[paper] SPICE Modeling of Cycle-to-Cycle Variability in RRAM Devices

E.Salvador^a, M.B.Gonzalez^b, F.Campabadal^b, J.Martin-Martinez^a, R.Rodriguez^a, E.Miranda^a

SPICE Modeling of Cycle-to-Cycle Variability in RRAM Devices

Solid-State Electronics; In Press, Journal Pre-proof

Available online 29 May 2021, 108040

DOI: 10.1016/j.sse.2021.108040

a) Departament d’Enginyeria Electrònica, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Valles, Spain
b) Institut de Microelectrònica de Barcelona, IMB-CNM, CSIC, 08193 Cerdanyola del Valles, Spain

Abstract: In this work, we investigated how to include uncorrelated cycle-to-cycle (C2C) variability in the LTSpice quasi-static memdiode model for RRAM devices. Variability in the I-V curves is first addressed through an in-depth study of the experimental data using the FITDISTRPLUS package for the R language. This provides a first approximation to the identification of the most suitable model parameter distributions. Next, the selected candidate distributions are incorporated into the model script and used for carrying out Monte Carlo simulations. Finally, the experimental and simulated observables (set and reset currents, transition voltages, etc.) are statistically compared and the model estimands recalculated if it is necessary. Here, we put special emphasis on describing the main difficulties behind this seemingly simple procedure.

Figure 4. Comparison of experimental and simulated parameter distributions: 

a) IHRS, b) VT, c) ILRS, and d) VR.

Acknowledgements: This work was supported by the Spanish Ministry of Science, Innovation and Universities through projects TEC2017-84321-C4-1-R, TEC2017-84321-C4-4-R, and PID2019-103869RB-C32.

The U.S. Senate passed a bill offering $52 billion to bolster domestic #chip #semi manufacturing

The U.S. Senate passed a bill offering $52 billion to bolster domestic #chip #semi manufacturing. (Bloomberg) https://t.co/6FQEoWMVY1 https://t.co/27tHbbiYhQ

— Wladek Grabinski (@wladek60) Jun 10, 2021

---

from Twitter https://twitter.com/wladek60

June 10, 2021 at 03:47PM
via IFTTT

[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).