Detection of ultra-low protein concentrations with the simplest possible field effect transistor

Aptamer-functionalized field-effect transistor biosensors for disease diagnosis and environmental monitoring

Nano-biosensors that are composed of recognition molecules and nanomaterials have been extensively utilized in disease diagnosis, health management, and environmental monitoring. As a type of nano-biosensors, molecular specificity field-effect transistor (FET) biosensors with signal amplification capability exhibit prominent advantages including fast response speed, ease of miniaturization, and integration, promising their high sensitivity for molecules detection and identification. With intrinsic characteristics of high stability and structural tunability, aptamer has become one of the most commonly applied biological recognition units in the FET sensing fields. This review summarizes the recent progress of FET biosensors based on aptamer functionalized nanomaterials in medical diagnosis and environmental monitoring. The structure, sensing principles, preparation methods, and functionalization strategies of aptamer modified FET biosensors were comprehensively summarized. The relationship between structure and sensing performance of FET biosensors was reviewed. Furthermore, the challenges and future perspectives of FET biosensors were also discussed, so as to provide support for the future development of efficient healthcare management and environmental monitoring devices.

Advances in silicon nanowire applications in energy generation, storage, sensing, and electronics: a review

Nanowire-based technological advancements thrive in various fields, including energy generation and storage, sensors, and electronics. Among the identified nanowires, silicon nanowires (SiNWs) attract much attention as they possess unique features, including high surface-to-volume ratio, high electron mobility, bio-compatibility, anti-reflection, and elasticity. They were tested in domains of energy generation (thermoelectric, photo-voltaic, photoelectrochemical), storage (lithium-ion battery (LIB) anodes, super capacitors), and sensing (bio-molecules, gas, light, etc). These nano-structures were found to improve the performance of the system in terms of efficiency, stability, sensitivity, selectivity, cost, rapidity, and reliability. This review article scans and summarizes the significant developments that occurred in the last decade concerning the application of SiNWs in the fields of thermoelectric, photovoltaic, and photoelectrochemical power generation, storage of energy using LIB anodes, biosensing, and disease diagnostics, gas and pH sensing, photodetection, physical sensing, and electronics. The functionalization of SiNWs with various nanomaterials and the formation of heterostructures for achieving improved characteristics are discussed. This article will be helpful to researchers in the field of nanotechnology about various possible applications and improvements that can be realized using SiNW.

Current Status of Field-Effect Transistors for Biosensing Applications

The latest novelties in electronic biosensors indicate an increased interest in the compatibilization between Field Effect Transistors (FETs) and bioreceptors, either enzymes, antibodies or cells, for the purpose of detecting the multiple analytes [...].

Generalized Analytical Model for Enzymatic BioFET Transistors

Software tools that are able to simulate the functionality or interactions of an enzyme biosensor with Metal Oxide Semiconductor (MOS), or any Field Effect Transistor (FET) as transducer, represent a gap in the market. Bio-devices, or Enzyme-FET, cannot be simulated by Atlas or equivalent software. This paper resolves this issue for the enzymatic block coupled with FETs’ role within biosensors. The first block has the concentration of biological analyte as the input signal and concentration of ions from the enzymatic reaction as the output signal. The modeling begins from the Michaelis–Menten formalism and analyzes the time dependence of the product concentrations that become the input signal for the next FET block. Comparisons within experimental data are provided. The analytical model proposed in this paper represents a general analytical tool in the design stage for enzymatic transistors used in clinical practices.