Plant-Assisted Green Synthesis of MgO Nanoparticles as a Sustainable Material for Bone Regeneration: Spectroscopic Properties

This work is devoted to magnesium oxide (MgO) nanoparticles (NPs) for their use as additives for bone implants. Extracts from four different widely used plants, including Aloe vera, Echeveria elegans, Sansevieria trifasciata, and Sedum morganianum, were evaluated for their ability to facilitate the "green synthesis" of MgO nanoparticles. The thermal stability and decomposition behavior of the MgONPs were analyzed by thermogravimetric analysis (TGA). Structure characterization was performed by X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDS), ultraviolet-visible spectroscopy (UV-Vis), dynamic light scattering (DLS), and Raman scattering spectroscopy (RS). Morphology was studied by scanning electron microscopy (SEM). The photocatalytic activity of MgO nanoparticles was investigated based on the degradation of methyl orange (MeO) using UV-Vis spectroscopy. Surface-enhanced Raman scattering spectroscopy (SERS) was used to monitor the adsorption of L-phenylalanine (L-Phe) on the surface of MgONPs. The calculated enhancement factor (EF) is up to 102 orders of magnitude for MgO. This is the first work showing the SERS spectra of a chemical compound immobilized on the surface of MgO nanoparticles.

Plexcitonic Nanorattles as Highly Efficient SERS-Encoded Tags

Plexcitonic nanoparticles exhibit strong light-matter interactions, mediated by localized surface plasmon resonances, and thereby promise potential applications in fields such as photonics, solar cells, and sensing, among others. Herein, these light-matter interactions are investigated by UV-visible and surface-enhanced Raman scattering (SERS) spectroscopies, supported by finite-difference time-domain (FDTD) calculations. Our results reveal the importance of combining plasmonic nanomaterials and J-aggregates with near-zero-refractive index. As plexcitonic nanostructures nanorattles are employed, based on J-aggregates of the cyanine dye 5,5,6,6-tetrachloro-1,1-diethyl-3,3-bis(4-sulfobutyl)benzimidazolocarbocyanine (TDBC) and plasmonic silver-coated gold nanorods, confined within mesoporous silica shells, which facilitate the adsorption of the J-aggregates onto the metallic nanorod surface, while providing high colloidal stability. Electromagnetic simulations show that the electromagnetic field is strongly confined inside the J-aggregate layer, at wavelengths near the upper plexcitonic mode, but it is damped toward the J-aggregate/water interface at the lower plexcitonic mode. This behavior is ascribed to the sharp variation of dielectric properties of the J-aggregate shell close to the plasmon resonance, which leads to a high opposite refractive index contrast between water and the TDBC shell, at the upper and the lower plexcitonic modes. This behavior is responsible for the high SERS efficiency of the plexcitonic nanorattles under both 633 nm and 532 nm laser illumination. SERS analysis showed a detection sensitivity down to the single-nanoparticle level and, therefore, an exceptionally high average SERS intensity per particle. These findings may open new opportunities for ultrasensitive biosensing and bioimaging, as superbright and highly stable optical labels based on the strong coupling effect.

Comparative Study of SERS-Spectra of NQ21 Peptide on Silver Particles and in Gold-Coated "Nanovoids"

The NQ21 peptide has relatively recently attracted attention in the biomedical sphere due to its prospects for facilitating the engineering of the HIV1 vaccine and ELISA test. Today, there is still a need for a reliable and fast methodology that reveals the secondary structure of this analyte at the low concentrations conventionally used in vaccines and immunological assays. The present research determined the differences between the surface-enhanced Raman scattering (SERS) spectra of NQ21 peptide molecules adsorbed on solid SERS-active substrates depending on their geometry and composition. The ultimate goal of our research was to propose an algorithm and SERS-active material for structural analysis of peptides. Phosphate buffer solutions of the 30 µg/mL NQ21 peptide at different pH levels were used for the SERS measurements, with silver particles on mesoporous silicon and gold-coated "nanovoids" in macroporous silicon. The SERS analysis of the NQ21 peptide was carried out by collecting the SERS spectra maps. The map assessment with an originally developed algorithm resulted in defining the effect of the substrate on the secondary structure of the analyte molecules. Silver particles are recommended for peptide detection if it is not urgent to precisely reveal all the characteristic bands, because they provide greater enhancement but are accompanied by analyte destruction. If the goal is to carefully study the secondary structure and composition of the peptide, it is better to use SERS-active gold-coated "nanovoids". Objective results can be obtained by collecting at least three 15 × 15 maps of the SERS spectra of a given peptide on substrates from different batches.

Mechanically Tunable Lattice-Plasmon Resonances by Templated Self-Assembled Superlattices for Multi-Wavelength Surface-Enhanced Raman Spectroscopy

Lattice plasmons, i.e., diffractively coupled localized surface plasmon resonances, occur in long-range ordered plasmonic nanostructures such as 1D and 2D periodic lattices. Such far-field coupled resonances can be employed for ultrasensitive surface-enhanced Raman spectroscopy (SERS), provided they are spectrally matched to the excitation wavelength. The spectral positions of lattice plasmon modes critically depend on the lattice period and uniformity, owing to their pronounced sensitivity to structural disorder. We report the fabrication of superlattices by templated self-assembly of gold nanoparticles on a flexible support, with tunable lattice-plasmon resonances by means of macroscopic strain. We demonstrate that the highest SERS performance is achieved by matching the lattice plasmon mode to the excitation wavelength, by post-assembly fine-tuning of long-range structural parameters. Both asymmetric and symmetric lattice deformations can be used to adapt a single lattice structure to both red-shifted and blue-shifted excitation lines, as exemplified by lattice expansion and contraction, respectively. This proof-of-principle study represents a basis for alternative designs of adaptive functional nanostructures with mechanically tunable lattice resonances using strain as a macroscopic control parameter.

Dendritic Forest-Like Ag Nanostructures Prepared Using Fluoride-Assisted Galvanic Replacement Reaction for SERS Applications

Dendritic forest-like Ag nanostructures were deposited on a silicon wafer through fluoride-assisted galvanic replacement reaction (FAGRR) in aqueous AgNO₃ and buffered oxide etchant. The prepared nanostructures were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy, inductively coupled plasma–optical emission spectroscopy, a surface profiler (alpha step), and X-ray diffraction. Additionally, the dendritic forest-like Ag nanostructures were characterized using surface-enhanced Raman scattering (SERS) when a 4-mercaptobenzoic acid (4-MBA) monolayer was adsorbed on the Ag surface. The Ag nanostructures exhibited intense SERS signal from 4-MBA because of their rough surface, and this intense signal led to an intense local electromagnetic field upon electromagnetic excitation. The enhancement factor for 4-MBA molecules adsorbed on the Ag nanostructures was calculated to be 9.18 × 10⁸. Furthermore, common Raman reporters such as rhodamine 6G, 4-aminothiolphenol, 5,5′-dithiobis-2-nitrobenzoic acid, and carboxyfluorescein (FAM) were characterized on these dendritic forest-like Ag nanostructures, leading to the development of an ultrasensitive SERS-based DNA sensor with a limit of detection of 33.5 nM of 15-mer oligonucleotide.

Efficient Capture and Raman Analysis of Circulating Tumor Cells by Nano-Undulated AgNPs-rGO Composite SERS Substrates

The analysis of circulating tumor cells (CTCs) in the peripheral blood of cancer patients is critical in clinical research for further investigation of tumor progression and metastasis. In this study, we present a novel surface-enhanced Raman scattering (SERS) substrate for the efficient capture and characterization of cancer cells using silver nanoparticles-reduced graphene oxide (AgNPs-rGO) composites. A pulsed laser reduction of silver nanowire-graphene oxide (AgNW-GO) mixture films induces hot-spot formations among AgNPs and artificial biointerfaces consisting of rGOs. We also use in situ electric field-assisted fabrication methods to enhance the roughness of the SERS substrate. The AgNW-GO mixture films, well suited for the proposed process due to its inherent electrophoretic motion, is adjusted between indium tin oxide (ITO) transparent electrodes and the nano-undulated surface is generated by applying direct-current (DC) electric fields during the laser process. As a result, MCF7 breast cancer cells are efficiently captured on the AgNPs-rGO substrates, about four times higher than the AgNWs-GO films, and the captured living cells are successfully analyzed by SERS spectroscopy. Our newly designed bifunctional substrate can be applied as an effective system for the capture and characterization of CTCs.

In Situ Differentiation of Multiplex Noncovalent Interactions Using SERS and Chemometrics

Probing changes of noncovalent interactions is crucial to study the binding efficiencies and strengths of (bio)molecular complexes. While surface-enhanced Raman scattering (SERS) offers unique molecular fingerprints to examine such interactions in situ, current platforms are only able to recognize hydrogen bonds because of their reliance on manual spectral identification. Here, we differentiate multiple intermolecular interactions between two interacting species by synergizing plasmonic liquid marble-based SERS platforms, chemometrics, and density functional theory. We demonstrate that characteristic 3-mercaptobenzoic acid (probe) Raman signals have distinct peak shifts upon hydrogen bonding and ionic interactions with tert-butylamine, a model interacting species. Notably, we further quantify the contributions from each noncovalent interaction coexisting in different proportions. As a proof-of-concept, we detect and categorize biologically important nucleotide bases based on molecule-specific interactions. This will potentially be useful to study how subtle changes in biomolecular interactions affect their structural and binding properties.

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens

Olfaction is important for identifying and avoiding toxic substances in living systems. Many efforts have been made to realize artificial olfaction systems that reflect the capacity of biological systems. A sophisticated example of an artificial olfaction device is the odor compass which uses chemical sensor data to identify odor source direction. Successful odor compass designs often rely on plume-based detection and mobile robots, where active, mechanical motion of the sensor platform is employed. Passive, diffusion-based odor compasses remain elusive as detection of low analyte concentrations and quantification of small concentration gradients from within the sensor platform are necessary. Further, simultaneously identifying multiple odor sources using an odor compass remains an ongoing challenge, especially for similar analytes. Here, we show that surface-enhanced Raman scattering (SERS) sensors overcome these challenges, and we present the first SERS odor compass. Using a grid array of SERS sensors, machine learning analysis enables reliable identification of multiple odor sources arising from diffusion of analytes from one or two localized sources. Specifically, convolutional neural network and support vector machine classifier models achieve over 90% accuracy for a multiple odor source problem. This system is then used to identify the location of an Escherichia coli biofilm via its complex signature of volatile organic compounds. Thus, the fabricated SERS chemical sensors have the needed limit of detection and quantification for diffusion-based odor compasses. Solving the multiple odor source problem with a passive platform opens a path toward an Internet of things approach to monitor toxic gases and indoor pathogens.