Results 231 to 240 of about 858,236 (306)

Millisecond‐Scale Relaxation in Metastable HZO Ferroelectric Capacitors for Bio‐Inspired Temporal Computing

open access: yesAdvanced Electronic Materials, EarlyView.
Through the introduction of a niobium oxide layer into a hafnia ferroelectric capacitor stack, we build a memory device with a strong imprint effect. This imprint leads to a millisecond retention loss that can be tuned by the programming conditions that can be utilized as a scalable, analog hardware time constant for bio‐inspired temporal computing ...
Luca Fehlings   +3 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

Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses

open access: yesAdvanced Electronic Materials, EarlyView.
Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol   +7 more
wiley   +1 more source

Nonmonotonic Enhancement of Electro‐Optic Properties of Wurtzite AlN Thin Films by Sc Doping

open access: yesAdvanced Electronic Materials, EarlyView.
EO coefficient, rc, for Sc‐AlN thin films in comparison with that for Mg ZnO thin films (left). Calculated electric field intensity of the fundamental mode supported by the active area that includes Sc‐AlN (right). ABSTRACT Wurtzite ferroelectrics, such as Sc‐doped AlN, have recently attracted considerable attention for their potential in realizing ...
K. Abe   +11 more
wiley   +1 more source

Enhanced Resistive Switching Uniformity in Tantalum Oxide Memristor Devices via Copper Implantation

open access: yesAdvanced Electronic Materials, EarlyView.
Metal oxide memristor devices typically suffer from uncontrolled forming processes and limited resistive switching uniformity due to the stochastic formation of an oxygen vacancy filament. Improved resistive switching uniformity in Ta2O5 memristor is developed by Cu implantation in the switching oxide.
Shaochuan Chen, Ilia Valov
wiley   +1 more source

Low‐Field Giant Dielectric Tunability by Polaron‐Mediated Interfacial Polarization in Pulsed‐Laser‐Deposited‐Nanocrystalline/Amorphous Composite BaTiO3 Thin Films

open access: yesAdvanced Electronic Materials, EarlyView.
Comparison of tunability efficiency between vacuum‐deposited PLD‐BTO films grown at Td = 550°C in the present study and representative previous reports. ABSTRACT Electrically tunable dielectric thin films are essential components for next‐generation low‐voltage electronic devices.
Shinya Kondo   +7 more
wiley   +1 more source

Environmental Effects on RRAM Cells Based on 2D Halide Perovskite Materials

open access: yesAdvanced Electronic Materials, EarlyView.
RRAM offers high speed, scalability, and low power, positioning it as a next‐generation non‐volatile memory. Two‐dimensional halide perovskites show promise due to tunable optoelectronic properties and flexible processing but suffer from environmental sensitivity. This review examines degradation from humidity, temperature, light, and strain, discusses
Mojtaba Joodaki   +3 more
wiley   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

open access: yesAdvanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali   +3 more
wiley   +1 more source

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