Call for Chapters

Title: Sub-Micron Semiconductor Devices: Design and Applications

Introduction: To follow Moore’s law, semiconductor devices are scaled-down without compromising the performance. Semiconductor devices are supposed to be reduced in dimensions and work at lower operating biases but the problem arises during the manufacturing of the devices. Thus, it is a dire necessity to opt for a solution that can help in continuing the path of performance improvement. Steady performance enhancement using optimization techniques can support the time required for advancements in fabrication technologies. This publication confines the novel semiconductor devices, issues with conventional devices, optimization techniques and solutions for the performance enhancement. Even with the presence of a vast amount of data regarding semiconductor devices, it is hard for a researcher to go through most of the recent advancements altogether and understand them in a clear way. The motive behind the book is to comprehensibly present the material related to the recent advancements in the field of semiconductor devices that can allow the reader to interpret the possible concepts behind the content. The study of novel semiconductor devices may help in unraveling the mystery behind the problems that are required to tackle during the fabrication of molecular devices.

Topics: [Not limited to the given topics but relevant topics will be considered as well]

• Basic of Scaled-Down Devices
• (Nano-FET, TFET, LED, Solar Cell, TFT, HEMT, Diodes, RTDs, Photodiode, Quantum-Dots, Spin-FET, etc.)
• Comparative Study of Novel Semiconductor Devices
• Inclusion of Quantum Effects in Nano-Devices
• (Short Channel Effects, Fermi-Level-Pinning, Quantum Confinement, Discrete DOS, etc.)
• Device Modelling and Physics
• (Analytical, Compact, NEGF, Quantum, Verilog, Spice, etc.)
• Novel Materials for Devices
• (Graphene, Silicene, TMDCs, Organic, Perovskite, 2D Materials, TCO, Photo-dielectric, etc.)
• Characterization and Fabrication
• (Spectroscopic, Microscopic, MBE, CVD, Spin-Coating, Defects, etc.)
• Optimization Techniques
• (Negative Capacitance, Feedback, Gate-on-Source, Dopingless, 2DEG, Schottky Contact, etc.)
• Testing of Semiconductor Devices
• Applications
• (Biosensor, Radiation Sensor, Light Sensor, Analog/Digital Circuit Applications, MEMS, etc.)
• Issues and Solutions of Novel devices
• Future Device Technology

Important Dates (Updated):

Chapter Proposal Submission: 10 September 2020 Notification of Acceptance: 15 September 2020 Full Chapter Submission: 25 October 2020

Review Result Returned: 30 October 2020 Final Acceptance: 10 November 2020 Publication of Book: January-February 2021

Submission:

Kindly submit the chapter proposal [Tittle, Abstract (500-1000 words), Possible Content, Author details] before the due date via E-mail at call.chapters.crc@gmail.com. Any kind of query regarding the chapter or abstract submission, formatting and corrections can be submitted to query.chapters.crc@gmail.com

Editors:

Ashish Raman¹, Deep Shekhar² and Naveen Kumar³

Electronics and Communication Engineering Department, Dr. B. R. Ambedkar National Institute of Technology Jalandhar, [Grand Trunk Road, Barnala - Amritsar Bypass Rd, Jalandhar, India 144011] 

Official E-mail IDs: ¹ ramana@nitj.ac.in, ² deeps.ec.18@nitj.ac.in, ³ naveenk.ec.16@nitj.ac.in

[chapter] Design of FET Biosensors

Khuraijam Nelson Singh¹ and Pranab Kishore Dutta¹

Chapter 8: Analytical Design of FET-Based Biosensors

in Advanced VLSI Design and Testability Issues; Eds: Suman Lata et all.

CRC Press, 19 Aug 2020; 360 pages

¹NERIST, Arunachal Pradesh, India

Abstract: Research on biosensors has seized the interested researchers over the past few decades due to their various advantages and applications. They are used in the discovery of drugs, monitoring of diseases, agriculture, food quality control, industrial wastage monitoring, military, etc. The sensing analyte is the main element that differentiates a biosensor from the other physical/chemical sensors. In general, the biosensor is a device that is used to detect an analyte using a biosensitive receptor. Its main components are as follows:

• Analytes: The substance that is intended to be detected, such as glucose in a glucose sensor, ammonia in ammonia sensor, and so on.
• Bioreceptors: The bioreceptors are biosensitive elements used to detect target analytelbiomolecule. They are sensitive to the analytes of interest. Some examples of bioreceptors are antigen, DNA, enzyme, and so on.
• Transducers: The elements that are used to convert energy from one form to another are called transducers. In a biosensor, the interaction of analytes and bioreceptors produces changes in the form of heat, gas, light, ions, or electrons. These changes are then converted into a quantif‌iable form by the transducer. Usually, the output of the transducer is in the form of electrical or optical signals, and the generated signal is proportional to the interaction between the analyte and the biosensor.

FIG: Schematic diagram of ion-sensitive f‌ield-effect transistor (ISFET)

[paper] GCC Method for Determining MOSFET VTH

Matthias Bucher¹, Nikolaos Makris¹, Loukas Chevas¹

Generalized Constant Current Method for Determining MOSFET Threshold Voltage

arXiv:2008.00576v1 (2 Aug 202) 

has been submitted to the IEEE for possible publication

¹ School of Electrical and Computer Engineering, Technical University of Crete

Abstract: A novel method for extracting threshold voltage (VTH) and substrate effect parameters of MOSFETs with constant current bias at all levels of inversion is presented. This generalized constant-current (GCC) method exploits the charge-based model of MOSFETs to extract threshold voltage and other substrate-effect related parameters. The method is applicable over a wide range of current throughout weak and moderate inversion and to some extent in strong inversion. This method is particularly useful when applied for MOSFETs presenting edge conduction effect (subthreshold hump) in CMOS processes using Shallow Trench Isolation (STI).

Fig:  Application of the GCC method in presence of edge conduction phenomenon in STI MOSFETs. A constant current is applied to determine pinchoff voltage for the center transistor in moderate inversion at IC=2. To characterize the edge transistor, imposing a current criterion IC=1E−4 corresponds to ICe≈0.02. Pinchoff voltage (VP) and slope factor n characteristics illustrate the determination of parameters for center and edge transistors.

Acknowledgment: This work was partly supported under Project INNOVATION-EL-Crete

(MIS 5002772).

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[paper] Macromodels for MEMS Switches

Aurel-Sorin Lup¹, Gabriela Ciuprina¹, Daniel Ioan¹ and Anton Duca¹

and Alexandra Nicoloiu² and Dan Vasilache²

Physics-aware macromodels for MEMS switches

COMPEL International Journal (2020)

¹DEE Politehnica, Uni. Bucharest, (R)

²IMT-Bucharest, Bucharest (R)

Abstract: The purpose of this paper is to propose a physics-aware algorithm to obtain radio frequency (RF)- reduced models of micro-electromechanical systems (MEMS) switches and show how, together with multiphysics macromodels, they can be realized as circuits that include both lumped and distributed parameters. The macromodels are extracted with a robust procedure from the solution of Maxwell’s equations with electromagnetic circuit element (ECE) boundary conditions. The reduced model is extracted from the simulations of three electromagnetic field problems, in full-wave regime, that correspond to three configurations: signal lines alone, switch in the up and down positions. The technique is exemplified for shunt switches, but it can be extended for lateral switches. Moreover, the algorithm is able take frequency dependence into account both for the signal lines and for the switch model. For the later, the order of the model is increased until a specified accuracy is achieved. The use of ECE as boundary conditions for the RF simulation of MEMS switches has the advantage that the definition of ports is unambiguous and robust as the ports are clearly defined. The extraction approach has the advantage that the simplified model keeps the basic phenomena, i.e. the propagation of the signal along the lines. As the macromodel is realized with a netlist that uses transmission lines models, the lines’ extension is natural. The frequency dependence can be included in the model, if needed.

Fig: Modeling chain: from continuous models to reduced macromodels

Acknowledgement: The work has been funded by the Operational Programme Human Capital of the Ministry of European Funds through The Financial Agreement 51675/09.07.2019, SMIS code 125125.