Spiking neural networks (SNNs) sharing large similarity with biological nervous systems are
promising to process spatiotemporal information and can provide highly time‐and energy …

Neuromorphic computing powered by spiking neural networks (SNN) provides a powerful
and efficient information processing paradigm. To harvest the advantage of SNNs, compact …

The poor carrier mobility of polycrystalline Mg3Sb2 at low temperatures strongly degrades
the thermoelectric performance. Ionized impurities are initially thought to dominate charge …

The designing of novel materials is a fascinating and innovative pathway in materials
science. Particularly, novel layered compounds have tremendous influence in various …

While mixed ionic-electronic conductors with metal-insulator transition (MIT) are promising
candidates for designing neuromorphic computing hardware, the fundamentals of resistive …

For more than five decades, the flexibility of the von Neumann architecture—in which data
from discrete memory units arrive at dedicated compute units as both operations and …

Ferroelectric domain walls, agile nanoscale interfaces of polar order, can be selectively
controlled by electric fields for their position, conformation, and function, which is ultimately …

Memristors are a promising technology to surpass the limitations of the current silicon
complementary metal-oxide-semiconductor architecture via the realization of neuromorphic …

Memristors have emerged as a viable component for developing neuromorphic hardware
platforms, which can compete with biological systems in density, accuracy, and energy …

The electronic structure of the single-crystalline solid solutions Nb 1-x V x Se 2 has been
studied using soft X-ray photoelectron, resonant photoelectron, and absorption …