics and
sensors is becoming a major challenge. A triboelectric nanogenerator (TENG) is a …

By integrating sensing, memory and processing functionalities, biological nervous systems
are energy and area efficient. Emulating such capabilities in artificial systems is, however …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Memristor-enabled neuromorphic computing systems provide a fast and energy-efficient
approach to training neural networks,,–. However, convolutional neural networks (CNNs) …

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 …

Computer simulations can play a central role in the understanding of phase-change
materials and the development of advanced memory technologies. However, direct quantum …

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

The rapid development of neuro-inspired computing demands synaptic devices with ultrafast
speed, low power consumption, and multiple non-volatile states, among other features …

Abstract Two-dimensional (2D) layered materials are attracting a lot of attention because of
unique physicochemical properties that are intriguing for both fundamental research and …