Results 191 to 200 of about 5,673,730 (326)
A frequency‐tunable ferroelectric synaptic transistor based on a buried‐gate InGaZnO channel and Al2O3/HfO2 dielectric stack exhibits linear and reversible weight updates using single‐polarity pulses. By switching between ferroelectric and trap‐assisted modes depending on input frequency, the device simplifies neuromorphic circuit design and achieves ...
Ojun Kwon +8 more
wiley +1 more source
Organic Electrochemical Transistors for Neuromorphic Devices and Applications
Organic electrochemical transistors are emerging as promising platforms for neuromorphic devices that emulate neuronal and synaptic activities and can seamlessly integrate with biological systems. This review focuses on resultant organic artificial neurons, synapses, and integrated devices, with an emphasis on their ability to perform neuromorphic ...
Kexin Xiang +4 more
wiley +1 more source
Ferroelectrics Hybrids: Harnessing Multifunctionality of 2D Semiconductors in the Post‐Moore Era
In this Review, the state of art of ferroelectric hybrid systems—combining ferroelectrics, 2D semiconductors, and molecular switches is presented—as next‐generation platforms for high‐density, multifunctional electronics. By discussing 2D FeFET applications, nanoscale material downscaling, M3D integration, and emerging ferroelectrics, it highlights ...
Haixin Qiu +3 more
wiley +1 more source
Intercalation‐Induced Phase Transitions in Ferroelectric α‐In2Se3
Using the electrolyte gating technique, the van der Waals ferroelectric semiconductor α‐In2Se3 undergoes a series of transitions from a ferroelectric semiconductor to a dirty metal and finally to a metal, accompanied by a structural transformation. Concurrently, the ferroelectric hysteresis window progressively narrows and eventually disappears with ...
Xin He +12 more
wiley +1 more source
Ultrahigh High‐temperature Capacitive Energy Storage Via Proton Irradiation
Proton irradiation concurrently induces enhanced dielectric constant and breakdown field in aromatic polymers with ether bonds, which enables an ultrahigh discharged energy density of 6.9 J cm−3 at above the efficiency of 95% at 150 °C, exceeding current dielectric polymers and nanocomposites.
Chenyi Li +11 more
wiley +1 more source
Poor long‐term retention of organic electrochemical transistor (OECT) artificial synapses with poly(3,4‐ethylenedioxythiophene): poly(styrene sulfonate) (PEDOT: PSS) have been a major obstacle for precise emulation of synaptic functions, mainly because of uncontrollable diffusion of mobile ions.
Minsub Lee +9 more
wiley +1 more source
Nitride Ferroelectric Domain Wall Memory for Next‐Generation Computing
In this study, a nitride ferroelectric domain wall memory (FeDMEM) device with potential for scalable integration into conventional CMOS technology is demonstrated. The novel domain wall conduction phenomena and its reflection in the memristive response of fiber‐textured Pt/Al0.72Sc0.28N(20 nm)/Pt capacitors is examined, revealing high read currents ...
Georg Schönweger +8 more
wiley +1 more source
Is There A Pure Electronic Ferroelectric?
The search for faster, more reliable ferroelectric materials has shifted from traditional lattice‐driven ferroelectrics, which rely on slow ionic displacements, to electronic ferroelectrics, where polarization is governed by electronic ordering. This shift enables ultrafast switching, low‐field operation, and resistance to fatigue.
Xudong Wang +8 more
wiley +1 more source
Research on Seismic and Self-Centering Performance of SMAF-ECC Prefabricated Self-Centering Frame Joints Based on Finite Element Simulation. [PDF]
Cao Y, Wu Q, Yang Z.
europepmc +1 more source
Designing Memristive Materials for Artificial Dynamic Intelligence
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley +1 more source

