[C4P] Special Issue on Advances in Sensor Devices for Biomedical Monitoring

International Journal of High Speed Electronics and Systems

ISSN (print): 0129-1564 | ISSN (online): 1793-6438

Call for Papers

Special Issue on Advances in Sensor Devices for Biomedical Monitoring

A biosensor is an analytical device, used for the detection of a chemical substance, that combines a biological component with a physicochemical detector. The sensitive biological element, e.g., tissue, microorganisms, organelles, cell receptors, enzymes, antibodies, nucleic acids, etc., is a biologically derived material or biomimetic component that interacts with, binds with, or recognizes the analyte under study. The transducer or the detector element, which transforms one signal into another one, works in a physicochemical way: optical, piezoelectric, electrochemical, electrochemiluminescence etc., resulting from the interaction of the analyte with the biological element, to easily measure and quantify. This special issue invites new strategies, innovative technologies, and algorithms to showcase the development in Sensor Devices for Biomedical Monitoring

The topic of interest includes the following:

• Biomedical sensors for Persuasive Monitoring
• Application of AI in biomedical sensor technology
• Devices embedded in Biosensors for biomedical Monitoring
• Automation in sensory devices for biomedical Monitoring
• Impact of Digitization on development of Biosensors.
• Flexible mechanics and electronic sensing devices for biomedical Monitoring
• Translucent and elastic sensors for biomedical Monitoring
• Automated Cell identification devices in biosensors for biomedical Monitoring
• Impact of Silk fibroin substrate in the development of Biosensor
• Study on Polymer electronic skin as Biosensor
• Review and comparative study in Biosensor

Important Dates:

Paper Submission Deadline: February 25, 2022

Author Notificatione: May 05, 2022

Revised Papers Submissione: July 15, 2022

Final Acceptancee: September 27, 2022

Guest Editorial Team:

Dr. Carlos Enrique Montenegro Marin

District University Francisco José de Caldas,

Bogotá, Colombia

Dr. Dinesh Jackson Samuel

Oxford Brookes University,

Oxford OX3 0BP, United Kingdom

Dr. Nallappan Gunasekaran

Shibaura Institute of Technology,

Saitama 337-8570, Japan.

[paper] MOSFET Threshold Voltage Extraction

Nikolaos Makris and Matthias Bucher (IEEE Member)

On MOSFET Threshold Voltage Extraction 

Over the Full Range of Drain Voltage Based on Gm/ID

arXiv:2106.00747v1 [physics.app-ph] 1 June 2021

Abstract: A MOSFET threshold voltage extraction method covering the entire range of drain-to-source voltage, from linear to saturation modes, is presented. Transconductance-to-current ratio is obtained from MOSFET transfer characteristics measured at low to high drain voltage. Based on the charge-based modeling approach, a near-constant value of threshold voltage is obtained over the whole range of drain voltage for ideal, long-channel MOSFETs. The method reveals a distinct increase of threshold voltage versus drain voltage for halo-implanted MOSFETs in the low drain voltage range. The method benefits from moderate inversion operation, where high-field effects, such as vertical field mobility reduction and series resistances, are minimal. The present method is applicable over the full range of drain voltage, is fully analytical, easy to be implemented, and provides more consistent results when compared to existing methods.

Fig: Extraction of threshold voltage for a long-channel MOSFET from transconductance-to-current ratio (TCR) covering linear to saturation modes. (a) GmUT /ID obtained from ID vs. VG characteristics measured at different values of VDS (long-channel n-MOSFET) together with model (b) Criterion for threshold voltage nGmUT /ID varies among two asymptotic values in linear and saturation modes.

Aknowlegements: This work was partly supported under Project INNOVATION-EL-Crete (MIS 5002772).

Related papers:

[i] T. Rudenko, V. Kilchytska, M. K. M. Arshad, J. Raskin, A. Nazarov and D. Flandre, "On the MOSFET Threshold Voltage Extraction by Transconductance and Transconductance-to-Current Ratio Change Methods: Part I—Effect of Gate-Voltage-Dependent Mobility," in IEEE Transactions on Electron Devices, vol. 58, no. 12, pp. 4172-4179, Dec. 2011.

doi: 10.1109/TED.2011.2168226

[ii] T. Rudenko, V. Kilchytska, M. K. M. Arshad, J. Raskin, A. Nazarov and D. Flandre, "On the MOSFET Threshold Voltage Extraction by Transconductance and Transconductance-to-Current Ratio Change Methods: Part II—Effect of Drain Voltage," in IEEE Transactions on Electron Devices, vol. 58, no. 12, pp. 4180-4188, Dec. 2011.

doi: 10.1109/TED.2011.2168227

[iii] T. Rudenko, V. Kilchytska, M. K. M. Arshad, J. Raskin, A. Nazarov and D. Flandre, "Influence of drain voltage on MOSFET threshold voltage determination by transconductance change and gm/Id methods," ULIS, Cork, Ireland, 2011, pp.1-4.

doi: 10.1109/ULIS.2011.5758012

[paper] JART VCM v1 Verilog-A Compact

JART VCM v1 Verilog-A Compact

Model User Guide

Christopher Bengel, David Kaihua Zhang, Rainer Waser, Stephan Menzel

Electronic Materials Research Laboratory; RWTH Aachen University
Forschungszentrum Jülich

Abstract: The JART VCM v1a model was developed to simulate the switching characteristics of ReRAM devices based on the valence change mechanism. In this model, the ionic defect concentration (oxygen vacancies) in the disc region close to the active electrode (AE) defines the resistance state. The concentration changes due to the drift of the ionic defects. Furthermore, these oxygen vacancies act as mobile donors and modulate the Schottky barrier at the AE/oxide interface. In this model, Joule heating is considered, which significantly accelerates the switching process at high current levels. Since the JART VCM v1b model represents an improvement of the JART VCM v1a model, this user guide will have its focus on the JART VCM v1b model. Here, the equivalent circuit diagram (ECD) as well as some equations have been modified to explain the switching dynamics more accurately  Based on the JART VCM v1b model, a variability model was developed, which includes both device-to-device and cycle-to-cycle variability. In terms of the device-to-device variability, the VCM cells are initiated with statistical distributed parameters: filament lengths, filament radii and maximum and minimum values for the oxygen vacancy concentration in the disc. The cycle-to-cycle variability is achieved by changing the four quantities during SET and RESET. The latest extension of the JART VCM v1b also includes RTN, which is based on statistical jumps of oxygen vacancies into and out of the disc region.

Fig: Equivalent circuit diagram of the JART VCM v1b model (a) 

along with the electrical model in Verilog-A (b).

The Verilog-A code of this model can be downloaded here (Verilog-A file).
The User Guide for this model version can be downloaded here (User Guide PDF).

[paper] Compact Modeling of Flicker Noise in HV MOSFETs

Ravi Goel (Student Member, IEEE), Yogesh Singh Chauhan (Fellow, IEEE) 

Compact Modeling of Flicker Noise in High Voltage MOSFETs and Experimental Validation 

In 2021 IEEE Latin America Electron Devices Conference (LAEDC), pp. 1-4. IEEE, 2021 

DOI: 10.1109/LAEDC51812.2021.9437922

*Department of Electrical Engineering, Indian Institute of Technology Kanpur, India

Abstract: An analytical model of flicker noise (also called 1/f or low frequency noise) for the drift region is developed to formulate a 1/f model for high voltage MOSFETs using the subcircuit approach in this work. For halo doped drain extended MOSFET (DEMOS), the contribution factors of halo, channel and drift regions are obtained to capture anomalous behavior of 1/f noise. Similar to Halo doped DEMOS, for LDMOS, the contribution factors for channel and the drift region are obtained to capture the SID for different drain biases and channel lengths. The proposed model is validated with measurement data of 50V LDMOS and DEMOS.

Fig: Halo doped DEMOS and its sub-circuit equivalent. In halo doped DEMOS, the channel is divided into halo region and channel region, followed by drift region. In LDMOS, the channel is followed by the drift region. CFsh, CFch, and CFdrift are the contribution factors and are calculated using small-signal analysis.

Acknowledgments: The authors thank Sarvesh S. Chauhan for his valuable feedback. This work was partially supported by the Swarna Jayanti Fellowship (Grant No. – DST/SJF/ETA-02/2017- 18) and FIST Scheme (Grant No. – SR/FST/ETII-072/2016) of the Department of Science and Technology, India and Berkeley Device Modeling Center (BDMC).

#top10 biggest semiconductor companies last 2020 year

#top10 biggest semiconductor companies last 2020 yearhttps://t.co/a6CXnjL3sJ #semi pic.twitter.com/19vZ2lINKc

— Wladek Grabinski (@wladek60) June 3, 2021

---

from Twitter https://twitter.com/wladek60

June 03, 2021 at 02:59PM
via IFTTT