[https://t.co/pmnr27KGAy] #Alibaba Announces #opensource #RISC-V-Based Xuantie Series #Processors #semi #chips #riscv https://t.co/VTIRXyYpEI

[https://t.co/pmnr27KGAy] #Alibaba Announces #opensource #RISC-V-Based Xuantie Series #Processors #semi #chips #riscv https://t.co/VTIRXyYpEI

— Wladek Grabinski (@wladek60) Oct 20, 2021

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from Twitter https://twitter.com/wladek60

October 20, 2021 at 01:36PM
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Apple Unveils New M1 Pro, Monster M1 Max SoCs

[https://t.co/rrssJ7q5A5] Apple Unveils New M1 Pro, Monster M1 Max SoCs #semiconductor #intel #apple #customsilicon #competition #leadership #semi https://t.co/9wsFqWvLXN

— Wladek Grabinski (@wladek60) Oct 19, 2021

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from Twitter https://twitter.com/wladek60

October 19, 2021 at 10:07AM
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President Macron wants #EU to double its #semi #production

Like Thierry Breton, the president Emmanuel Macron wants #EU to double its#semi  #production capacity. The #France and #Europe want to invest €6 billion and €40 billion respectively. [ @VIPress, #semiconductors, #chips] https://t.co/AzzG721WX9

— Wladek Grabinski (@wladek60) Oct 13, 2021

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from Twitter https://twitter.com/wladek60

October 13, 2021 at 01:38PM
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[paper] Parameter Extraction of Power MOSFET Models

Michihiro Shintani, Aoi Ueda and Takashi Sato

Accelerating Parameter Extraction of Power MOSFET Models Using Automatic Differentiation

IEEE Transactions on Power Electronics (2021)

DOI:  10.1109/TPEL.2021.3118057

 
Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma (J)

Graduate School of Informatics, Kyoto University (J)
 

Abstract: The extraction of the model parameters is as im- portant as the development of compact model itself because simulation accuracy is fully determined by the accuracy of the pa- rameters used. This study proposes an efficient model-parameter extraction method for compact models of power MOSFETs. The proposed method employs automatic differentiation (AD), which is extensively used for training artificial neural networks. In the proposed AD-based parameter extraction, gradient of all the model parameters is analytically calculated by forming a graph that facilitates the backward propagation of errors. Based on the calculated gradient, computationally intensive numerical differentiation is eliminated and the model parameters are efficiently optimized. Experiments are conducted to fit current and capacitance characteristics of commercially available silicon carbide MOSFET using power MOSFET models having 13 model parameters. Results demonstrated that the proposed method could successfully derive the model parameters 3.50× faster than a conventional numerical-differentiation method while achieving the equal accuracy.

Fig: Backward propagation mode. The dashed arrows indicate the path from E to SCALE.

The propagated values on the path in the backward propagation are highlighted

Acknowledgment: This work was partially supported by JST-OPERA Program Grant Number JPMJOP1841, Japan. The part of this work is also supported by JSPS KAKENHI Grant 20H04156 and 20K21793.

[paper] MEMS Sensors Reliability

M. Hommel^a, H. Knab^a, S. Galal Yousef^b

Reliability of automotive and consumer MEMS sensors - An overview

Microelectronics Reliability (114252) online Oct. 11, 2021

DOI: 10.1016/j.microrel.2021.114252

a Robert-Bosch-GmbH, Automotive Electronics, Tübinger Str. 123, 72762 Reutlingen, Germany
b Bosch Sensortec GmbH, Gerhard-Kindler-Str. 9, 72770 Reutlingen, Germany

Abstract: In our daily life, sensors play more and a more important role. They take over many functions in the automotive world as well as in consumer products with an increasing dissemination of the internet of things. In addition, they offer a broad variety of new applications. Sensors are typically build up in a package including a sensing element (e.g. micromechanical structures in acceleration sensors or membranes in gas sensors, etc.) and a microelectronic chip to evaluate the sensor data. This article will give an overview, how the reliability of such a system is validated. The challenges for reliability in terms of requirements and qualification for automotive and consumer applications will be discussed. The complex structure of a sensor module in combination with a broad variety of materials implies many possible failure mechanisms, which have to be considered. Some relevant sensor failure mechanisms caused by mechanical shock, thermo-mechanical stress and the influence of humidity on sensor reliability will be shown. The challenges for describing the influence of humidity on the sensor lifetime by an acceleration model will be discussed in detail. Finally, the paper will give an outlook for the reliability challenges of future sensor applications.

Fig: Loads on a MEMS sensor module.