Results 91 to 100 of about 12,413 (305)

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

open access: yesAdvanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen   +7 more
wiley   +1 more source

AlGaN/GaN Heterostructures in High Electron Mobility Transistors [PDF]

open access: yes, 2018
AlGaN/GaN heterostructures are of high research and industrial interest for the production of high electron mobility transistors (HEMT) utilizing the two-dimensional electron gas (2DEG) induced at the interface due to polarization effects. In the current work, the effect of AlGaN thickness on 2DEG formation is under discussion. In particular, ultrathin
Caban, P.   +4 more
openaire   +1 more source

AlGaN based high electron mobility transistors

open access: yes, 2023
High electron mobility AlGaN/GaN have been successfully grown on low cost and high challenges AlN/Si substrates. By inserting a thin SiN layer between GaN and AlN to improve the quality of GaN, the result showed that the thin SiN layer could greatly increase the mobility of the two- dimensional electron gas formed at the interface of AlGaN and GaN ...
openaire   +2 more sources

Zero-field spin splitting in In0.52Al0.48As/InxGa1-xAs metamorphic high-electron-mobility-transistor structures on GaAs substrates using Shubnikov-de Haas measurements

open access: yes, 2002
Shubnikov-de Haas measurements were carried out for In0.52Al0.48As/InxGa1-xAs metamorphic high-electron-mobility-transistor structures grown on GaAs substrates with different indium contents and/or different Si delta-doping concentrations. Zero-field (B--
Cui LJ   +8 more
core  

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

open access: yesAdvanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung   +9 more
wiley   +1 more source

InP High-electron-mobility Transistors [PDF]

open access: yes, 2021
Isabel Harrysson Rodrigues   +1 more
openaire   +1 more source

Self-consistent analysis of AlSb/InAs high electron mobility transistor structures

open access: yes, 2010
The influences of channel layer width, spacer layer width, and delta-doping density on the electron density and its distribution in the AlSb/InAs high electron mobility transistors (HEMTs) have been studied based on the self-consistent calculation of the
ypzeng@semi.ac.cn   +4 more
core  

FinHEMT: FinFET-based High Electron Mobility Transistor with Strained Silicon Channel

open access: yes, 2015
We report a novel FinFET-based high electron mobility transistor (FinHEMT) with a strained-silicon (s-Si) channel proposed by a simple Si-compatible fabrication process. Through TCAD device simulation, proposed FinHEMT can be used as high-performance low-
Sung-Ho Kim   +5 more
core   +1 more source

180nm metal gate, high-k dielectric, implant-free III--V MOSFETs with transconductance of over 425 μS/μm [PDF]

open access: yes, 2007
: Data is reported from 180 nm gate length GaAs n-MOSFETs with drive current (Ids,sat) of 386 μA/μm (Vg=Vd =1.5 V), extrinsic transconductance (gm) of 426 μS/μm, gate leakage ( jg,limit) of 44 nA/cm2, and on resistance (Ron) of 1640 Ω μm. The gm and Ron
Moran, D.A.J.   +8 more
core   +1 more source

Ferroelectric Dynamic‐Field‐Driven Nucleation and Growth Model for Predictive Materials‐To‐Circuit Co‐Design

open access: yesAdvanced Materials, EarlyView.
This study presents a compact dynamic‐field‐driven nucleation and growth (DFNG) model that captures ferroelectric switching behavior under arbitrary voltage waveforms. It enables extraction of time‐dependent domain wall velocity and growth dimensionality, which can then be extended to device‐level modeling.
Yi Liang   +10 more
wiley   +1 more source

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