Sep 21, 2020

[paper] OTFTs in Mechanical Sensors

Organic Thin Film Transistors in Mechanical Sensors 
Zachary A. Lamport, Marco Roberto Cavallari2,3, 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

Sep 18, 2020

[paper] Co-designing electronics with microfluidics


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Sep 17, 2020

[paper] Compact Model for MoS2 FETs

A physics-based compact model for MoS2 field-effect transistors
considering the band-tail effect and contact resistance
Yuan Liu1, Jiawei Zeng2, Zeqi Zhu1, Xiao Dong2 and WanLing Deng3
Japan Society of Applied Physics; Accepted Manuscript online 11 September 2020
1Guangdong University of Technology, Guangzhou, Guangdong, CHINA
2Jinan University, Guangzhou, Guangdong, CHINA
3Electronic Engineering, Jinan University, Guangzhou, GuangDong, 510630, CHINA

Abstract: In this paper, we present a compact surface-potential-based drain current model in molybdenum disulfide (MoS2) field-effect transistors (FETs). Considering variable range hopping (VRH) transport via band-tail states in MoS2 transistors, an explicit solution for surface potential has been derived and it provides a good description over different regions of operation by comparisons with numerical data. Based on charge-sheet model (CSM) which applies to drift-diffusion transport, the current expression including contact resistance and velocity saturation effect is developed. Furthermore, the presented model is validated and shows a good agreement with experiment data for MoS2 FETs. Keywords: molybdenum disulfide (MoS2), surface potential, current expression.


Fwd: September 2020 Newsletter: Planet-Scale Processing of Silicates

September 2020 Newsletter: Planet-Scale Processing of Silicates
In the eastern Sierra Nevada mountains, near Mammoth Lakes, California, is a geological phenomenon: a cliffside lined with thousands of 10-20 meter tall pillars of basalt. The organized rock columns are so incongruous with the surrounding high altitude pine forest that they seem supernatural. Shepherds who frequented the area in the 1800's named it the "Devil's Woodpile." Today, it's a popular park called the Devils Postpile National Monument.

To a MEMS engineer, this odd rock cliff bears a striking resemblance to
the columnar grains in thin film PZT or ZnO. What a mind bender to see
familiar shapes from SEM images towering overhead.

Like PZT or ZnO, a special set of environmental conditions created the Devils Postpile. It was not, however, the result of grain growth; instead, the Postpile formed from a pool of lava which then cracked into a network of polygons as it cooled. (More like misprocessed thick photoresist!)
A scale factor of 20 million: PZT with columnar grains (top)
compared to basalt columns (bottom).
On top of the Devils Postpile, one particular area has a smooth surface
which reveals the cross-sections of the polygonal columns, 50-100 cm in width. This most unusual stone patio was formed by the water, pressure, and motion of a passing Ice Age glacier, a massive-scale version of chemical mechanical polishing (CMP). Basalt rock is primarily composed of SiO2 (45-52% by weight) and other metal oxides, such as TiO2, Al2O3 and MgO; all familiar MEMS materials, just in a much larger format.
Ancient CMP: cross-section of basalt columns, polished flat
by a glacier. Note the fine lines that were created by
grit trapped in the moving glacier.
Four kilometers from the Postpile is the stunning 30 meter tall Rainbow 
Falls, etched through two layers of volcanic rock. The top masking layer
of rock is harder than the thick underlayer of softer rhyodacite. Water
pouring over the edge erodes the soft rock at a faster rate, leaving a
re-entrant cliff face and thereby creating a beautiful waterfall.

An idle thought while hiking on a hot summer day: Is geology just a
planet-scale version of MEMS processes?
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