Related papers: A Dual-Memory Ferroelectric Transistor Emulating S…
We report the fabrication and testing, at 4.2 K, of an SISFS device, where S, F, and I denote a superconductor (Nb), a ferromagnetic material (permalloy), and an insulator (AlOx), respectively. The F layer covers about one half of the top…
Memristors are emerging as key electronic components that retain resistance states without power. Their non-volatile nature and ability to mimic synaptic behavior make them ideal for next-generation memory technologies and neuromorphic…
Physical reservoir computing is a computational framework that implements spatiotemporal information processing directly within physical systems. By exciting nonlinear dynamical systems and creating linear models from their state, we can…
Optical memristors represent a monumental leap in the fusion of photonics and electronics, heralding a new era of applications from neuromorphic computing to artificial intelligence. However, current technologies are hindered by complex…
We analyzed micrometer-scale titanium-niobium-oxide prototype memristors, which exhibited low write-power (<3 {\mu}W) and energy (<200 fJ/bit/{\mu}m2), low read-power (~nW), and high endurance (>millions of cycles). To understand their…
RRAM-based in-Memory Computing is an exciting road for implementing highly energy efficient neural networks. This vision is however challenged by RRAM variability, as the efficient implementation of in-memory computing does not allow error…
Ferroelectric-based capacitive crossbar arrays have been proposed for energy-efficient in-memory computing in the charge domain. They combat the challenges like sneak paths and high static power faced by resistive crossbar arrays but are…
Information technologies require entangling data stability with encryption for a next generation of secure data storage. Current magnetic memories, ranging from low-density stripes up to high-density hard drives, can ultimately be detected…
Brain-inspired computing aims to mimic cognitive functions like associative memory, the ability to recall complete patterns from partial cues. Memristor technology offers promising hardware for such neuromorphic systems due to its potential…
Ferroelectric tunneling junctions (FTJ) are considered to be the intrinsically most energy efficient memristors. In this work, specific electrical features of ferroelectric hafnium-zirconium oxide based FTJ devices are investigated.…
The operation of a novel nonvolatile memory device based on a conductive ferroelectric/non-ferroelectric thin film multilayer stack is simulated numerically. The simulation involves the self-consistent steady state solution of Poisson's…
The rising energy demands of conventional AI systems underscore the need for efficient computing technologies like brain-inspired computing. Physical reservoir computing (PRC), leveraging the nonlinear dynamics of physical systems for…
The emergence of resistive non-volatile memories opens the way to highly energy-efficient computation near- or in-memory. However, this type of computation is not compatible with conventional ECC, and has to deal with device unreliability.…
Ferroelectric non-volatile capacitance-based memories enable non-destructive readout and low-power in-memory computing with 3D stacking potential. However, their limited memory window (1-10 fF/{\mu}m) requires material-device-circuit…
In-memory computing on a reconfigurable architecture is the emerging field which performs an application-based resource allocation for computational efficiency and energy optimization. In this work, we propose a Ferroelectric…
In this paper, we demonstrate low-thermal-budget ferroelectric field-effect transistors (FeFETs) based on two-dimensional ferroelectric CuInP2S6 (CIPS) and oxide semiconductor InZnO (IZO). The CIPS/IZO FeFETs exhibit non-volatile memory…
Over the past decades, the relentless scaling and mass production of flash memory have underpinned the data-centric era. Yet charge-trap-based 3D NAND flash is now constrained by intrinsic physical and architectural limits, including…
With the ever-increasing energy need to process big data, the realization of low-power computing technologies, such as superconducting logic and memories, has become a pressing issue. Developing fast and non-volatile superconducting memory…
Hierarchical temporal memory (HTM) tries to mimic the computing in cerebral-neocortex. It identifies spatial and temporal patterns in the input for making inferences. This may require large number of computationally expensive tasks like,…
The multiple ferroelectric polarization tuned by external electric field could be used to simulate the biological synaptic weight. Ferroelectric synaptic devices have two advantages compared with other reported ones: One is the intrinsic…