The search for alternatives to traditional Li-ion batteries has sparked interest in the chemistry
and manufacturing of solid-state Li-ion conductors. Li-ion conductors are traditionally …

The advanced progress of electronic-based devices for artificial neural networks and recent
trends in neuromorphic engineering are discussed in this review. Recent studies indicate …

Convolutional neural networks (CNNs) have been widely used in image recognition and
processing tasks. Memristor-based CNNs accumulate the advantages of emerging …

Typical filament-type memristors suffer from temporal and spatial variations in the resistive
switching due to stochastic filament formation, which hinders the implementation of …

Specialized hardware for neural networks requires materials with tunable symmetry,
retention, and speed at low power consumption. The study proposes lithium titanates …

Memristors have attracted tremendous interest in the fields of high-density memory and
neuromorphic computing. However, despite the tremendous efforts that have been devoted …

Challenges in the fields of renewable energy harvesting, data storage, and nanoelectronics
have resparked interest in ferroelectric domain walls (DWs) as tunable, nanoscale elements …

The development of memristor-based spiking neuromorphic systems (NS) has been
essentially driven by the hope to replicate the extremely high energy efficiency of biological …

The high performance requirements of nowadays computer networks are limiting their ability
to support important requirements of the future. Two important properties essential in …

Resistive and capacitive switching in capacitor metal/nanocomposite/metal (M/NC/M)
structures based on (Co-Fe-B) x (Li Nb O 3) 100− x NC fabricated by ion-beam sputtering …