Functionalized polymeric biosensors via electrospinning assisted by controlled radical polymerization - de Castro, Karine Cappuccio [UNESP]; Hatami, Tahmasb; Vieira, Roniérik Pioli; Pinheiro, Ivanei Ferreira; Ferreira, Filipe Vargas; Mei, Lucia Helena Innocentini (Springer Nature, 2024)
Biosensors stand at the forefront of innovation in critical fields such as medicine, food safety, and environmental monitoring, offering precise detection of specific biomarkers. Among these, polymer-based biosensors have emerged as powerful tools, evolving from inert materials to intricately tailored structures capable of precise molecular binding. Electrospinning, a prominent fabrication method, offers a cost-effective approach for developing diagnostic kits, pushing the boundaries of biosensors with exceptionally low analyte detection limits. However, the reliance on commercial polymers restricts the versatility of electrospun nanofibers due to the fixed properties and limited functionalization options of off-the-shelf materials. These constraints prevent the tailoring of nanofibers to meet specific or diverse needs, as their molecular structure and surface functionalities are not easily adjustable. A promising solution is integrating Controlled Radical Polymerization (CRP) with electrospinning. CRP provides precise control over polymer properties, enabling the creation of nanofibers with customized functionalities for various applications. This approach combines the benefits of electrospinning, such as high surface area-to-volume ratios, with the advanced capabilities of CRP to enhance the selectivity and sensitivity of biosensors. This review represents recent advancements in biosensors, covering acquisition, characterization, and applications, with a focal point on the role of functional polymers. Exploring biosensor architecture, electrospinning principles, controlled polymer synthesis, CRP techniques, and polymer topologies, the manuscript also discusses challenges and future prospects, including microfluidic integration, multi-detection capabilities, machine learning, and the development of wearable biosensors. Graphical abstract: (Figure presented.)