Trends in Paper-based Electrochemical Biosensors: From Design to Application
Abstract
Electrochemical bio-sensing using paper-based detection systems is the main focus of this review. The different existing designs of 2-dimensional and 3-dimensional sensors, and fabrication techniques are discussed. This review highlights the effect of adopting different sensor designs, distinct fabrication techniques, as well as different modification methods, in order to produce reliable and reproducible reading. The use of various nanomaterials have been demonstrated in order to modify the surface of electrodes during fabrication to further enhance the signal for subsequent analysis. The reviewed sensors were classified into categories based on their applications, such as diagnostics, environmental and food testing. One of the major advantages of using paper-based electrochemical sensors is the potential for miniaturization, which only requires relatively small amount of samples, and the low cost for the purpose of mass production. Additionally, most of the devices reviewed were made to be portable, making them well-suited for on-site detection. Finally, paper-based detection is an ideal platform to fabricate cost-effective, user-friendly and sensitive electrochemical biosensors, with large capacity for customization depending on functional needs.
Read the paper
Related studies
- Nano Biosensors: Properties, applications and electrochemical techniques
- Electrochemically Synthesized MIP Sensors: Applications in Healthcare Diagnostics
- Toward a Harmonization for Using in situ Nutrient Sensors in the Marine Environment
- Electrochemical determination of rutin by using NiFe2O4 nanoparticles-loaded reduced graphene oxide
- Application of Polyoxometalate-based composites for sensor systems: A review
- Sensitive Electrochemical and Thermal Detection of Human Noroviruses Using Molecularly Imprinted Polymer Nanoparticles Generated against a Viral Target
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.