Plasma-assisted fabrication of nanoparticle-decorated electrospun nanofibers

SERS Assays Based on Electrospun Nanofibers: Preparation and Analytical Applications

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool and an up-to-date method of analytical chemistry due to its high sensitivity and fingerprint recognition capabilities. Nowadays SERS due to its label-free detection capabilities is being actively developed in medical fields, for example in the analysis of biologically important substances in different matrixes, for potential on-site detection of toxic substances, food safety, and so on. To get the SERS signal, it is necessary the presence of plasmonic nanostructures in the SERS substrates. Electrospun nanofibers have been an attractive alternative to SERS-platforms due to the diversity of advantages, including ease of preparation, structure flexibility, and others. In this review, we summarized the methods of plasmonic nanostructures incorporating substrate based on electrospun nanofibers. Also, the analytical application of SERS-active electrospun nanofibers with embedded nanostructures focused on biologically significant molecules is observed in detail. Finally, the future outlook in the application of these substrates in bioanalysis as the most promising area in analytical chemistry is presented.

Modelling of urea hydrolysis kinetics using genetic algorithm coupled artificial neural networks in urease immobilized magnetite nanoparticles

The presence of urea in runoff from fertilized soil could be contributing to the growth of dangerous blooms. Enzymatic urea hydrolysis is a well-known outstanding process that, when integrated with nanotechnology, would be much more efficient. This research provides a novel perspective on magnetic nanobiocatalysts that reduce diffusion barriers in effective urea hydrolysis. Surprisingly, the model developed with the use of a Genetic Algorithm (GA) and an Artificial Neural Network (ANN) demonstrated that the system's diffusion restrictions were reduced. In order to forecast accurate outputs using artificial intelligence (AI), a neural network with one hidden layer and 20 neurons was built utilizing multilayer feed-forward network and showed highest output (diffusion co-efficient) with least mean square error (MSE). The diffusion coefficients of free urease, urease immobilized onto porous MNs (U-aMNs), and nanobiocatalyst, i.e. urease immobilized onto surface modified MNs (U-MN_β), were 1.9 × 10^-17, 12.62 × 10^-16, and 15.48 × 10^-16 cm²/min, respectively. These results revealed that the addition of Chitosan to the surface of MNs had a considerable impact on enzyme dispersion. The decrease in Damkohler number (Da) from 2.37 ± 0.26 for U-aMNs to 2.19 ± 0.11 for U-MN_β suggested a beneficial effect in overcoming diffusion constraints. Pseudo-first order and pseudo-second order models were used to analyze urea uptake kinetics, with the former model offering the best fit to the system, with R² values that were much closer to unity.

Design, Fabrication and Applications of Electrospun Nanofiber-Based Surface-Enhanced Raman Spectroscopy Substrate

Surface-enhanced Raman spectroscopy (SERS) is an advanced and powerful analysis tool. Due to the advantages of high sensitivity, high resolution, and nondestructive testing, it has been widely used in physics, chemistry, material science and other fields. In recent years, substantial progress has been made in developing flexible platforms for the design and fabrication of SERS substrates. One important kind of the flexible platforms is based on electrospun nanofibers. Electrospun nanofibers not only have unique advantages such as easy preparation, high porosity and large specific surface area, but also can increase the number of hotspots when combined with precious metal nanomaterials, thereby enhancing the SERS signal and expanding the application scope. In this review, we firstly focus on two strategies for the fabrication of metal nanostructure decorated in/on the electrospun nanofibers, namely in-situ and ex-situ. Then the applications of these SERS substrates in the fields of quantitative analysis, monitoring chemical reactions and recyclable detection are introduced in detail. Finally, the challenges as well as perspectives are presented to offer a guideline for the future exploration of these SERS substrates. We expect that it will provide new inspiration for the development of electrospun nanofiber-based SERS substrates.

The current state of the art of plasmonic nanofibrous mats as SERS substrates: design, fabrication and sensor applications

Surface-enhanced Raman scattering (SERS) is a widely used analytical tool that allows molecular fingerprint-based ultra-sensitive detection through an enhanced electromagnetic field generated by plasmonic metal nanoparticles (MNPs) by virtue of their localized surface plasmon resonance (LSPR). Although significant progress has been made in the design and fabrication of a variety of SERS substrates, MNP-decorated electrospun nanofibrous (NF) mats have attracted much attention due to their unique nanoscale structural and functional properties. This review focuses on the current state of the art in the fabrication of plasmonic NF mats with the main focus on the pre-mix, in situ, and ex situ approaches. The characteristic functional advantages and limitations of these strategies are also highlighted, which might be helpful for the research community when adopting a suitable approach. The potential of these plasmonic NF mats as a SERS-active optical sensor substrate, and their performance parameters such as the limit of detection, analytical range, and enhancement factor, and real-world applications are also discussed. The summary and futuristic discussion in this review might be of significant value in developing plasmonic NF mat-based SERS-active point-of-care diagnostic chips for a wide range of applications.

Plasma-treated electrospun nanofibers as a template for the electrostatic assembly of silver nanoparticles

Silver nanoparticles assembled on a plasma treated electrospun nanofiber membrane could show excellent SERS effect.