[paper] Device for the Detection and Quantification of Exosomes

Diego Barrettino1, Christoph Zumbühl1, Raphael Kummer1, Markus Thalmann1, Carolina Balbi2, Giuseppe Vassalli2, Rosane Moura Dos Santos3 and Jean-Michel Sallese3

Low-Cost Portable Medical Device for the Detection and Quantification of Exosomes

2023 IEEE SENSORS, Vienna, Austria, 2023, pp. 1-4,

doi: 10.1109/SENSORS56945.2023.10325271. 

1 Lucerne University of Applied Sciences and Arts (HSLU), Institute of Electrical Engineering, CH- 6048 Horw, Switzerland
2 Istituto Cardiocentro Ticino, Via Tesserete 48, CH-6900 Lugano, Switzerland
3 Swiss Federal Institute of Technology Lausanne (EPFL), EPFL SCI STI EDLAB, Station 11, CH-1015 Lausanne, Switzerland

Abstract: The design, fabrication and testing of a low-cost portable medical device for the detection and quantification of exosomes is presented in this paper. The portable medical device comprises a sensor array that can detect the presence of exosomes and quantify its concentration, a microfluidic device that handles the human serum containing the exosomes, and all the necessary readout and control electronics. Measurement results performed with exosomes showed that the portable medical device can detect exosomes with a concentration of 2.5x108 /µL thus paving the way to a wide range of diagnostic applications.

Fig. Exosome immobilized on top of the functionalized (antibody CD63 +protein G
+ polydopamine + graphene oxide) JLFET biosensor and tagged with a gold (Au) nanoparticle attached to an exosome biomarker (antibody CD31)

[book chapters] Equation-Based Compact Modeling

 

Debnath, P., Sarkar, B., & Chanda, M. (Eds.). (2023).

Differential Equation Based Solutions 

for Emerging Real-Time Problems

(1st ed.). CRC Press 

DOI 10.1201/9781003227847

Chapter: Differential Equation-Based Compact 2-D Modeling of Asymmetric Gate Oxide Heterojunction Tunnel FET; By: Sudipta Ghosh, Arghyadeep Sarkar

Abstract: Tunnel Field Effect Transistor (TFET) has emerged as an effective alternative device to replace MOSFET for a few decades. The major drawbacks of MOSFET devices are the short-channel effects, due to which the leakage current increases with a decrease in device dimension. So, scaling down TFET is more efficacious than that of MOSFETs. Sub-threshold swing (SS) is another advantageous characteristic of TFET devices for high-speed digital applications. In TFETs the SS could be well below 60 mV/decade, which is the thermal limit for MOSFET devices and therefore makes it more suitable than MOSFET for faster switching applications. It is observed from the literature studies that the performances of the TFET devices have been explored thoroughly by using 2-D TCAD simulation but an analytical model is always essential to understand the physical behavior of the device and the physics behind this; which facilitates further, the analysis of the device performances at circuit level as and when implemented.

Chapter: Differential Equation-Based Analytical Modeling of the Characteristics Parameters of the Junctionless MOSFET-Based Label-Free Biosensors; by: Manash Chanda, Papiya Debnath, Avtar Singh

Abstract: Recently Field Effect transistor (FET)-based biosensing applications have gained significant attention due to the demand for quick and accurate diagnosis of different enzymes, proteins, DNA, viruses, etc; cost-effective fabrication process; portability and better sensitivity and selectivity compared to the existing biosensors. FET is basically a three-terminal device with source, drain, and gate terminals. Basically, the gate terminal controls the current flow between the source and drain terminals. In FETs, first, a nanogap is created in the oxide layer or in the gate by etching adequate materials. When the biomolecules are trapped inside the nanocavity then the surface potentials change and also the threshold voltage varies. As a result, the output current also changes. Finally, by measuring the changes in the threshold voltage or the device current, one can easily detect the biomolecules easily.

[papers] Biosensors for Agriculture, Environment and Food

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J. Ajayan, P. Mohankumar, R. Mathew, L. R. Thoutam, B. K. Kaushik and D. Nirmal

"Organic Electrochemical Transistors (OECTs)

Advancements and Exciting Prospects for Future Biosensing Applications" 

in IEEE Transactions on Electron Devices, vol. 70, no. 7, pp. 3401-3412, July 2023

DOI: 10.1109/TED.2023.3271960

Abstract: Over the past few decades, the field of organic electronics has depicted proliferated growth, due to the advantageous characteristics of organic semiconductors, such as tunability through synthetic chemistry, simplicity in processing, cost-effectiveness, and low-voltage operation, to cite a few. Organic electrochemical transistors (OECTs) have recently emerged as a highly promising technology in the area of biosensing and flexible electronics. OECT-based biosensors are capable of sensing brain activities, tissues, monitoring cells, hormones, DNAs, and glucose. Sensitivity, selectivity, and detection limit are the key parameters adopted for measuring the performance of OECT-based biosensors. This article highlights the advancements and exciting prospects of OECTs for future biosensing applications, such as cell-based biosensing, chemical sensing, DNA/ribonucleic acid (RNA) sensing, glucose sensing, immune sensing, ion sensing, and pH sensing. OECT-based biosensors outperform other conventional biosensors because of their excellent biocompatibility, high transconductance, and mixed electronic–ionic conductivity. At present, OECTs are fabricated and characterized in millimeter and micrometer dimensions, and miniaturizing their dimensions to nanoscale is the key challenge for utilizing them in the field of nanobioelectronics, nanomedicine, and nanobiosensing. URL

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Y. Wu et al., 

"A Dynamic Concentration-Dependent Analytical I,–V Model for LG-GFET Biosensor" 

in IEEE Transactions on Electron Devices, vol. 70, no. 6, pp. 3255-3262, June 2023, 

DOI: 10.1109/TED.2023.3268139.

Abstract: In the past few years, liquid-gated graphene field-effect transistors (LG-GFETs) have been widely used in biological detection due to their unique advantages. An accurate transistor model is the basis of biological detection circuit design, however, the reported GFET models are mainly focusing on solid-gated GFETs. Therefore, it is essential to conduct the research on LG-GFET model. In this article, an improved  IV  model of LG-GFET is presented based on Fregonese’s model. An improved electric double-layer capacitor model is proposed for LG-GFET. Then, the relationship among iron concentration, bias voltages, and current is studied comprehensively. Furthermore, the drain current response change with time is taken into account and the dynamic concentration-dependent model is established. To verify the accuracy of the proposed model, LG-GFET is simulated in TCAD software and fabricated to perform the measurement. The simulation results and measurement results are compared with the model results, respectively. These results show that the relative root-mean-square error (RMSE) to both simulation and measurement results is less than 5.7%. It is revealed that the proposed model can be applied to biological detection and achieve high accuracy.URL

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Special Issue "Biosensors for Agriculture, Environment and Food"

Biosensors (ISSN 2079-6374) an Open Access Journal by MDPI

Editor-in-Chief Prof. Dr. Giovanna Marrazza 

Department of Chemistry “Ugo Schiff”, University of Florence, Italy

Food safety has become a hot issue concerned by governments, people and society. Biosensors have been playing a greater vital role in monitoring agro-products and their production process to ensure end-foods’ quality and safety, and they usually demonstrate a lot of benefits, such as being sensitive, rapid, portable, cheap and especially suitable for on-site testing. So, this topic will concern the development of biosensors and analytical methods, especially for chemicals, microorganisms, biotoxins in agriculture, environment and food samples. It is suggested that biosensors should be in line with the trend of five “S”, Sensitivity, Specificity (Selection), Speed, Simultaneously, Small (Smart), and that all detection methods should be validated using agriculture, environment or food samples. Interdisciplinary research and integrative application research related to biosensors are also encouraged, including review articles and research articles.

Compact Modeling of 2D Field-Effect Biosensors

Francisco Pasadas¹, Tarek El Grour², Enrique G. Marin¹, Alberto Medina-Rull¹, Alejandro Toral-Lopez¹, Juan Cuesta-Lopez¹, Francisco G. Ruiz¹, Lassaad El Mir² and Andrés Godoy¹

Compact Modeling of Two-Dimensional Field-Effect Biosensors.

Sensors 2023, 23, 1840.

DOI: 10.3390/s23041840

1 Pervasive Electronics Advanced Research Laboratory (PEARL), Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada,18071 Granada, Spain
2 Laboratory of Physics of Materials and Nanomaterials Applied at Environment (LaPhyMNE) LR05ES14, Faculty of Sciences of Gabes, Gabes University, Erriadh City, Zrig, 6072 Gabes, Tunisia

Abstract: A compact model able to predict the electrical read-out of field-effect biosensors based on two-dimensional (2D) semiconductors is introduced. It comprises the analytical description of the electrostatics including the charge density in the 2D semiconductor, the site-binding modeling of the barrier oxide surface charge, and the Stern layer plus an ion-permeable membrane, all coupled with the carrier transport inside the biosensor and solved by making use of the Donnan potential inside the ion-permeable membrane formed by charged macromolecules. This electrostatics and transport description account for the main surface-related physical and chemical processes that impact the biosensor electrical performance, including the transport along the low-dimensional channel in the diffusive regime, electrolyte screening, and the impact of biological charges. The model is implemented in Verilog-A and can be employed on standard circuit design tools. The theoretical predictions obtained with the model are validated against measurements of a MoS2 field-effect biosensor for streptavidin detection, showing excellent agreement in all operation regimes and leading the way for the circuit-level simulation of biosensors based on 2D semiconductors

FIG: Schematic of a two-dimensional field-effect biosensor. A sketch of the position-dependent potential is also shown, highlighting the surface charge density at the 2D channel (σ2D), at the oxide-electrolyte interface (σ0), and at the membrane-diffuse regions of the electrolyte (σmd). The latter comprises a charge-free layer (Stern layer) and an ion-permeable membrane due to the presence of charged macromolecules, with a diffusion layer located between the barrier oxide surface and the bulk electrolyte. The potential difference from the electrolyte bulk to the barrier oxide surface, ψ0, encompasses two contributions originating from a potential drop (ψ0 − ψm) across the Stern layer extending between the outer Helmholtz plane (OHP) and the barrier oxide surface, and a potential drop across the ion-permeable membrane layer formed by charged macromolecules and the diffuse layer (ψm)

Funding: This work is funded by the Spanish Government MCIN/AEI/10.13039/501100011033 through the projects PID2020-116518GB-I00 and TED2021-129769B-I00 (MCIU/AEI/FEDER-UE); and by FEDER/Junta de Andalucía-Consejería de Transformacion Económica, Industria, Conocimiento y Universidades through the projects P20_00633 and A-TIC-646-UGR20. F. Pasadas acknowledges funding from PAIDI 2020 and the European Social Fund Operational Programme 2014–2020 no. 20804. A. Medina-Rull acknowledges the support of the MCIN/AEI/PTA grant, with reference PTA2020- 018250-I. J. Cuesta-Lopez acknowledges the FPU program FPU019/05132, and A. Toral-Lopez the support of Plan Propio of Universidad de Granada.

Data Availability Statement: The Verilog-A model for 2D EIS BioFETs is available from the corresponding author (fpasadas@ugr.es) upon reasonable request.

IJHSES Special Issue Volume 29, Issue 01n04, 2020

IJHSES Special Issue on Nanotechnology for Electronics, Biosensors, 

Additive Manufacturing and Emerging Systems Applications 

Guest Editors: F. Jain, C. Broadbridge, M. Gherasimova and H. Tang

Volume 29, Issue 01n04 (March, June, September, December 2020) 

This Special issue on Nanotechnology for Electronics, Biosensors, Additive Manufacturing and Emerging Systems Applications comprises peer reviewed articles selected from the 29th annual symposium of the Connecticut Microelectronics and Optoelectronics Consortium (CMOC), virtually held on October 2, 2020 and hosted by Information Technology Staff, University of Connecticut (Storrs Campus).

Organized by a team of seven academic institutions and about eighteen companies across the United States, this symposium sign-posted the progress and development of state-of-arts research in high-speed electronics over the last 30 years.

Articles include keynote presentations by three experts in their field:

• Dr. H. Lee, Electronic and IR Sensing in Forensics, U. New Haven, and Henry Lee Center for Forensic Research
• Dr. E. Fossum, Quanta Image Sensor, Dartmouth College
• Dr. J. Chow, Quantum Computing, IBM Thomas J. Watson, Research Center

The papers presented span from novel materials and devices, biosensors and bio- nano- systems, artificial intelligence, robotics and emerging technologies, to applications in each of these fields, Systems for implementing data with security tokens; single chemical sensor for multi-analyte mixture detection; RF energy harvesters; additively manufactured RF devices for 5G, IoT, RFID and smart city applications are also included in this special issue on high performance materials for implementing high-speed electronic systems.

In the area of material synthesis, modeling of dislocations behavior in various II-VI and III-V heterostructures and their gettering at sidewall bringing novel approaches are also featured

Coming hot on the heels, are recent developments on high performance devices include equivalent circuits models at room and 4.2K; quantum dot nonvolatile memories, 3D- confined quantum dot channel (QDC) and spatial wavefunction switched (SWS) FETs for high-speed multi-bit logic and novel system applications.

In summary, the papers selected for this special issue cover various aspects of h performance materials and emerging devices for implementing high-speed electronic systems. We would like to take this opportunity to express our thanks to the authors, participants, and reviewers for their contributions and active participation, networking, and knowledge sharing on a variety of research areas.

[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)