Search Results (1,535)

This paper discusses the fabrication of three-dimensional dendritic Ag nanostructures, showcasing pronounced Localized Surface Plasmon Resonance (LSPR) effects. These nanostructures, employed in surface-enhanced Raman scattering (SERS), function as sensors for lactic acid in artificial sweat. The dendritic structures of the silver nanoparticles (AgNPs) create an effective SERS substrate, with additional hotspots at branch junctures enhancing LSPR. We achieve differential LSPR effects by varying the distribution and spacing of branches and the overall morphology. Adjustments to electrodeposition parameters, such as current and plating solution protective agents on an anodized aluminum oxide (AAO) base, allow for precise control over LSPR intensities. By pre-depositing AgNPs, the electron transmission paths during electrodeposition are modified, which leads to optimized dendritic morphology and enhanced LSPR effects. Parameter optimization produces elongated rods with main and secondary branches, covered with uniformly sized, densely packed, non-overlapping spherical AgNPs. This configuration enhances the LSPR effect by generating additional hotspots beyond the branch tips. Fine-tuning the electrodeposition parameters improved the AgNPs’ morphology, achieving uniform particle distribution and optimal spacing. Compared to non-SERS substrates, our structure amplified the Raman signal for lactic acid detection by five orders of magnitude. This method can effectively tailor SERS substrates for specific analytes and laser-based detection. Full article

Surface-enhanced Raman scattering (SERS) is a powerful tool for biosensing with high sensitivity, selectivity, and capability of multiplex monitoring for both in vivo and in vitro studies. This has been applied for the identification and detection of different biological metabolites such as lipids, nucleic acids, and proteins. The present review article explores the vast applications of metallic nanoparticles for SERS-based biosensing. We have summarized and discussed the fundamental principles, theories, developments, challenges, and perspectives in the field of SERS-based biosensing using different metal nanoparticle substrates namely gold, silver, copper, and bimetallic nanoparticles. Full article

Furfural is an essential compound that contributes to the distinctive flavor of sauce-flavored Baijiu. However, traditional detection methods are hindered by lengthy and complex sample preparation procedures, as well as the need for expensive equipment. Therefore, there is an urgent need for a new approach that allows rapid detection. In this study, we developed a novel surface-enhanced Raman spectroscopy (SERS) substrate by constructing MXene (Ti₃C₂T_X) @Ag nanoparticles (Ag NPs) through an electrostatic attraction method. The MXene (Ti₃C₂T_X) @Ag NPs were successfully fabricated, with adsorbed NaCl-treated Ag NPs uniformly absorbed on the surface of MXene (Ti₃C₂T_X), creating high-density distributed SERS “hot spots”. The prepared substrate demonstrated excellent sensitivity, uniformity, repeatability, and long-term stability, with a low detectable concentration of 10⁻⁹ M for R6G (Rhodamine 6G) and an enhancement factor of up to 7.08 × 10⁵. When applied for the in situ SERS detection of furfural in Baijiu, the detection limit was as low as 0.5 mg/L. Overall, the proposed method offers rapid, low-cost, and sensitive quantitative analysis, which is significant not only for detecting furfural in Baijiu but also for identifying hazardous substances and distinguishing between authentic and counterfeit Baijiu products. Full article

Surface-enhanced Raman scattering (SERS) holds significant potential across environmental monitoring, materials science, and biomedical applications. However, challenges regarding ultra-sensitive detection and repeatability are bottlenecks for practical applications, especially in terms of detection uniformity. In this study, we utilized surface acoustic waves (SAW) in conjunction with Raman spectroscopy to actively enrich 5 μL of 50 nm gold nanoparticles (AuNPs), thereby achieving innovative SERS-active sensing. This dynamic enrichment process enables the dense and uniform aggregation of AuNPs in droplets, thereby facilitating reliable ultrasensitive detection. The SAW system was further optimized through hydrophobic surface treatment. Using 4-mercaptobenzoic acid as a probe analyte, our SAW-SERS method successfully detected concentrations as low as 10⁻⁸ mol/L. The surface acoustic waves had the capability to significantly amplify Raman signal intensity up to 100 compared to conventional drying methodologies. This SAW-induced AuNP clustering technology offers a rapid, label-free SERS sensing method characterized by exceptional sensitivity and uniformity. Full article

Anisotropic plasmonic nanoparticles usually generate SERS enhancement factors that are significantly larger than those generated by spherical plasmonic nanostructures, so the former are usually preferred as substrates for SERS measurements. Gold nanorods are one of the most commonly used anisotropic nanomaterials for SERS experiments. Unfortunately, even a slight contamination of the surfactant used in the process of the synthesis of gold nanorods has a significant impact on the geometry of the resulting nanostructures. In this work, using easily formed silver nanorods as templates, hollow AuAg nanorods are formed by means of a silver–gold galvanic exchange reaction (in this process, nanostructures with a cavity inside form because one gold atom replaces three silver atoms). Hollow AuAg nanorods are highly active during SERS measurements—for shorter wavelengths of the excitation radiation, they display greater SERS activity than Au nanorods. To our knowledge, this is the first example of the use of hollow plasmonic nanorods for SERS measurements. Elemental mapping of the rods showed that the silver, some of which remained after the galvanic replacement, is mainly located close to the internal cavity that was formed, whereas the gold is mainly located at the outermost regions of the nanostructure. This explains the high chemical stability of these nanostructures. Full article

Background: Heracleum sphondylium, a medicinal plant used in Romanian ethnopharmacology, has been proven to have remarkable biological activity. The escalating concerns surrounding antimicrobial resistance led to a special attention being paid to new efficient antimicrobial agents based on medicinal plants and nanotechnology. We report the preparation of a novel, simple phytocarrier that harnesses the bioactive properties of H. sphondylium and silver nanoparticles (HS-Ag system). Methods: H. sphondylium’s low metabolic profile was determined through gas chromatography–mass spectrometry and electrospray ionization–quadrupole time-of-flight–mass spectrometry. The morphostructural properties of the innovative phytocarrier were analyzed by X-ray diffraction, Fourier-transform infrared spectroscopy, Raman spectroscopy, dynamic light scattering, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The antioxidant activity was evaluated using total phenolic content, ferric reducing antioxidant power, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) in vitro assays. The antimicrobial activity screening against Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa, and Escherichia coli was conducted using the agar well diffusion method. The 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay estimated the in vitro potential cytotoxicity on normal human dermal fibroblasts (NHDF) and cervical cancer (HeLa) cells. Results: A total of 88 biomolecules were detected, such as terpenoids, flavonoids, phenolic acids, coumarins, phenylpropanoids, iridoids, amino acids, phytosterols, fatty acids. The HS-Ag phytocarrier heightened efficacy in suppressing the growth of all tested bacterial strains compared to H. sphondylium and exhibited a significant inhibition of HeLa cell viability. Conclusions: The new HS-Ag phytocarrier system holds promise for a wide range of medical applications. The data confirm the capacity to augment the pertinent theoretical understanding in the innovative field of antimicrobial agents. Full article

Raman spectroscopy provides detailed information about the molecular composition of a sample. The classical identification of components in a multi-component sample typically involves comparing the preprocessed spectrum with a known reference stored in a database using various spectral matching or machine-learning techniques or relies on universal models based on a two-step analysis including first, the component identification, and then the decomposition of the mixed signal. However, although large databases and universal models cover a wide range of target materials, they may be not optimized to the variability required in a specific application. In this study, we propose a single-step method using deep learning (DL) modeling to decompose a simulated mixture of real measurements of Raman scattering into relevant individual components regardless of noise, baseline and the number of components involved and quantify their ratios. We hypothesize that training a custom DL model for applications with a fixed set of expected components may yield better results than applying a universal quantification model. To test this hypothesis, we simulated 12,000 Raman spectra by assigning random ratios to each component spectrum within a library containing 13 measured spectra of organic solvent samples. One of the DL methods, a fully connected network (FCN), was designed to work on the raw spectra directly and output the contribution of each component of the library to the input spectrum in form of a component ratio. The developed model was evaluated on 3600 testing spectra, which were simulated similarly to the training dataset. The average component identification accuracy of the FCN was 99.7%, which was significantly higher than that of the universal custom trained DeepRaman model, which was 83.1%. The average mean absolute error for component ratio quantification was 0.000562, over one order of magnitude smaller than that of a well-established non-negative elastic net (NN-EN), which was 0.00677. The predicted non-zero ratio values were further used for component identification. Under the assumption that the components of a mixture are from a fixed library, the proposed method preprocesses and decomposes the raw data in a single step, quantifying every component in a multicomponent mixture, accurately. Notably, the single-step FCN approach has not been implemented in the previously reported DL studies. Full article

In order to achieve low-cost scalability, the same-wavelength bidirectional (SWB) fiber communication system is a better solution. We present a detailed investigation of the performance of the different orders Raman amplifiers in same-wavelength bidirectional fiber communication systems. We discuss how to suppress the main factor affecting system performance which is Rayleigh scattering noise (RSN). By using different Raman amplifiers to construct different quasi-lossless transmission, the performance changes in the same-wavelength bidirectional fiber optic communication system were studied. On this basis, multi-channel and same-wavelength single fiber bidirectional system experiments were conducted to compare the performance of second-order Raman systems and first-order Raman systems. The results indicate that the Rayleigh scattering suppression effect of second-order Raman systems is better, and compared to first-order Raman systems, the average signal-to-noise ratio (SNR) can be increased by 2.88 dB. Full article

The use of multiple wavelengths to excite Titanium Dioxide Raman scattering in the near-infrared was investigated for optical nanothermometry. Indeed, Raman spectroscopy can be a very interesting technique for this purpose, as it offers non-disruptive contactless measurements with a high spatial resolution, down to a few µm. A method based on the ratio between the anti-Stokes and Stokes peaks of Anatase Titanium Dioxide was proposed and tested at three different wavelengths, 785, 800 and 980 nm, falling into the first biological transparency window (BTW-I). Using a temperature-controller stage, the temperature response of the sample was measured between 20 and 50 °C, allowing the thermal sensitivity for this range to be estimated. The use of sufficiently high laser power results in the generation of local heating. A proof of concept of the proposed thermometric method was performed by determining the extent of local heating induced by increasing laser power. By exciting with an 800 nm laser at low power intensities, a temperature equal to room temperature (RT) was found, while a maximum temperature increase of 15 °C was detected using the anti-Stokes/Stokes method. Full article

In this study, a MOF-199/Ag@Au SERS sensing structure was successfully synthesized by combining metal–organic frameworks (MOFs) with surface-enhanced Raman scattering (SERS) technology for the efficient detection of dopamine (DA), a biomarker for neurological diseases, in serum. Using electrochemical methods, a copper-based MOF (MOF-199) was synthesized in situ on copper substrates and further deposited with silver nanoparticles (AgNPs). Subsequently, gold nanoshells were encapsulated around these silver cores by in situ chemical deposition. This preparation process is simple, controllable, and inexpensive. Furthermore, a novel Azo reaction-based DA SERS method was proposed to detect 1 pM DA, which represents an improvement in sensitivity by two orders of magnitude compared to previous unlabeled SERS detection methods and by four orders of magnitude compared to another SERS approach proposed in this work. There was an excellent linear relationship (R² = 0.976) between the SERS signal at 1140 cm⁻¹ and the DA concentration (0.001 M~1 pM). The results indicate that the MOF-199/Ag@Au sensor structure can successfully achieve both the qualitative and quantitative detection of DA in serum, thus providing a robust technical basis for the application of SERS technology in the field of clinical neurological disease screening. Full article

In this work, Surface-Enhanced Raman Spectroscopy (SERS) was employed as an effective detection technique for folpet, characterized by its notable specificity and sensitivity. The investigation involved the use of UV–Vis, Raman, and SERS spectroscopy of folpet at different concentrations for a comprehensive study of plasmon-driven effects such as plasmon resonance, plasmon hybridization, and electric field enhancement resulting in the SERS’ intensification. Specifically, SERS detection of folpet solutions at concentrations below 100 µM is presented in detail by using Ag nanoparticles prepared with hydroxylamine reduction. The experimentation encompassed diverse conditions to optimize the detection process, with Raman spectra acquired for both folpet powder and aqueous solution of folpet at the natural pH. SERS analyses were conducted across a concentration range of 9.5 × 10⁻⁸ to 1.61 × 10⁻⁴ M, employing 532 nm excitation. The differences in the spectral profiles observed for folpet Raman powder and SERS are ascribed to N–S cleavage; these changes are attributed to plasmon catalysis induced by the used Ag nanoparticles. Transmission electron microscopy (TEM) was also important in the present analysis to better understand which mechanism of nanoparticles aggregation is more favorable for the SERS detection regarding the formation of hot spots in the suspension. Complementing the experimental data, the molecular structure and theoretical Raman spectra of the folpet molecule were calculated through density functional theory (DFT) methods. The outcomes of these calculations were crucial in the elucidation of folpet’s vibrational modes. The culmination of this research resulted in the successful detection of folpet, achieving a notable limit of detection at 4.78 × 10⁻⁸ M. This comprehensive approach amalgamates experimental and theoretical methodologies, offering significant insights into the detection capabilities and molecular characteristics of folpet via SERS analysis. Full article

Cyclodextrins (CDs) are macrocycles that are well suited for forming inclusion complexes for surface-enhanced Raman scattering (SERS) detection of analytes due to their low Raman activity, which minimizes background SERS signals and enhances the detection of target molecules without interference. In this paper, we systematically investigated the synthesis of both silver (Ag) and gold (Au) nanoparticles (NPs) using CDs as reducing and capping agents in a basic environment using microwave (MW), ultrasound (US), and room temperature (RT) synthesis. We found that replacing NaOH with K₂CO₃ as an alkaline environment almost doubles the size (from <10 nm to around 20 nm) of AgNPs in the MW-assisted synthesis. Synthesis using the US produces less stable particles due to the sample evolution after US irradiation. Ag (20 nm) and Au (11 nm) were successfully obtained at room temperature in the presence of CDs and K₂CO₃. All synthesized particles present SERS activity. CD capping allowed us to detect hydrophobic molecules like naphthalene and melamine. In the case of methylene blue, the CD capping prevents the changes induced in the SERS by a basic pH. We also demonstrate that the newly synthesized NPs can discriminate by SERS the propranolol enantiomers. Moreover, propranolol inclusion in CDs leads to a dramatic change in its SERS spectrum. Full article

Three-dimensional plasma nanostructures with high light–thermal conversion efficiency show the prospect of industrialization in various fields and have become a research hotspot in areas of light–heat utilization, solar energy capture, and so on. In this paper, a simple chemical synthesis method is proposed to prepare gold nanoparticles, and the electrophoretic deposition method is used to assemble large-area three-dimensional gold nanostructures (3D-GNSs). The light–thermal water evaporation monitoring and surface-enhanced Raman scattering (SERS) measurements of 3D-GNSs were performed via theoretical simulation and experiments. We reveal the physical processes of local electric field optical enhancement and the light–thermal conversion of 3D-GNSs. The results show that with the help of the efficient optical trapping and super-hydrophilic surface properties of 3D-GNSs, they have a significant effect in accelerating water evaporation, which was increased by nearly eight times. At the same time, the three-dimensional SERS substrates based on gold nanosphere particles (GNSPs) and gold nanostar particles (GNSTs) had limited sensitivities of 10⁻¹⁰ M and 10⁻¹² M to R6G molecules, respectively. Therefore, 3D-GNSs show strong competitiveness in the fields of solar-energy-induced water purification and the Raman trace detection of organic molecules. Full article

Raman spectroscopy with the advantages of the in situ and simultaneous detection of multi-components has been widely used in the identification and quantitative detection of gas. As a type of scattering spectroscopy, the detection sensitivity of Raman spectroscopy is relatively lower, mainly due to the low signal collection efficiency. This paper presents the design and assembly of a multi-channel cavity-enhanced Raman spectroscopy system, optimizing the structure of the sample pool to reduce the loss of the laser and increase the excitation intensity of the Raman signals. Moreover, three channels are used to collect Raman signals to increase the signal collection efficiency for improving the detection sensitivity. The results showed that the limits of detection for the CH₄, H₂, CO₂, O₂, and N₂ gases were calculated to be 3.1, 34.9, 17.9, 27, and 35.2 ppm, respectively. The established calibration curves showed that the correlation coefficients were all greater than 0.999, indicating an excellent linear correlation and high level of reliability. Meanwhile, under long-time integration detection, the Raman signals of CH₄, H₂, and CO₂ could be clearly distinguished at the concentrations of 10, 10, and 50 ppm, respectively. The results indicated that the designed Raman system possesses broad application prospects in complex field environments. Full article

Surface-Enhanced Raman Spectroscopy (SERS) is a powerful, non-destructive technique for enhancing molecular spectra, first discovered in 1974. This study investigates the enhancement of Raman signals from single- and few-layer molybdenum disulfide (MoS₂) when interacting with silver nanoparticles. We synthesized a MoS₂ membrane primarily consisting of monolayers and bilayers through a wet chemical vapor deposition method using metal salts. The silver nanoparticles were either directly grown on the MoS₂ membrane or placed beneath it. Raman measurements revealed a significant increase in signal intensity from the MoS₂ membrane on the silver nanoparticles, attributed to localized surface plasmon resonances that facilitate SERS. Our results indicate that dichalcogenide/plasmonic systems have promising applications in the semiconductor industry. Full article