Si2 VAMPyRE: compact model parser and checker

Si2 #Compact #Model #Coalition Offers VAMPyRE, the software is a standalone compact model parser and checker written in Python, to Members and Developers https://t.co/vPQWlcQ99l pic.twitter.com/gbUq5nBFOA

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[tutorial] next generation 3D nano device simulator

Single-electron transistor - laterally defined quantum dot - 3D Tutorial

Stefan Birner

https://www.nextnano.com

Single-electron transistor - laterally defined quantum dot In this tutorial, we simulate an AlGaAs/GaAs heterostructure grown along the z direction. This structure leads to a two-dimensional electron gas (2DEG). By appying a gate voltage on top of the structure in the (x,y) plane, one is able to deplete the 2DEG and a laterally defined QD is formed. By adjusting the gate voltage, one is able to tune the number of electrons that are inside the QD.

This figure shows the conduction band edge Ec(x,y) and the electron density n(x,y) for the 2DEG plane, i.e. at z = 8 nm below the GaAs/AlGaAs heterojuntion. The geometry of the top gates is indicated by the blue regions. The following figure shows the calculated conduction band edge and the electron density of the heterostructure. The results are similar to Fig. 4 in paper [1].

The following figure shows two 2D slices through the lateral (x,y) plane at a distance of 8 nm below the AlGaAs/GaAs interface. In the middle, the electron density is shown. The electron density has been calculated classically. At the bottom, the conduction band edge is shown. The results are similar to Fig. 5 in paper [1]. At the top, the four gates are shown.

REF:

[1] A. Scholze, A. Schenk, W. Fichtner; Single-Electron Device Simulation; IEEE TED 47, 1811 (2000)

[paper] OTFTs in Mechanical Sensors

Organic Thin Film Transistors in Mechanical Sensors 

Zachary A. Lamport, Marco Roberto Cavallari^2,3, Kevin A. Kam, 

Christine K. McGinn, Caroline Yu, and Ioannis Kymissis

DOI: 10.1002/adfm.202004700

¹Department of Electrical Engineering, Columbia University, USA
²Departamento de Engenharia de Sistemas Eletrônicos, EPU de São Paulo, Brazil
³Department of Renewable Energies. UNILA, Brazil

Abstract: The marriage of organic thin-film transistors (OTFTs) and flexible mechanical sensors has enabled previously restricted applications to become a reality. Counterintuitively, the addition of an OTFT at each sensing element can reduce the overall complexity so that large-area, low-noise sensors can be fabricated. The best-performing instance of this is the active matrix, used in display applications for many of the same reasons, and nearly any type of flexible mechanical sensor can be incorporated into these structures. In this Progress Report, some of the flexible sensor devices that have taken advantage of these mechanical properties are highlighted, examining the advantages that OTFTs offer in the hybrid integration of local amplification and switching. In particular, the current research on resistive pressure sensors, capacitive pressure sensors, resistive or piezoresistive strain sensors, and piezoelectric sensors is identified and enumerated.

Fig: Suspended-gate FET: a) Schematic illustration of device geometry; b) electrical equivalent circuit; c) pressure response of ID at constant VDS = VGS = −60 V

Acknowledgements C.M. received funding from the National Science Foundation Graduate Research Fellowship Program (DGE—1644869). Z.L. thanks Corning and the NSF under STTR 1914013 for financial support.

[paper] Memristors in SPICE

Modeling networks of probabilistic memristors in SPICE

Vincent J. Dowling¹, Valeriy A. Slipko², Yuriy V. Pershin¹

arXiv:2009.05189v1 [cs.ET] 11 Sep 2020

DOI: 10.13164/re.2020.0001

¹Department of Physics and Astronomy, University of South Carolina, Columbia, SC 29208 USA
²Institute of Physics, Opole University, Opole 45-052, Poland

Abstract. Efficient simulation of probabilistic memristors and their networks requires novel modeling approaches. One major departure from the conventional memristor modeling is based on a master equation for the occupation probabilities of network states. In the present article, we show how to implement such master equations in SPICE. In the case studies, we simulate the dynamics of ac-driven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice codes are included.

Fig: Ac-driven probabilistic binary memristor: (a) simulated circuit, (b) schematics of SPICE model, and (c) example of current-voltage curves found with SPICE simulations. The listing of SPICE model is given in Apendix.

Appendix: SPICE code examples

B1 0 p0 I=-gm(tau01,V01,V(Va))*V(p0)*u(V(Va))+gm(tau10,V10,-V(Va))*V(p1)*u(-V(Va))

B2 0 p1 I=gm(tau01,V01,V(Va))*V(p0)**u(V(Va))-gm(tau10,V10,-V(Va))*V(p1)**u(-V(Va))

C1 p0 0 1 IC=1

C2 p1 0 1 IC=.0

R2 Va 0 1k

R1 Va 0 10k

R3 VI 0 1k

B3 0 VI I=I(R1)*V(p0)+I(R2)*V(p1)

V1 Va 0 SINE(0 1 200 0 0 0 0)

.FUNC gm(x,y,z)1/(x*exp(-z/y))

.param tau01=3E5 V01=.05

.param tau10=3E5 V10=.05

.tran 0 .1 0.05 10E-7

.backanno

.end

[paper] Co-designing electronics with microfluidics

Remco van Erp, Reza Soleimanzadeh, Luca Nela, Georgios Kampitsis & Elison Matioli; Co-designing electronics with microfluidics for more sustainable cooling. Nature 585, 211–216 (2020). DOI: 10.1038/s41586-020-2666-1 https://t.co/WQ3ddWLuqp #paper pic.twitter.com/gqt3iVegwp

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