Results 191 to 200 of about 18,384 (300)

Elasto-magnetic instabilities for amplified actuation and mechanical memory. [PDF]

open access: yesNat Commun
Choi SY   +8 more
europepmc   +1 more source

Efficient Codes for Multilevel Flash Memories

open access: yes, 2014
C. VARANASI, TALLINI, Luca, B. BOSE
core  

Robust and Compatible Ferroelectric Memories with Polycrystalline TiO2 Channel for 3D Integration

open access: yesAdvanced Electronic Materials, EarlyView.
Robust and monolithic 3D compatible ferroelectric memories are realized using the polycrystalline TiO2 channel‐based FeFET. The review covers physical mechanisms of the TiO2 channel FeFET, quantitative benchmarking, and advanced planar/vertical architectures for monolithic 3D integration based on HfO2‐TiO2 gate stack, offering a roadmap for reliable ...
Xujin Song   +10 more
wiley   +1 more source

Strategy of programming applications using non-volatile memories and non-volatile memory library

open access: yesScientific Papers of Silesian University of Technology. Organization and Management Series, 2017
Hubert ŁOPUSIŃSKI   +2 more
openaire   +1 more source

Model‐Based Time‐Modulated Write Algorithm for 1R Analog Memristive Crossbar Arrays

open access: yesAdvanced Electronic Materials, EarlyView.
A novel model‐based time‐modulated write algorithm efficiently programs analog 1R memristive crossbar arrays by varying pulse duration at a fixed voltage. By leveraging a physics‐based compact model and a dynamic gain mechanism, this approach overcomes device nonlinearities and parasitic effects.
Richard Schroedter   +7 more
wiley   +1 more source

Non‐Destructive, Reference‐Free Quantitative Analysis of TaOx Memristive Devices Using Soft X‐Ray Radiation

open access: yesAdvanced Electronic Materials, EarlyView.
A non‐destructive, quantitative approach has been developed to explore the nanoscale dynamics of TaOx‐based memristive devices. The utilization of nano‐X‐ray fluorescence analysis enables the direct probing of spatially resolved elemental distributions, including those present in buried layers, that are critical for the resistive switching.
André Wählisch   +9 more
wiley   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

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