Results 191 to 200 of about 255,384 (338)

Mason, TJ

open access: yes, 2023
Mason, TJ
core  

Non‐Uniform Space‐Time‐Coding Modulation for Low‐Complexity Diagnostics of Reconfigurable Intelligent Surfaces

open access: yesAdvanced Electronic Materials, EarlyView.
A diagnostic method for reconfigurable intelligent surfaces (RIS) based on non‐uniform space‐time‐coding modulation is presented. Fault localization is achieved via amplitude‐only spectral measurements, eliminating the need for complex signal processing. A one‐to‐one mapping between harmonic components and RIS elements enables accurate detection.
Xiao Qing Chen   +8 more
wiley   +1 more source

Collisionless damping of flows in the TJ-II stellarator

open access: yes, 2012
E. Sánchez   +11 more
semanticscholar   +1 more source

A Compendium of Logic Gates Based on Reconfigurable Three‐Independent‐Gate Transistors Realized in FDSOI Hardware

open access: yesAdvanced Electronic Materials, EarlyView.
This work electrically characterizes sixteen logic gates built from three‐independent‐gate reconfigurable transistors fabricated on full‐scale 300 mm wafers using the industrial 22 nm fully depleted FDSOI process of GlobalFoundries. Static and time‐resolved measurements confirm correct operation, including a 1‐bit adder and reconfigurable AOI/OAI ...
Juan P. Martinez   +12 more
wiley   +1 more source

Embedded Direct‐Written Organic Micro‐TEGs for High‐Efficiency Skin‐Heat Harvesting

open access: yesAdvanced Electronic Materials, EarlyView.
A finite‐element–guided design of direct‐written organic micro‐thermoelectric generators is presented for efficient skin‐heat harvesting. Embedding PEDOT:PSS/PBFDO thermoelectric legs within flexible substrates suppresses interfacial heat losses and enhances vertical heat flow.
Milad Jabri   +4 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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