Synapses are essential for the transmission of neural signals. Synaptic plasticity allows for
changes in synaptic strength, enabling the brain to learn from experience. With the rapid …

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

Mimicking biological synapses with microelectronic devices is widely considered as the first
step in hardware building artificial neuromorphic networks, which is also the basis of brain …

Neuromorphic computing based on memristors capable of in-memory computing is
promising to break the energy and efficiency bottleneck of well-known von Neumann …

Multi-terminal memristor and memtransistor (MT-MEMs) has successfully performed
complex functions of heterosynaptic plasticity in synapse. However, theses MT-MEMs lack …

Ferroelectric tunnel junctions (FTJs) have been regarded as one of the most promising
candidates for next-generation devices for data storage and neuromorphic computing owing …

Recently, neuromorphic computing has been proposed to overcome the drawbacks of the
current von Neumann computing architecture. Especially, spiking neural network (SNN) has …

Electrolyte‐gated transistors (EGTs) have been extensively studied as a next‐generation
neuromorphic device mimicking the biological ionic flux in synapses. However, its long‐term …

With the advent of post-Moore era, the development of memory devices based on bulk
materials gradually entered the bottleneck period. Two-dimensional (2D) materials have …

Advances in large‐area and high‐quality 2D transition metal dichalcogenides (TMDCs)
growth are essential for semiconductor applications. Here, the gas‐phase alkali metal …