Results 91 to 100 of about 77,589 (241)

Electrically detected magnetic resonance using radio-frequency reflectometry

, 2009
The authors demonstrate readout of electrically detected magnetic resonance at radio frequencies by means of an LCR tank circuit. Applied to a silicon field-effect transistor at milli-kelvin temperatures, this method shows a 25-fold increased signal-to ...
Ferguson, A. J., Huebl, H., McCamey, D. R., Starrett, R. P., van Beveren, L. H. Willems   +4 more
core   +2 more sources

Silicon Nitride Resistive Memories

Advanced Electronic Materials, EarlyView.
Amorphous SiNx is an attractive resistance switching material for ReRAM applications due to its physicochemical properties, such as humidity resistance, low oxygen diffusivity, and is used as a metal diffusion blocker. By modifying the ratio between N and Si atoms, the microstructure of the SiNx is affected, rendering it possible to change the ...
Alexandros‐Eleftherios Mavropoulis, Nikolaos Vasileiadis, Iosif‐Angelos Fyrigos, Emmanouil Stavroulakis, Caroline Bonafos, Pascal Normand, Georgios Ch. Sirakoulis, Panagiotis Dimitrakis   +7 more
wiley   +1 more source

Magnetotransport in dilute 2D Si-MOSFET system

, 2003
The beating pattern of Shubnikov-de Haas oscillations is reproduced in both the crossed and tilted magnetic field configuration and in presence of zero-field valley splitting in Si-MOSFET system.
M. V. CHEREMISIN, Pudalov V. M.
core   +1 more source

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

Advanced 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, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

RF performance of strained Si MODFETs and MOSFETs on "virtual" SiGe substrates: A Monte Carlo study [PDF]

, 1997
No abstract ...
Asenov, A., Babiker, S., Barker, J.R., Beaumont, S.P., Roy, S.   +4 more
core  

Spin resonance of 2D electrons in a large-area silicon MOSFET

, 2007
We report electron spin resonance (ESR) measurements on a large-area silicon MOSFET. An ESR signal at g-factor 1.9999(1), and with a linewidth of 0.6 G, is observed and found to arise from two-dimensional (2D) electrons at the Si/SiO2 interface.
A.M. Tyryshkin, Ando, Feher, Friesen, Ghosh, Graeff, Kane, Nestle, Poole, S. Avasthi, S. Shankar, S.A. Lyon, Vrijen, Wallace, Wilamowski, Wilamowski, Young   +16 more
core   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Modeling of Power Module for 48 V High Power Inverter [PDF]

Informacije MIDEM, 2021
T. Skuber, A. Sešek, J. Trontelj
doaj   +1 more source

Investigation of carrier transport in high performance Si0.73Ge0.27-OI pMOSFET through back-gate modulation

Gongneng cailiao yu qijian xuebao
In this paper, the carrier transport characteristics of a high-performance SiGe-on-insulator p-channel metal-oxide-semiconductor field-effect transistor (SiGe-OI pMOSFET) are systematically investigated using a back-gate modulation method.
Zhengyang CHEN, Choonghyun LEE, Yiming QU   +2 more
doaj   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source