High Surface Enhanced Raman Spectroscopy Research Articles

High sensitive setup of gold nanorods substrates for explosives detection using surface enhanced Raman spectroscopy

Surface enhanced Raman spectroscopy (SERS) is a sensitive analytical technique that has been widely utilised for detection of trace levels of organic species. The detection of trace levels of poor vapour pressure molecules such as explosives is a critical challenging due to the low concentration of adsorbed molecules on the surface sites of the SERS substrate. In this work, gold nanorods were fabricated with analyte samples and provided highly sensitivity of SERS detection along with low limit-of-detection (LOD) for explosives down to pM of 2,4- dinitrotoluene (DNT) and nM of both 2,4,6-trinitrotoluene (TNT) and 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) with highly specificity. The sensitivity of the detection was developed by optimising the adsorption of the molecules on nanorods sites, where nanorods and analyte solution were mixed followed by rigorous stirring. This procedure allowed extra molecules to be adsorbed on the nanorods surface, thus, high SERS enhanced has been observed with high specific identification of target probes. This approach showed a powerful method for rapid detection of explosives based SERS technique especially for illicit samples, where the enhancement factor calculated for analytes was in the range 3.17×108 to 2.69×1011.

Single AgNF@ZIF-8 nanoparticle for deep learning assisted SERS detection of gaseous molecule

Random nanogaps between plasmonic nanoparticles formed by the surface tension of solution bring a great challenge in the application of Surface Enhanced Raman Spectroscopy (SERS) technique. Meanwhile, due to its natural nanogaps on the surface, single plasmonic nanoflower exhibits a unique charm for avoiding random gaps in the quantitative analysis of SERS. Herein, a single core-shell plasmonic nanoparticle consisting of an Ag nanoflower (AgNF) core and zeolite imidazolate frame-8 (ZIF-8) shell is synthesized for SERS detection of the gaseous molecule. Benefiting the porous shell of ZIF-8 to capture gaseous molecules and natural nanogaps on the surface of AgNF to enhance Raman intensity, SERS spectra of the gaseous molecule are successfully collected with high sensitivity at 10−6 M, which also exhibit high SERS stability with RSD at 2.29 % for single nanoparticle and 9.86 % for multiple single nanoparticles. In addition, two levels of automatic identification based on deep learning (DL) are also implemented in this work, whose data demonstrate artificial neural network (ANN) algorithm could identify gaseous glutaraldehyde (GA) as typical volatile organic compounds (VOCs) with high accuracy at 97.5 %. This single core-shell plasmonic MOF nanoparticle overcomes the limitations of traditional SERS detection in nanoparticle aggregating and realizes the detection of gaseous molecules, which enlarges the application of SERS technique.

Application of high sensitive silver nanocubes SERS substrate for detection of metribuzin

Metribuzin, which is a triazinone herbicide, is extensively used in agricultural activities in order to control the spread of broad leaved weeds and grasses. This herbicide is treated as a hazardous chemical, since it multiplies the contamination in the ecosystem by infiltrating to groundwater and soil layers. Thus, detection of Metribuzin in even low concentrations is of vital importance. To date, analytical methods such as High Performance Liquid Chromatography (HPLC), reversed-phase thin-layer chromatography (RP-TLC) with UV absorption detection, Gas chromatography, and Mass spectrometry were utilized in order to detect Metribuzin. At this point, Surface Enhanced Raman Spectroscopy (SERS), while being not as analytical as the methods discussed above, emerges as a significant alternative, since it requires almost no consumables, requires a very short time for analysis and it allows on site analysis. In this study Ag nanocubes were synthesized as a SERS substrate and They were utilized for detection of Metribuzin at concentrations from 10−3 to 10−10 M. Reproducibility, sensitivity and chemical stability tests exhibited that Ag nanocubes were excellent candidates of SERS substrates by allowing detection at ultra- low concentrations up to 10−10 M.

SERS-active substrates using DVD-R coated in silver thin films: A preliminary study for detection of commercial glyphosate

Glyphosate (GLP) is the herbicide with the highest level of global commercialization and historical use. Even though numerous studies have found this substance to be harmless, current research demonstrates that GLP might affect human health. For this reason, researcher efforts are concentrating on alternatives for analytical quantification, such as Surface Enhanced Raman Spectroscopy (SERS). In this work, a DVD-R@AgNPs SERS substrate was produced by the Cathodic Cage Plasma Deposition (CCPD) technique, which allowed a thin film layer deposition of silver nanoparticles (AgNPs) on the PC grating structure from Digital Video/Versatile Disc Recordable (DVD-R). Scanning Electron Microscopy with energy-dispersive X-ray spectroscopy was used to characterize the substrate and chemical changes on the surface after AgNPs deposition. The DVD-R@AgNPs substrate was used to detect standard crystal violet (CV), GLP, and RoundupTM GLP (GLP-RU) using Raman Spectroscopy. The CV was used as a control sample for SERS measurement, allowing the calculation of the substrate enhancement factor, which was in the order of ∼ 105. To evaluate the efficiency of the SERS substrate, the limit of detection was calculated and showed values of ∼ 10-10 mol/L for CV, 10-7 and 10-8 mol/L for GLP, and 10-6 mol/L for GLP-RU. Thus, the DVD-R@AgNPs SERS sensor is a low-cost substrate that analyzes traces of pesticides such as commercial GLP, demonstrating high SERS sensitivities and many applications.

Dramatically enhanced SERS and photocatalytic performances over a portable Ag nanoparticles anchored flower-like metal-organic frameworks induced by TiO2/Zn sheet

Aimed at obtaining a new type of bi-functional materials for highly efficient surface enhanced Raman spectroscopy (SERS) detection and photocatalytic degradation of organic pollutants, a low content of Ag nanoparticles (0.5 wt. % Ag) anchored flower-like 2-methylimidazole zinc metal organic frameworks (ZIF-8) induced by TiO2/Zn sheet was facilely constructed without adding any reductants or UV-light reduction. With p-aminothiophenol (PATP, a typical pesticide) as an analyte, SERS and photocatalytic degradation performances of the resulting Zn/TiO2/ZIF-8/Ag (Zn-TZA) sheet were evaluated. The cost-effective Zn-TZA sheet exhibited high SERS activity and excellent stability towards PATP detection, and its detection limit can reach 1 × 10-11 M. In addition, the Zn-TZA sheet showed high and stable photocatalytic performance for PATP degradation. In particularly, by means of the plug and play Zn-TZA, the detection and degradation of PATP in real samples can also be effectively achieved. The strong coupling and electron transfer among Ag NPs, TiO2/Zn, and ZIF-8 in the Zn-TZA sheet were very advantageous to enhancing the bi-functionality. Additionally, the increased enrichment of PATP on the special sheet was also an important factor for the enhanced bi-functionality. It will provide new ideas for designing competitive bi-functional materials that are used to detect and degrade organic poisons in waste water.

The Functional Fe3O4@SiO2@AuNPs SERS Nanomaterials for Rapid Enrichment and Detection of Mercury Ions in Licorice

There has been an increasing demand for rapid and sensitive techniques for the detection of heavy metal ions that are harmful to the human body in traditional Chinese medicine (TCM). However, the complex chemical composition of TCM makes the quantitative detection of heavy metal ions difficult. In this study, the magnetic Fe3O4@SiO2@AuNPs nanoparticles combined with a probe molecule DMcT were used for the specific enrichment and detection of Hg2+ in the complex system of licorice. The core of Fe3O4 was bonded with SiO2 to increase its stability. A layer of AuNPs was deposited to produce a “core–shell” Raman substrate with high surface-enhanced Raman spectroscopy (SERS) activity, which was surface modified by DMcT probe molecules with sulfhydryl groups. In the presence of Hg2+, Hg2+ binds to N on the amino group of DMcT to form N-Hg2+-N complexes, which induces Fe3O4@SiO2@AuNPs-DMcT clustering to enhance SERS signal. The Raman probe molecule DMcT showed an excellent linear relationship (R2 = 0.9709) between the SERS signal at 1416 cm−1 and the Hg2+ concentration (0.5~100 ng/mL). This method achieved a good recovery (89.10~111.00%) for the practical application of detection of Hg2+ in licorice extracts. The results demonstrated that the functional Fe3O4@SiO2@AuNPs-DMcT performed effective enrichment and showed high sensitivity and accurate detection of heavy metal ions from the analytes.

Label-free therapeutic drug monitoring in human serum by the 3-step surface enhanced Raman spectroscopy and multivariate analysis

Surface enhanced Raman spectroscopy (SERS) is widely used in drug molecular detection. However, SERS detections of drug molecules in serum with high sensitivity and reproducibility remains extremely challenging due to signal interference of complex constituents of serum. The latter presents a high SERS background noise that buries the signals of the drug molecules. Here, we report a 3-step method to make SERS system of silver nanoparticle clusters to overcome the interference and achieve quantitative SERS analysis of drugs in serum by 1) proteins removal from serum; 2) enhanced drug adsorption on the nanoparticles; and 3) background suppression by internal standard in nanoparticle aggregation. By careful selection of the aggregation agents and internal standard, clear SERS peaks of the internal standard and six different drug analytes were observed for pesticide identification in human serum. Significantly, the SERS peak ratio of the internal stardard and drug analytes has achieved univariate quantitative monitoring of drug metabolism in mice serum, which is in agreement with analysis by the multivariate curve resolution-alternating least squares method. Our method shows great clinical application potential in therapeutic drug monitoring and personalized medicine.

Determination of blood species using echelle Raman spectrometer and surface enhanced Raman spectroscopy

Blood species identification of human and animals has attracted much attention in the areas of customs inspection and forensic science. The combination of vibrational spectroscopy and machine learning has been proven to be feasible and effective for this purpose. However, the popularization of this technology needs instrument which is compact, robust and more suitable for field application. Besides the quantity of the blood sample should be as little as possible. In this study, we proposed a system using echelle Raman spectrometer combined with surface enhanced Raman spectroscopy (SERS), which protocol combines the advantages of broadband and high resolution of echelle Raman spectrometer with the advantages of high SERS spectral sensitivity. The SERS spectra of 26 species including human were collected with echelle Raman spectrometer, and the convolutional neural network was used for species identification, with an accuracy rate of over 94%. The feasibility, validity and reliability of the combination of echelle Raman spectrometer and SERS for blood species identification were realized.

Ultrasensitive SERS substrates based on Au nanoparticles photo-decorated on Cu2O microspheres for the detection of rhodamine B and methylene blue

Integrating noble-metal and semiconductor nanomaterials for Raman signal enhancement is of great significance in the field of surface enhanced Raman spectroscopy (SERS). In this work, a SERS-active substrate composed of Au nanoparticles (NPs) on Cu2O microspheres is produced by the polyol and photochemical methods for the effective detection of organic dye molecules, rhodamine B (RhB) and methylene blue (MB). The formation of Au/Cu2O nanostructure is confirmed by X-ray diffraction, field emission scanning electron microscopy , elemental mapping and UV-Vis spectroscopy. The proposed heterogeneous nanomaterials have high SERS activity by the synergistic interaction among Au NPs, Cu2O microspheres and organic dye molecules through electromagnetic and chemical mechanisms. The photochemical parameter for the growth of Au NPs and Cu2O microspheres is optimized by elevating the SERS signal intensity to high extent. The measured analytical enhancement factors (AEFs) are as high as 2.55 × 1012 for RhB and 1.2 × 1011 for MB. The corresponding limits of detection (LOD) are 2.36 × 10-13 M for RhB and 3.40 × 10-12 M for MB. The reproducibility and the uniformity with the relative standard deviation (RSD) < 10% confirm the superiority of the proposed SERS substrate. The real-sample analysis of RhB in the chili solution and MB in the pond water gives the satisfactory recovery values > 87.8%. This reliable and facile production approach is practically applicable to produce SERS-active substrates in various real applications.

Real-time validation of Surface-Enhanced Raman Scattering substrates via convolutional neural network algorithm

Development of next-generation sensor technologies could be advanced by exploiting surface enhanced Raman spectroscopy (SERS) substrates capable of considerably enhancing signal detection of analytes of interest down to single molecule levels. The widespread implementation of SERS, however, requires overcoming many of the existing and emerging challenges related to the enhancement inconsistency from the different parts of substrates, resulting in inconsistent readings. Here, a custom-designed convolutional neural networks (CNN) algorithm is developed to specifically analyse and validate substrates in real-time, providing a rapid output and identification of SERS active structures on each substrate enabling a consistently high signal enhancement. A computational algorithm has been developed to identify regions of high and consistent SERS activity from acquired optical microscopy images of SERS structures in real-time. The CNN model is tested on the inputted optical images and outputs the predicted consistent SERS-active structures or regions overlaid on top of the input image. The optimised CNN model used is a pre-trained neural network (VGG16) with the last layers fine-tuned. This model achieves an accuracy of 90% in classifying our uniquely developed electrohydrodynamically (EHD) fabricated, highly enhancing, SERS-active structures from optical images, enabling a real-time predictive tool for SERS substrates. The CNN output generates a heatmap, which provides feedback on the regions of high SERS activity, overlaid on the optical image to rapidly facilitate the SERS spectral acquisition measurements. Beyond its application for EHD, the versatility of the developed method renders it easily extendable for implementation with further, current and future, fabrication techniques of SERS substrates. The full script run yields an accuracy of 87.5 ± 12.0% for in-situ measurement acquisition, successfully demonstrating a proof-of-concept of rapidly identifying consistent SERS structures via the real-time CNN processing of optical images.

Flexible hydrophobic filter paper-based SERS substrate using silver nanocubes for sensitive and rapid detection of adenine

Flexible paper-based surface enhanced Raman spectroscopy (SERS) substrate has attracted great attention in the sensitive detection of analytes in recent years. However, due to its inherent hydrophilic surface, the nanoparticles will not be concentrated very well on the surface of the paper. This reduces the reproducibility and sensitivity of the paper-based substrate. Herein, we demonstrate flexible hydrophobic paper-based substrate using silver nanocubes loaded on polymethylhydrosiloxane modified filter paper (AgNCs@SiO2/PMHS modified filter paper) to realize high sensitivity and reproducibility. The hydrophobic filter paper was obtained by dip-soaking the filter paper into PMHS solution, resulting in increased contact angle to ~112.5°. The AgNCs@SiO2/PMHS modified paper substrate shows high analytical enhancement factor (AEF) of 6.55 × 106, which is 2.2-fold enhancement compared to AgNCs@SiO2/normal paper substrate, and a low detection limit of 0.1 nM rhodamine 6G and 0.89 nM adenine. The high SERS enhancement factor and sensitivity is attributed to the high hotspots density created in the hydrophobic surface as a result of the excellent uniformity and superior sample collection efficiency compared to the normal filter paper-based substrate. Besides, the substrate shows excellent spot-to-spot and substrate-to-substrate reproducibility, with relative standard deviation (RSD) of 6.05% and 9.22%, respectively. Moreover, the AgNCs@SiO2/PMHS modified filter paper substrate achieved good stability; the Raman signal intensity only drops by 25.88% after 3 months of exposure to air. Therefore, this flexible hydrophobic AgNCs@SiO2/PMHS modified filter paper substrate with low cost fabrication and label-free SERS detection is a promising SERS platform for analytical and biological sensing applications.

A high sensitive glucose sensor based on Ag nanodendrites/Cu mesh substrate via surface-enhanced Raman spectroscopy and electrochemical analysis

A high sensitive micro/nano-structured glucose sensor via Surface Enhanced Raman Spectroscopy (SERS) detection and electrochemical analysis was developed in this work. Ag nanodendrites/Cu mesh substrate were prepared through facile electrochemical deposition method, which exhibited high SERS sensitivity and electrocatalytic activity. By SERS measurements, glucose can be detected as low as 0.005 mM and exhibit a good linear relationship between concentrations (0.5–5 mM) and the SERS intensities. Moreover, glucose in human urine with different concentrations were successfully detected by the substates. By electrochemical method, the conductivity was firstly tested by CV and ESI tests. Amperometric responses of 0.5 mM glucose were compared with Cu mesh electrode, and the Ag nanodendrites/Cu mesh electrode showed higher electrochemical detection sensitivity. Results revealed the Ag nanodendrites/Cu mesh substrate can be used as glucose sensor with high detection sensitivity, reproducibility, selectivity and practicability, which has great potential in noninvasive medical diagnosis in further works.

Waveguide-based surface-enhanced Raman spectroscopy detection of protease activity using non-natural aromatic amino acids.

Surface enhanced Raman spectroscopy (SERS) is a selective and sensitive technique, which allows for the detection of protease activity by monitoring the cleavage of peptide substrates. Commonly used free-space based SERS substrates, however, require the use of bulky and expensive instrumentation, limiting their use to laboratory environments. An integrated photonics approach aims to implement various free-space optical components to a reliable, mass-reproducible and cheap photonic chip. We here demonstrate integrated SERS detection of trypsin activity using a nanoplasmonic slot waveguide as a waveguide-based SERS substrate. Despite the continuously improving SERS performance of the waveguide-based SERS substrates, they currently still do not reach the SERS enhancements of free-space substrates. To mitigate this, we developed an improved peptide substrate in which we incorporated the non-natural aromatic amino acid 4-cyano-phenylalanine, which provides a high intrinsic SERS signal. The use of non-natural aromatics is expected to extend the possibilities for multiplexing measurements, where the activity of several proteases can be detected simultaneously.

Ordered gold-coated glass nano-sting array with large density tips as highly SERS-active chips for detection of trace organophosphorous toxicant

A simple and cost-effective route to fabricating gold-coated glass nano-stings’ arrays is presented for highly efficient surface enhanced Raman spectroscopy (SERS) chips via reactive ion etching of the glass slide covered with polystyrene (PS) colloidal monolayer and sputtering deposition of gold on it. The as-fabricated SERS chips consist of the nearly-hemispherical particles with submicron-size, which are hexagonally arranged into the ordered arrays. There are many short and long Au-coated glass nano-stings standing vertically on the hemispherical particles, showing high density tips (up to 7.0 × 103 μm−2). The formation of such gold-coated glass hierarchically structured array is attributed to the geometry of PS colloidal monolayer and the nanoscale roughness of glass slide’s surface. Further, it has been demonstrated that such gold-coated glass array chip is highly SERS-active and can be utilized to detect trace organophosphorous toxicant with the limit below ppt level and good reproducibility in measurements. The intensity of the Raman peak shows the linear relation, in logarithmic scale, with the organophosphorous concentration from ppt to ppm level, exhibiting the possibility of quantitative detection in a large concentration range. This work has demonstrated the cost-effective method to fabricate the high performance SERS chips for trace detection of toxic molecules.

Electrofluidynamic Patterning of Tailorable Nanostructured Substrates for Surface-Enhanced Raman Scattering.

The unique attributes of surface enhanced Raman spectroscopy (SERS) make it well suited to address the challenges associated with portable diagnostics. However, despite the remarkable progress in this field, where the instrumentation has made great strides forward providing a route to the miniaturization of sensing devices, to date producing three-dimensional low-cost SERS substrates which simultaneously fulfill the multitude of criteria of high sensitivity, reproducibility, tunability, multiplexity, and integratability for rapid sensing has not yet been accomplished. Successful implementation of SERS requires readily fine-tuned nanostructures, which create a high enhancement. Here, an advanced electrofluidynamic patterning (EFDP) technique enables rapid fabrication of SERS active topographic morphologies with high throughput and at a nanoresolution via the spatial and lateral modulation of the dielectric discontinuity due to the high electric field generated across the polymer nanofilm and air gap. The subsequent formation of displacement charges within the nanofilm by coupling to the electric field yield a destabilizing electrostatic pressure and amplification of EFDP instabilities enabling the controllable pattern formation. The top of each gold coated EFDP fabricated pillar generates controllable high SERS enhancement by coupling of surface plasmon modes on top of the pillar, with each nanostructure acting as an individual sensing unit. The absolute enhancement factor depends on the topology as well as the tunable dimensions of the nanostructured units, and these are optimized in the design and engineering of the dedicated EFDP apparatus for reproducible, low-cost fabrication of the three-dimensional nanoarchitectures on macrosurfaces, rendering them for easy integration in further lab-on-a-chip devices. This unique combination of nanomaterials and nanospectroscopic systems lay the platform for a variety of applications in chemical and biological sensing.

Wrinkled 2H-phase MoS2 sheet decorated with graphene-microflowers for ultrasensitive molecular sensing by plasmon-free SERS enhancement

High surface-enhanced Raman spectroscopy (SERS) activity is ordinarily derived from noble-metal nanoarrays. In recent years, certain two-dimensional (2D) inorganic materials have become suitable for SERS. However, the limits of detection (LODs) of these plasmon-free materials are insufficient for meeting the requirements of molecular analysis. Herein, the centralization of the probe molecule pre-concentration process, and enhancement of interfacial interactions between the substrate and molecules were pivotal accomplishments in the development of a hetero-substrate comprised of a wrinkled semiconducting 2H-phase MoS2 (W-MoS2) platform decorated with graphene-microflowers (GMFs), for the achievement of noble-metal-comparable SERS detection. The GMFs served as supersized molecular enrichers, creating abundant SERS 'active regions', and thus, the LOD in the adsorption equilibrium state was 5 × 10−11 M for rhodamine B (RhB), and the maximum enhancement factor (EF) was 2.96 × 107. Additionally, performance degradation of GMFs/W-MoS2 was below 6 %, following long-term detection over 50 days. The sub-nanomolar sensitivity of the GMFs/W-MoS2 substrate can be attributed to the synergistic effects of the efficacious pre-concentration of probe molecules, enhanced charge-transfer, and multiple light scattering, all of which can promote the progress of plasmon-free SERS detection.

Precise cancer detection via the combination of functionalized SERS surfaces and convolutional neural network with independent inputs

Combining the advanced approaches of surface functionalization and chemistry, plasmonics, surface enhanced Raman spectroscopy (SERS), and machine learning, we propose the advanced route for express and precise recognition of normal and cancer cells. Our interdisciplinary approach uses plasmonic coupling between the specific nanoparticles and underlying periodical plasmonic surface and achieves high SERS enhancement factor. The surface of gold multibranched nanoparticles (AuMs) was functionalized with different chemical groups to achieve partially selective entrapping of biomolecules from cells cultivation media and generate information-rich inputs for machine learning methods and SERS-based cells recognition. Evaluation of convolutional neural networks (CNN) training results, performed with ad hoc feature selection method, suggests that the grafted functional groups provide specificity to proteins, nucleic acids and lipids, responsible for cancer line identification. The dataset of SERS control spectra of normal and cancer cell’s metabolites were classified by the trained CNN and perfectly distinguished with 100 % prediction accuracy.

Long-range ordered silver nanoflower array structure for surface enhanced Raman scattering detecting

Surface enhanced Raman spectroscopy (SERS) is a key nondestructive detecting technology with a broad application demands. However, relative low stability and homogeneity of the SERS substrate hinder its practical applications. Here, a simple and flexible approach is proposed to achieve the arrayed SERS substrates with the periodicity and local randomness by directly growing silver nanoflowers on the patterned wafer fabricated by the optical interference method. By utilizing the hotspot effect of nanogaps within/between the Ag nanoflowers, the SERS substrates demonstrate the low detecting limit of 5 × 10−10 M and 5 × 10−9 M in one-dimensional (1D) and two-dimensional (2D) pattern structures for Rhodamine 6G (R6G) probe molecule, respectively. The periodicity assures the fabricated substrate a promising reproducibility and stability. After the 1D array structure is left for 21 days, the intensity of Raman signal of R6G maintains at 80%. Moreover, the proposed method has the advantages of simple preparation, low cost, flexible tunability, and easy-fabrication large scale substrate. The results indicate that the long-range ordered silver nanoflower array structures are promising candidates for the high performance SERS substrate in chemical analysis, medicine and environment monitoring.

The shining brightness of daylight fluorescent pigments: Raman and SERS study of a modern class of painting materials

Raman and surface enhanced Raman spectroscopy (SERS) are established techniques allowing for fast and sensitive identification of dyes and pigments. To date, Raman has only limitedly been applied to the identification of daylight fluorescent pigments, despite this modern class of materials has been adopted by several significant artists (e.g. Frank Stella, Peter Halley, Andy Warhol, and Keith Haring).In this study, seven commercial daylight fluorescent pigments from Radiant were investigated by Raman and SERS spectroscopy. A new type of silver colloid, consisting mainly of rod-like silver nanostructures guaranteeing a high SERS enhancement, has been employed here for the first time in cultural heritage studies.As the number of fluorescent dyes suitable for the manufacturing of daylight fluorescent pigments is limited, these materials are often constituted by a mixture of dyes. Since SERS is not able to physically separate multiple dyes in mixtures, to reveal the complex composition of these materials the coupling of SERS with a separation technique proved to be mandatory. Thin-layer chromatography, being a cost-effective and fast procedure, was chosen for this purpose. The identification of each component was made possible by the comparison of SERS spectra from standard fluorescent dyes, thus increasing the available SERS database for modern materials.Lastly, the analytical protocol was applied to a modern artwork called “Rosso verde nero”, made in 1968 by the Italian artist Carla Accardi, who used to paint on plastic surfaces with fluorescent colours.

Cu/Ag Sphere Segment Void Array as Efficient Surface Enhanced Raman Spectroscopy Substrate for Detecting Individual Atmospheric Aerosol.

Surface enhanced Raman spectroscopy (SERS) shows great promise in studying individual atmospheric aerosol. However, the lack of efficient, stable, uniform, large-array, and low-cost SERS substrates constitutes a major roadblock. Herein, a new SERS substrate is proposed for detecting individual atmospheric aerosol particles. It is based on the sphere segment void (SSV) structure of copper and silver (Cu/Ag) alloy. The SSV structure is prepared by an electrodeposition method and presents a uniform distribution, over large 2 cm2 arrays and at low cost. The substrate offers a high SERS enhancement factor (due to Ag) combined with lasting stability (due to Cu). The SSV structure of the arrays generates a high density of SERS hotspots (1.3 × 1014/cm2), making it an excellent substrate for atmospheric aerosol detection. For stimulated sulfate aerosols, the Raman signal is greatly enhanced (>50 times), an order of magnitude more than previously reported substrates for the same purpose. For ambient particles, collected and studied on a heavy haze day, the enhanced Raman signal allows ready observation of morphology and identification of chemical components, such as nitrates and sulfates. This work provides an efficient strategy for developing SERS substrate for detecting individual atmospheric aerosol.