Results 161 to 170 of about 3,455 (262)

Bistable Networks Enable Complex Shape Changes

open access: yesAdvanced Science, EarlyView.
Transition‐controlled metamaterials are networks of bistable mechanical memory that store local binary states and express them as global shape change. By decoupling low‐force programming from high‐force holding, a single lattice is reconfigured into distinct 2D profiles and 3D surfaces without continuous actuation, enabling reusable morphing materials ...
Sawyer Thomas, Jeffrey Lipton
wiley   +1 more source

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

People Counting and Positioning Using Low‐Resolution Infrared Images for FeFET‐Based In‐Memory Computing

open access: yesAdvanced Electronic Materials, EarlyView.
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar   +9 more
wiley   +1 more source

SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range

open access: yesAdvanced Electronic Materials, EarlyView.
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel   +6 more
wiley   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

open access: yesAdvanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez   +10 more
wiley   +1 more source

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