Raman Spectroscopy Signal Research Articles

Deep Learning for Chondrogenic Tumor Classification through Wavelet Transform of Raman Spectra.

The grading of cancer tissues is still one of the main challenges for pathologists. The development of enhanced analysis strategies hence becomes crucial to accurately identify and further deal with each individual case. Raman spectroscopy (RS) is a promising tool for the classification of tumor tissues as it allows us to obtain the biochemical maps of the tissues under analysis and to observe their evolution in terms of biomolecules, proteins, lipid structures, DNA, vitamins, and so on. However, its potential could be further improved by providing a classification system which would be able to recognize the sample tumor category by taking as input the raw Raman spectroscopy signal; this could provide more reliable responses in shorter time scales and could reduce or eliminate false-positive or -negative diagnoses. Deep Learning techniques have become ubiquitous in recent years, with models able to perform classification with high accuracy in most diverse fields of research, e.g., natural language processing, computer vision, medical imaging. However, deep models often rely on huge labeled datasets to produce reasonable accuracy, otherwise occurring in overfitting issues when the training data is insufficient. In this paper, we propose a chondrogenic tumor CLAssification through wavelet transform of RAman spectra (CLARA), which is able to classify with high accuracy Raman spectra obtained from bone tissues. CLARA recognizes and grades the tumors in the evaluated dataset with accuracy by exploiting a classification pipeline consisting of the division of the original task in two binary classification steps, where the first is performed on the original RS signals while the latter is accomplished through the use of a hybrid temporal-frequency 2D transform.

Gold Nanoparticle-Bridge Array to Improve DNA Hybridization Efficiency of SERS Sensors.

The interfacial mass transfer rate of a target has a significant impact on the sensing performance. The surface reaction forms a concentration gradient perpendicular to the surface, wherein a slow mass transfer process decreases the interfacial reaction rate. In this work, we self-assembled gold nanoparticles (AuNPs) in the gap of a SiO2 opal array to form a AuNP-bridge array. The diffusion paths of vertical permeability and a microvortex effect provided by the AuNP-bridge array synergistically improved the target mass transfer efficiency. As a proof of concept, we used DNA hybridization efficiency as a research model, and the surface-enhanced Raman spectroscopy (SERS) signal acted as a readout index. The experimental verification and theoretical simulation show that the AuNP-bridge array exhibited rapid mass transfer and high sensitivity. The DNA hybridization efficiency of the AuNP-bridge array was 15-fold higher than that of the AuNP-planar array. We believe that AuNP-bridge arrays can be potentially applied for screening drug candidates, genetic variations, and disease biomarkers.

Background-penalty-free waveguide enhancement of CARS signal in air-filled anti-resonance hollow-core fiber.

We study coherent anti-Stokes Raman spectroscopy in air-filled anti-resonance hollow-core photonic crystal fiber, otherwise known as "revolver" fiber. We compare the vibrational coherent anti-Stokes Raman signal of N2, at ∼2331 cm-1, generated in ambient air (no fiber present), with the one generated in a 2.96 cm of a revolver fiber. We show a ∼170 times enhancement for the signal produced in the fiber, due to an increased interaction path. Remarkably, the N2 signal obtained in the revolver fiber shows near-zero non-resonant background, due to near-zero overlap between the laser field and the fiber cladding. Through our study, we find that the revolver fiber properties make it an ideal candidate for the coherent Raman spectroscopy signal enhancement.

Comparative screening the life-time composition and crystallinity variation in gilthead seabream otoliths Sparus aurata from different marine environments

Differences in crystallinity, structure and composition variation along the growing direction in gilthead seabream, Sparus aurata otoliths that inhabited different environments were determined to evaluate the correlation of spectroscopic and chemical data with the lifetime development and movement pattern. The Raman spectroscopy signal provided the characteristic bands whose Full Width at Half Maximum (FWHM) were used to track the signal variability. The FWHM showed an initial increase in the core area, followed by a decrease depicting two minima coinciding growth rings. The crystal discontinuity linked to annual rings was confirmed. The FWHM pattern followed cycle in the individual’s activity. However, no significant correlation with FWHM and environmental factors although the slope of the FWHM variation distinguished aquaculture and costal groups from open sea and transitional, estuarine waters. Raman data were further correlated with morphological and elemental composition obtained via SEM–EDX and by LA-ICP-MS. SEM clearly confirmed CRM findings. Finally, multiparameter analysis of Ba/Ca concentrations obtained by LA-ICP-MS indicated the separation of groups associated with aquaculture and transitional waters due lowest variability in the elemental composition. Other groups are more variable possibly due to the water oligotrophic character and greater variability in prey availability in each environment. Results of the present study showed the additional potential of Raman spectroscopy as a complementary tool for inference of migration or origin of fish based on otolith composition and structure like other well-established technique.

Development of a Handheld System for Liquor Authenticity Detection Based on Laser Spectroscopy Technique

In this paper, a handheld liquor authenticity detection system is demonstrated based on the laser spectroscopy technique, which consists of a handheld laser spectrometer and a mobile phone display terminal. In this system, the semiconductor laser is integrated into the spectrometer and the laser beam is further angled to the optical axis of the spectrometer to avoid interference of the fluorescence generated by the bottle wall. During the system operation, the laser excites the tested liquor to generate fluorescence and Raman spectroscopy signals, which are digitized and wirelessly transmitted by Wi-Fi to the Android mobile terminal. After the image processing by the mobile phone APP, the tested liquor spectrum curve is obtained. At the same time, based on the standard liquor spectrum curve stored in the database, the Pearson correlation coefficient is calculated and the matching similarity is given. In addition, this paper proposes a calibration method based on pure water Raman intensity to achieve accurate measurement of fluorescence intensity and minimize the influence of fluorescence intensity saturation on the measurement results. In the experiment, we measured the similarity of 12 brands of Chinese liquor by using our self-developed handheld laser spectrometer. Their authenticity of liquor could be given accurately and effectively.

Review on All-Fiber Online Raman Sensor with Hollow Core Microstructured Optical Fiber

Raman spectroscopy is widely used for qualitative and quantitative analysis of trace components in scientific fields such as food safety monitoring, drug testing, environmental monitoring, etc. In addition to its demonstrated advantages of fast response, non-destructive, and non-polluting characteristics, fast online Raman detection is drawing growing attention for development. To achieve this desirable capability, hollow core optical fibers are employed as a common transmission channel for light and fluid in the Raman sensor. By enhancing the interaction process between light and matter, the detection sensitivity is improved. At the same time, the Raman spectroscopy signal light collection efficiency is significantly improved. This article summarizes enhancement techniques reported for Raman sensors, followed by a detailed review on fiber-based Raman sensor techniques including theoretical analyses, fabrication, and application based on hollow core photonic crystal fibers and capillary-based hollow core fibers. The prospects of using these fibers for Raman spectroscopy are discussed.

Plasmonic Superlattice Membranes Based on Bimetallic Nano-Sea Urchins as High-Performance Label-Free Surface-Enhanced Raman Spectroscopy Platforms.

On the basis of an abundance of elemental plasmonic nanocrystals identifiable by their unique morphology and intrinsic optoelectronic properties, it is necessary to rationally tailor the structural parameters to optimize the functionalities of nanoassemblies for application as plasmonic circuits/devices. Among them, the plasmonic superlattice membrane has emerged as a novel optically active metamaterial, which is constructed by nanocrystals at a two-dimensional (2D) plane with a highly ordered structure and strong plasmonic coupling interactions. Here, we report on the fabrication of a novel plasmonic superlattice membrane using bimetallic core-shell nano-sea urchins (Nano-SEUs) as meta-atoms. Under the guidance of soft-ligand balancing in conjugation with drying-mediated self-assembly at the air/water interface, well-defined giant 2D superlattices with total lateral dimensions of up to 5 mm wide and 80 nm thick have been synthesized, corresponding to an aspect ratio of 62 500. Programmable morphology control over the Nano-SEUs has been achieved in high yield by rationally tuning the spiky branches as well as the thickness of the silver shell, allowing systematic variation of the plasmonic properties of the membrane. Such superlattice membranes exhibited a strong and reproducible surface-enhanced Raman spectroscopy (SERS) signal that originates from interparticle coupling and electric (E)-field enhancement, enabling an enhancement factor of up to 106. We also demonstrated that the fabricated membrane allows the label-free SERS detection of dopamine from 0.1 nM to 1 μM. Thus, this giant Nano-SEU assembled superlattice membrane can be used as a SERS substrate for on-spot biomarker detection, which paves a robust and inexpensive avenue for highly sensitive and reliable biomedical sensing and diagnostics.

Physically unclonable functions taggant for universal steganographic prints

Counterfeiting of financial cards and marketable securities is a major social problem globally. Electronic identification and image recognition are common anti-counterfeiting techniques, yet they can be overcome by understanding the corresponding algorithms and analysis methods. The present work describes a physically unclonable functions taggant, in an aqueous-soluble ink, based on surface-enhanced Raman scattering of discrete self-assemblies of Au nanoparticles. Using this stealth nanobeacon, we detected a fingerprint-type Raman spectroscopy signal that we clearly identified even on a business card with a pigment mask such as copper-phthalocyanine printed on it. Accordingly, we have overcome the reverse engineering problem that is otherwise inherent to analogous anti-counterfeiting techniques. One can readily tailor the ink to various information needs and application requirements. Our stealth nanobeacon printing will be particularly useful for steganography and provide a sensitive fingerprint for anti-counterfeiting.

HPTLC screening of saccharin in beverages by densitometry quantification and SERS confirmation.

As a widely used artificially synthesized sweetener, saccharin faced numerous disputes associated with food safety. Therefore, its fast analysis in food is of crucial importance. In this study, an analytical method for the fast and reliable screening of saccharin in various beverages was established and validated, by combining HPTLC with densitometry and surface enhanced Raman spectroscopy. The diluted sample liquid was directly sprayed and separated on a silica gel plate using a mixture of ethyl acetate and acetic acid in the ratio of 9 : 1 (v/v) as the mobile phase. The separation realized full isolation of the analyte from background noises. Then, a densitometry analysis in the absorption–reflection mode (working wavelength 230 nm) was optimized to obtain quantitative data, showing a good linearity in the range of 40–200 ng per band (R2 = 0.9988). The limits of detection and quantification were determined to be 6 and 20 ng per band, respectively, which were equal to 6 and 20 mg kg−1. The quantitative results also displayed satisfactory accuracy and precision, with a spike-recovery rate within 87.75–98.14% (RSD <5.13%). As a cost-efficient tool for confirmation, surface enhanced Raman spectroscopy was employed to profile the molecular fingerprint of the analyte eluted from the plate layer. Under optimized conditions (785 nm laser as the excitation light and silver nanoparticle loaded glass fiber paper as the active substrate), the elution of the saccharin band exhibited stable and sensitive surface enhanced Raman spectroscopy signals. This study demonstrated that HPTLC could be a versatile platform for food analysis, with outstanding simplicity and cost-efficiency.

Rapid and Simple Analysis of the Human Pepsin Secondary Structure Using a Portable Raman Spectrometer.

Human pepsin is a digestive protease that plays an important role in the human digestive system. The secondary structure of human pepsin determines its bioactivity. Therefore, an in-depth understanding of human pepsin secondary structure changes is particularly important for the further improvement of the efficiency of human pepsin biological function. However, the complexity and diversity of the human pepsin secondary structure make its analysis difficult. Herein, a convenient method has been developed to quickly detect the secondary structure of human pepsin using a portable Raman spectrometer. According to the change of surface-enhanced Raman spectroscopy (SERS) signal intensity and activity of human pepsin at different pH values, we analyze the change of the human pepsin secondary structure. The results show that the content of the β-sheet gradually increased with the increase in the pH in the active range, which is in good agreement with circular dichroism (CD) measurements. The change of the secondary structure improves the sensitivity of human pepsin SERS detection. Meanwhile, human pepsin is a commonly used disease marker for the noninvasive diagnosis of gastroesophageal reflux disease (GERD); the detection limit of human pepsin we obtained is 2 μg/mL by the abovementioned method. The real clinical detection scenario is also simulated by spiking pepsin solution in saliva, and the standard recovery rate is 80.7-92.3%. These results show the great prospect of our method in studying the protein secondary structure and furthermore promote the application of SERS in clinical diagnosis.

Hybrid Metal-Dielectric-Metal Sandwiches for SERS Applications.

The development of efficient plasmonic nanostructures with controlled and reproducible surface-enhanced Raman spectroscopy (SERS) signals is an important task for the evolution of ultrasensitive sensor-related methods. One of the methods to improving the characteristics of nanostructures is the development of hybrid structures that include several types of materials. Here, we experimentally investigate ultrathin gold films (3–9 nm) near the percolation threshold on Si/Au/SiO2 and Si/Au/SiO2/graphene multilayer structures. The occurring field enhanced (FE) effects were characterized by a recording of SERS signal from Crystal Violet dye. In this geometry, the overall FE principally benefits from the combination of two mechanisms. The first one is associated with plasmon excitation in Au clusters located closest to each other. The second is due to the gap plasmons’ excitation in a thin dielectric layer between the mirror and corrugated gold layers. Experimentally obtained SERS signals from sandwiched structures fabricated with Au film of 100 nm as a reflector, dielectric SiO2 spacer of 50 nm and ultrathin gold atop could reach SERS enhancements of up to around seven times relative to gold films near the percolation threshold deposited on a standard glass substrate. The close contiguity of the analyte to graphene and nanostructured Au efficiently quenches the fluorescent background of the model compound. The obtained result shows that the strategy of combining ultrathin nano-island gold films near the percolation threshold with gap plasmon resonances is promising for the design of highly efficient SERS substrates for potential applications in ultrasensitive Raman detection.

Gold Nanostars with Reduced Fouling Facilitate Small Molecule Detection in the Presence of Protein.

Gold nanoparticles have the potential to be used in biomedical applications from diagnostics to drug delivery. However, interactions of gold nanoparticles with different biomolecules in the cellular environment result in the formation of a “protein corona”—a layer of protein formed around a nanoparticle, which induces changes in the properties of nanoparticles. In this work we developed methods to reproducibly synthesize spheroidal and star-shaped gold nanoparticles, and carried out a physico-chemical characterization of synthesized anionic gold nanospheroids and gold nanostars through transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential (ZP), nanoparticles tracking analysis (NTA), ultraviolet-visible (UV–Vis) spectroscopy and estimates of surface-enhanced Raman spectroscopy (SERS) signal enhancement ability. We analyzed how they interact with proteins after pre-incubation with bovine serum albumin (BSA) via UV–Vis, DLS, ZP, NTA, SERS, cryogenic TEM (cryo-TEM) and circular dichroism (CD) spectroscopy. The tests demonstrated that the protein adsorption on the particles’ surfaces was different for spheroidal and star shaped particles. In our experiments, star shaped particles limited the protein corona formation at SERS “hot spots”. This benefits the small-molecule sensing of nanostars in biological media. This work adds more understanding about protein corona formation on gold nanoparticles of different shapes in biological media, and therefore guides design of particles for studies in vitro and in vivo.

Fast, sensitive and low-cost chemical sensor based on manufacturing nanostructured Co3O4 using Raman Spectroscopy

Nanostructured Co3O4 has novel properties, so it can be manufactured with simple, fast preparation of samples, and a low-cost process. FESEM field emission electron microscope scanning, XRD diffraction, and Raman spectroscopy characterized Co3O4 nanostructured tetrahedral structures with multiple branches. Good sensitivity and selectivity and high stability can be seen for the nanostructured Co3O4. Cationic surfactant (CTAB) and anionic surfactant (PVP) both have a guiding effect on Co3O4 production. The self-assembled Co3O4 particles in Methylene Blue (MB) exhibit excellent Surface Enhanced Raman Spectroscopy efficiency. An average enhancement factor (EF) of 50 × 106 was achieved for the Co3O4 in PVP on 135 gsm printing paper and 41 ×106 for the Co3O4 in CTAB on 240 gsm printing paper.The results showed Co3O4 in PVP produced the highest sensitivity, specificity, and the lowest limit of detection LOD which was 0.52 nM for MB as Raman reporter molecule, and the sensitivity offered almost 98% with selectivity equal to 92%. To the best of the author’s knowledge, this is the first demonstration of Co3O4 in PVP paper-based as a chemical sensor by enhanced Raman spectroscopy signal.

Separable surface enhanced Raman spectroscopy sensor platformed by HPTLC for facile screening of malachite green in fish

Facile and effective coupling of SERS sensor to chromatographic tools has been an attractive goal in the field of food analytical chemistry for years. Platformed by HPTLC, a separable SERS sensor was developed in this study and its analytical power was exemplarily evaluated by screening trace malachite green in fish. To enable enough detectability and reproducibility of SERS measurements, a flexible substrate based on the hybrid of AgNP and glass fiber paper was easily fabricated. Meanwhile, the crude extract of fish muscle was separated on the aluminum foil backed HPTLC plate, resulting in spiral isolation of the analyte from co-extracted matrix. Guided by the visible standard in parallel, bands of interest were thereafter transferred to the eluent by a handy puncher. Jointly with the as-prepared flexible substrate, the band eluent was measured by Raman spectroscopy, responding sensitive and characteristic fingerprint signals. Meanwhile, performances of the established SERS sensor were also examined, showing adequate detectability (LOD < 10 μg/kg), precision (RSD%<11.8%) and linearity (R2 = 0.9975 from 0.05 to 10 ng/band) for screening purpose. Apart from that, the analysis robustness for practical application was further validated with fish sample, giving spike-recovery rates from 78.8 to 87.3%. This work demonstrated that HPTLC platformed SERS sensor can reach an ideal balance between efficiency, throughput and reliability, and therefore might be a promising tool especially suitable for screening trace contaminants in sophisticated mixtures.

Highly Sensitive Colorimetric/Surface-Enhanced Raman Spectroscopy Immunoassay Relying on a Metallic Core-Shell Au/Au Nanostar with Clenbuterol as a Target Analyte.

Lateral flow immunoassay (LFIA) has emerged as an effective technique in the field of food safety and environmental monitoring. However, sensitive and quantitative detection is still challenging for LFIAs in complex environments. In this work, a dual-model colorimetric/SERS lateral flow immunoassay for ultrasensitive determination of clenbuterol was constructed based on a metallic core-shell Au/Au nanostar acting as a multifunction tag. Raman reporter molecules are located between the core (AuNP) and shell (Au nanostar) to form a sandwich structure, which contributes to eliminate the environmental interference and improve the detection stability. In addition, the Au/Au nanostar provides a much higher Raman enhancement due to the presence of sharp tips and larger surface roughness in comparison with gold nanoparticles (AuNPs). Thus, on the basis of the antibody-antigen interaction, the dual-model immunoassay can produce strong colorimetric and surface-enhanced Raman spectroscopy (SERS) signals for highly sensitive detection of the target analyte, clenbuterol. Under optimal conditions, clenbuterol could be detected by the colorimetric model with a visual detection limit of 5 ng/mL. Meanwhile, the SERS signal of the Au/Au nanostar was accumulated on the test line for the SERS model detection with a quantitative detection limit as low as 0.05 ng/mL, which is at least 200-fold lower than that of the traditional AuNPs-based immunoassay. Furthermore, recovery rates of the proposed method in food samples were 86-110%. This dual-model immunoassay provides an effective tool for antibiotic residues analysis and demonstrates a broad potential for future applications in food safety monitoring.

Self-energized organic-inorganic hybrid composite for surface enhanced Raman spectroscopy

In this study, we integrate plasmonic metal nanomaterials with a piezoelectric polyvinylidene fluoride (PVDF) polymer and lithium niobate (LiNbO3) based composite to form an all-solid-state flexible self-energized sensor. We demonstrate that following the application of a load, the film enhances the surface-enhanced Raman spectroscopy (SERS) signal of an analyte molecule up to 14 times. The piezoelectric β-phase of PVDF in the film is optimized through the introduction of multi-walled carbon nanotubes and post-fabrication UV irradiation annealing. Additionally, the SERS signal enhancement can be further increased by the application of in situ UV light irradiation of the sample, resulting in the generation of photoexcited electrons from LiNbO3 microparticles introduced into the composite. Both the application of a mechanical displacement and the UV light-induced charge generation result in an improved charge transfer between the film and an analyte molecule. The piezoelectric PVDF/LiNbO3 film has been shown to be a suitable SERS platform for the detection of important biological molecules, demonstrating the potential of the substrate for fast on-site detection applications.

Morpho-molecular signal correlation between optical coherence tomography and Raman spectroscopy for superior image interpretation and clinical diagnosis

The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future.

Investigation of dual plasmonic core-shell Ag@CuS nanoparticles for potential surface-enhanced Raman spectroscopy-guided photothermal therapy.

Aim: To prepare efficient metal-semiconductor nanoparticles as noninvasive, real-time imaging probes for photothermal therapy (PTT) applications. Materials & methods: A bottom-up approach was used to fabricate core-shell Ag@CuS nanoparticles (NPs). PTT and Raman mapping were done using HeLa cells. Theoretical simulation of electric field enhancement and heat dissipation density of Ag@CuS NPs was performed. Results: PTT-induced hyperthermia was achieved under 940nm near-infraredlight irradiation. Surface-enhanced Raman spectroscopy (SERS) signals of dye molecules were observed when conjugated with Ag@CuS NPs. Conclusion: Ag@CuS NPs are found to be efficient for SERS imaging and localized heating under laser irradiation, making a promising candidate for SERS-guided PTT.

A computationally efficient Monte-Carlo model for biomedical Raman spectroscopy.

Monte Carlo (MC) modeling is a valuable tool to gain fundamental understanding of light-tissue interactions, provide guidance and assessment to optical instrument designs, and help analyze experimental data. It has been a major challenge to efficiently extend MC towards modeling of bulk-tissue Raman spectroscopy (RS) due to the wide spectral range, relatively sharp spectral features, and presence of background autofluorescence. Here, we report a computationally efficient MC approach for RS by adapting the massively-parallel Monte Carlo eXtreme (MCX) simulator. Simulation efficiency is achieved through "isoweight," a novel approach that combines the statistical generation of Raman scattered and Fluorescence emission with a lookup-table-based technique well-suited for parallelization. The MC model uses a graphics processor to produce dense Raman and fluorescence spectra over a range of 800 - 2000 cm-1 with an approximately 100× increase in speed over prior RS Monte Carlo methods. The simulated RS signals are compared against experimentally collected spectra from gelatin phantoms, showing a strong correlation.

Label-free surface-enhanced Raman spectroscopy detection for tyrosine-methionine-aspartate-aspartate (YMDD)-motif mutants of HBV DNA

Hepatitis B is a widespread and potentially life-threatening disease caused by the hepatitis B virus, tyrosine-methionine-aspartate-aspartate (YMDD) - motif mutant is a known HBV variant and responsible for the drug resistance during Long-term lamivudine treatment. In this work, spermine-coated silver nanoparticles were used as surface-enhanced Raman scattering enhancement matrices to detect mutations in single sites of the hepatitis B virus single-stranded DNA. The unique Raman finger-print spectrum of DNA based on spermine-coated silver nanoparticles was detected. And the signals from the phosphate backbone allowed to be an internal standard for standardize the surface-enhanced Raman spectrum of DNA oligonucleotides. The spectral changes were quantitatively related to the composition of adenine in the DNA strand, and the correlation performance reached 0.99. The relative standard deviation of surface-enhanced Raman spectroscopy signal corresponding to the tyrosine-isoleucine-aspartate-aspartate (YIDD), tyrosine-valine-aspartate-aspartate (YVDD), and YMDD was 5.43 %, 7.5 %, and 7.28 %, respectively. The proposed method provides a potential tool for YMDD-motif mutants detection and reference for therapeutic drug monitoring.