Surface-enhanced Raman Spectra Research Articles

Direct comparison of different protocols to obtain surface enhanced Raman spectra of human serum

Label-free Surface Enhanced Raman Spectroscopy (SERS) is a rapid technique that has been extensively applied in clinical diagnosis and biomedicine for the analysis of biofluids. The purpose of this approach relies on the ability to detect specific “metabolic fingerprints” of complex biological samples, but the full potential of this technique in diagnostics is yet to be exploited, mainly because of the lack of common analytical protocols for sample preparation and analysis. Variation of experimental parameters, such as substrate type, laser wavelength and sample processing can greatly influence spectral patterns, making results from different research groups difficult to compare. This study aims at making a step toward a standardization of the protocols in the analysis of human serum samples with Ag nanoparticles, by directly comparing the SERS spectra obtained from five different methods in which parameters like laser power, nanoparticle concentration, incubation/deproteinization steps and type of substrate used vary. Two protocols are the most used in the literature, and the other three are “in-house” protocols proposed by our group; all of them are employed to analyze the same human serum sample. The experimental results show that all protocols yield spectra that share the same overall spectral pattern, conveying the same biochemical information, but they significantly differ in terms of overall spectral intensity, repeatability, and preparation steps of the sample. A Principal Component Analysis (PCA) was performed revealing that protocol 3 and protocol 1 have the least variability in the dataset, while protocol 2 and 4 are the least repeatable.

TriFNet: A triple-branch feature fusion network for pH determination by surface-enhanced Raman spectroscopy

Due to the acidic tumor microenvironment caused by metabolic changes in tumor cells, the accurate pH detection of extracellular fluid is helpful for doctors in precise tumor resection. The combination of Raman spectroscopy and deep learning provides a solution for pH detection. However, most existing studies use one-dimensional convolutional neural networks (1D-CNNs) for spectral analysis, which limits the performance due to insufficient feature extraction. In this work, we propose a 2D triple-branch feature fusion network (TriFNet) for accurate pH determination using surface-enhanced Raman spectra (SERS). Specifically, we design a triple-branch network structure by converting Raman spectra into three types of images to extensively extract complex patterns in spectra. In addition, an attention fusion module, which leverages the complementarity among features in both space and channel, is designed to obtain the valuable information, achieving further accurate pH determination. On our Raman spectral dataset containing 14,137 samples, we achieved mean absolute error (MAE) of 0.059, standard deviation of the absolute error (SD) of 0.07, root mean squared error (RMSE) of 0.092, and coefficient of determination (R2) of 0.991 on the test set. Compared with other published methods, the four metrics showed an average improvement of 47%, 39%, 43%, and 6%, respectively. In addition, visualization validates the diagnostic capability of our model to correlate with biomolecular signatures. Meanwhile, our model has robustness to different SERS chips. These results prove the potential of our method to develop an effective technology based on Raman spectroscopy for accurate pH determination to guide surgery.

Impact of the outer‐sphere and inner‐sphere association in the surface enhanced Raman spectra of metal complexes and gold nanoparticles

AbstractTransition metal complexes, such as the low‐spin bis (phenylterpyridine) (A) and bis (pyridylterpyrazine)iron (II) (B) complexes, provide didactic chromophore species for demonstrating the Raman, resonance Raman, and the surface‐enhanced Raman scattering (SERS) behavior in coordination chemistry, as well as for elucidating the nature of inner‐sphere and outer‐sphere association with plasmonic nanoparticles. Their electrostatically stabilized ion pairs with citrate–gold nanoparticles have been studied in an aqueous solution, from the pronounced changes in the plasmonic band at 540 nm. Complex A, lacking any coordinating site, can only generate outer‐sphere complexes with citrate–gold nanoparticles, but they are stable enough to give a strong SERS response, even at 10−8 M. At 10−6 M, agglomeration accompanies the decrease of the electrostatic repulsion, resulting in a sharp decay of the plasmon resonance band at 540 nm. This is followed by the rise of a plasmon coupling band above 700 nm. However, at 10−4 M, the excess of the complex in the adsorption layer produces a reverse effect, decreasing agglomeration. The observed Raman spectra are essentially similar for the several concentrations employed because the outer‐sphere interaction implies a SERS electromagnetic mechanism. In contrast, complex B exhibits several pyridine and pyrazine N‐atoms available to form inner‐sphere‐associated species. A selective enhancement of the SERS signals is observed at 10−8 M, clearly indicating a chemical mechanism, consistent with a bridging mode. At 10−6 M and above, the agglomeration leads to a plasmon coupling band at 800 nm, while the SERS response indicates a change in the binding modes dictated by the excess of the complexing molecules.

Catalyst-Free Carbon Dioxide Conversion in Water Facilitated by Pulse Discharges.

By inducing CO2-pulsed discharges within microchannel bubbles and regulating thus-forming plasma microbubbles, we observe high-performance, catalyst-free coformation of hydrogen peroxide (H2O2) and oxalate directly from CO2 and water. With isotope-labeled C18O2 as the feedstock, peaks of H218O16O and H216O2 observed by ex situ surface-enhanced Raman spectra indicate that single-atom oxygen (O) from CO2 dissociations and H2O-derived OH radicals both contribute to H2O2 formation. The global plasma chemistry modeling suggests that high-density, energy-intense electron supply enables high-density CO2- (aq) and HCO2- (aq) formation and their subsequent coupling to produce oxalate. The enhanced solvation of CO2, facilitated by the efficient transport of CxOy ionic species and CO, is demonstrated as a crucial benefit of spark discharges interacting with water at the bubble interface. We expect this plasma microbubble approach to provide a novel power-to-chemical avenue to convert CO2 into valuable H2O2 and oxalic acid platform chemicals, thus leveraging renewable energy resources.

Early-stage diagnosis of bladder cancer using surface-enhanced Raman spectroscopy combined with machine learning algorithms in a rat model

Early diagnosis and accurate assessment of tumor development facilitate early bladder cancer resection and initiation of drug therapy. This study enabled an early, accurate, label-free, noninvasive diagnosis of bladder tumors by analyzing nano-biomarkers in a single drop of urine through surface-enhanced Raman spectroscopy (SERS). In a standard N-butyl-N-4-hydroxybutyl nitrosamine–induced rat model of bladder cancer, cancer stage and polyp tumor development were monitored using a small endoscope with a diameter of 1.2 mm in a minimally invasive manner without the need to kill the rats. Samples were divided into cancer-free, early-stage, and polyp-form cancer. Training data were classified according to micro-cystoscopic 5-aminolevulinic acid fluorescence diagnosis, and specimens were postmortem verified through histopathological analysis. A drop of urine from each sample group was placed on an Au-coated zinc oxide nanoporous chip to filter nano-biomaterials and selectively enhance the Raman signals of nanoscale analytes via SERS. Principal component analysis was used to reduce the dimensionality of the collected Raman spectra, and partial least squares discriminant analysis was used to find diagnostic clusters based on the labeled samples. The combination of SERS and machine learning achieved an accuracy ≥99.6% in diagnosing both early- and polyp-stage bladder tumors. With an area under the receiver operating characteristic curve greater than 0.996, the accuracy of the diagnosis in the rat model suggests that SERS-based diagnostic methods are promising when coupled with machine learning. Low-cost, label-free, and noninvasive surface-enhanced Raman spectra are ideal for developing clinically relevant point-of-care diagnostic techniques.

Chemical Imaging of RNA-Tau Amyloid Fibrils at the Nanoscale Using Tip-Enhanced Raman Spectroscopy.

In the presence of cofactors, tau protein can form amyloid deposits in the brain which are implicated in many neurodegenerative disorders. Heparin, lipids, and RNA are used to recreate tau aggregates in vitro from recombinant protein. However, the mechanism of interaction of these cofactors and the interactions between cofactors and tau are poorly understood. Herein, we use tip-enhanced Raman spectroscopy (TERS) to visualize the spatial distribution of adenine, protein secondary structure, and amino acids (arginine, lysine and histidine) in single polyadenosine (polyA)-induced tau fibrils with nanoscale spatial resolution (<10-20 nm). Based on reference unenhanced and surface-enhanced Raman spectra, we show that the polyA anionic cofactor is incorporated in the fibril structure and seems to be superficial to the β-sheet core, but nonetheless enveloped within the random-coiled fuzzy coat. TERS images also prove the colocalization of positively charged arginine, lysine, and histidine amino acids and negatively charged polyA, which constitutes an important step forward to better comprehend the action of RNA cofactors in the mechanism of formation of toxic tau fibrils. TERS appears as a powerful technique for the identification of cofactors in individual tau fibrils and their mode of interaction.

DNAzyme amplifaction strategy coupled with peanut-shaped FexOy@MMC@Au and COF@Au synergistic SERS enhancement for ultrasensitive analysis of chloramphenicol

In this study, a target induced DNAzyme amplifaction strategy was developed combining with peanut-shaped FexOy@macro-/mesoporous carbon (MMC)@Au and covalent organic frameworks (COF)@Au to construct surface enhanced Raman spectrum (SERS) aptasensor for ultrasensitive detection of chloramphenicol (CAP). The polydopamine was firstly self-polymerized on the peanut-shaped Fe2O3 as a reductant to generate a uniform assembly of AuNPs, with multiple hotspots, to achieve high reproducibility. After carbonation process, the obtained magnetic peanut-shaped FexOy@MMC@Au could effectively avoid the Raman interference of the SERS substrate. When target CAP was dropped into the aptamer and DNAzyme double chains, CAP could specifically combining with aptamer, releasing DNAzyme chain to cut off hairpin DNA which was already assembled on the FexOy@MMC@Au. At this time, COF@Au@toluidine blue (TB)@S1 can be attract closed to the SERS substrate due to the complementation of S1 with residual hairpin DNA to produce strong Raman signal. Based on this principle, the SERS aptasensor for the detection of CAP possessed a very low limit of detection (LOD) of 7.35 fM was obtained. The results suggested the potential of this SERS aptasensor for sensitive and selective CAP diagnosis and be applied to the clinical and biochemical analysis.

Adsorption behavior, different green solvent effect and surface enhanced Raman spectra (SERS) investigation on inhibition of SARS-CoV-2 by antineoplastic drug Carmofur with silver/gold/platinum loaded silica nanocomposites: A combined computational analysis and molecular modelling approach

In recent times, extensive research has been carried out to uncover effective drug treatments for coronavirus disease (COVID-19). The Carmofur (HCFU) molecule is primarily known for its antineoplastic properties and its use in cancer treatment. Nowadays, the antineoplastic drug Carmofur has shown its effectiveness in inhibiting the SARS-CoV-2 virus. The primary objective of this article is to utilize theoretical knowledge to explore the absorption mechanism and interaction between the HCFU molecule and the noble metal (Ag/Au/Pt)-loaded silica nanocomposites (HCFU + Ag/Au/Pt…SiO2). The optimized geometry, frequency, and intensity of the vibrational bands of the HCFU molecule and its complexes were obtained from the DFT method with the LANL2DZ basis set. The SERS technique was carried out to explore the adsorption of HCFU molecule with metal (Ag/Au/Pt)-loaded silica nanocomposites. The chemical reactivity and the charge distribution within the molecule were analysed with the help of HOMO-LUMO, Molecular Electrostatic Potential (MEP), Electron Localized Function (ELF), and Localized Orbital Locator (LOL) studies. The polar protic (ethanol, methanol, and water) and polar aprotic (DMSO) solvents were used to analyse the UV–Visible spectra of the molecules using the TD-DFT method. The drug-likeness properties of the molecules were calculated utilizing Lipinski’s rule, and finally, the molecular docking prediction was carried out for the Carmofur (HCFU) and its complexes with the selected proteins.

Mg-Containing Zn3O3 Structures for Detection of CO2: A DFT Study on CHEM Effects of SERS and Electronic Properties.

Surface-enhanced Raman spectra (SERS) and electronic-structure-based properties are important tools for investigation of the molecular sensing ability of nanoparticles. The present computational study is intended to explore the sensing ability of Zn3O3 and Mg-containing Zn3O3 structures for CO2 molecules by CHEM effects of the SERS technique. Geometries of CO2-adsorbed Zn3O3, Zn2MgO3 (Mg as a substitutional impurity), and Zn3O3Mg (Mg as an interstitial impurity) structures are modeled using the B3LYP/6-31G(d,p) level of density functional theory. The Mg site of the Zn2MgO3 and Zn3O3Mg structures is preferential for the adsorption of CO2. The observed energy trends are supported by geometrical analysis, molecular orbital interactions, redshifts in CO2 vibrational modes, and topological properties. Raman activity enhancement of the CO2 symmetric vibrational mode is significant when the molecule is adsorbed at the Mg site of Zn3O3Mg. The observed Raman activity enhancement is supported by SERS spectra obtained from anharmonic calculations carried out on B3LYP/6-31G(d,p) geometries and substantiated by a larger change in the polarizability with energy corresponding to the symmetric vibrational mode of CO2. The TDDFT calculations, frequency-dependent polarizabilities, and charge transfer interactions show that Zn3O3Mg is a good substrate for sensing of CO2, with visible wavelengths, by resonance Raman effect. The trends with adsorption energy, Raman activity, and excited state properties are also substantiated by B3LYP/6-311+G(d,p) calculations.

Effects of magnetite on nitrate-dependent anaerobic oxidation of methane in an anaerobic membrane biofilm reactor: Metatranscriptomic analysis and mechanism prediction

Magnetite has been widely reported to accelerate methane production in anaerobic digestion. However, the effects of magnetite on the process of methane consumption, specifically nitrate-dependent anaerobic oxidation of methane (AOM), and its underlying mechanisms remain poorly understood. In this study, the addition of magnetite significantly improved the removal of nitrate in an anaerobic membrane biofilm reactor (AnMBfR) (25.2 ± 2.5 mg NO3−-N/L/d) compared to that in an AnMBfR without magnetite (8.7 ± 4.2 mg NO3−-N/L/d). Metatranscriptomic analysis showed that genes encoding type IV pilus assembly proteins were highly expressed in nitrate/nitrite-reducing bacteria in the biofilms of the two AnMBfRs. Specifically, the transcript abundance of these genes was observed to be higher in the presence of magnetite (gene expression levels, log2FPKM = 13.08) compared to the absence of magnetite (12.04). Biofilms with magnetite exhibited a linear increase in electron transfer resistance with increasing temperature, and the decrease in pH significantly increased their conductivity, indicating a metallic-like conductivity. Contrarily, an increase in temperature or decrease in pH did not influence the resistance or conductivity of biofilms without magnetite. Some of these cytochrome c (CYC)-like proteins were electrically active in the electrochemical Fourier transform infrared spectra and were closely associated with the outer-membrane multi-heme c-type cytochromes (OMCs). The intensities of the OMC-like bands in the surface-enhanced resonance Raman spectra with biofilms in the presence of magnetite were higher than those without magnetite. This study suggests that magnetite promotes the nitrate-dependent AOM process because of the formation of methanotrophic consortia based on direct interspecies electron transfer (DIET).

Qualitative and semi-quantitative analysis of melamine in liquid milk based on surface-enhanced Raman spectroscopy

Melamine is one of the common limited contaminations in dairy products. The traditional detection method has a long period and complicated pretreatment process. The rapid detection method is the better method to solve the screening of limited contaminations. In this paper, taking melamine as the research object, the surface enhanced Raman spectrum of melamine in liquid milk were collected by portable Raman spectrometer, and melamine was qualitatively identified and semi-quantitatively analyzed by Raman characteristic peak and Raman intensity, and a simple and efficient rapid screening method for limited contaminations was developed. The limit of detection is 0.25 mg/kg. The probability of detection is 100% at 2.5 mg/kg, which is the same between the two laboratories, indicating that the semi-quantitative method has good repeatability. The method of melamine proposed in this study can meet the rapid screening requirements of limited contaminations at the maximum residue limit, and has a good application prospect.

Intracellular Liquid‐Liquid Phase Separation Induces Tunable Anisotropic Nanocrystal Growth for Multidimensional Analysis

AbstractSpatially directed biomineralization of nanocrystals for specific optical purposes in biological systems and elucidation of the mechanism of biomineralized nanocrystals remains a fascinating but extremely challenging task. Herein, the biomineralization of tunable gold nanocrystals with in situ protein coronas by intracellular liquid‐liquid phase separation (LLPS) for in situ molecule surface‐enhanced Raman spectrum (SERS) analysis and tumor fluorescence identification. The anisotropic nanocrystals are realized by regulating LLPS, in which the nucleation of nanocrystals is at the protein secondary structural site (β‐Corner) of the droplet, the different adsorption energies of crystal surfaces further promote the directional growth of nanocrystals. Interestingly, gold nanocrystals with ultra‐narrow fluorescence emission at half‐peak width and ultra‐long Stokes shift and can obtain in situ molecular fingerprint information of protein corona to achieve by SERS. Of note are the anisotropic nanocrystals to differentiate clinical patient tumor tissue samples. Therefore, this study reveals the mechanism of intracellular tunable nanocrystal biomineralization and provides the basis for its biomedical application.

Photoexcited Plasmon-Driven Ultrafast Dynamics of the Adsorbate Probed by Femtosecond Time-Resolved Surface-Enhanced Time-Domain Raman Spectroscopy.

Metal nanoparticles have high potential in light-harvesting applications by transferring absorbed photon energy to the adsorbates. However, photoexcited plasmon-driven ultrafast dynamics of the adsorbate on metal nanoparticles have not been clearly understood. We studied ultrafast plasmon-driven processes of trans-1,2-bis(4-pyridyl)ethylene (BPE) adsorbed on gold nanoparticle assemblies (GNAs) using time-resolved surface-enhanced impulsive stimulated Raman spectroscopy (TR-SE-ISRS). After photoexciting the localized surface plasmon resonance (LSPR) band of the GNAs, we measured femtosecond time-resolved surface-enhanced Raman spectra of the adsorbate, which exhibited transient bleach in the Raman signal and following biphasic recovery that proceeds on the time scale of a few tens of picoseconds. The TR-SE-ISRS data were analyzed with singular value decomposition, and the obtained species-associated Raman spectra indicated that photoexcitation of the LSPR band alters chemical interaction between BPE and the GNAs on an ultrafast time scale; initial steady-state BPE is recovered through a precursor state that has weaker interaction with the GNAs.

Designing structures that maximize spatially averaged surface-enhanced Raman spectra.

We present a general framework for inverse design of nanopatterned surfaces that maximize spatially averaged surface-enhanced Raman (SERS) spectra from molecules distributed randomly throughout a material or fluid, building upon a recently proposed trace formulation for optimizing incoherent emission. This leads to radically different designs than optimizing SERS emission at a single known location, as we illustrate using several 2D design problems addressing effects of hot-spot density, angular selectivity, and nonlinear damage. We obtain optimized structures that perform about 4 × better than coating with optimized spheres or bowtie structures and about 20 × better when the nonlinear damage effects are included.

Optical fiber optrodes with silver-coated gold nanocavity ordered arrays for highly sensitive surface enhanced Raman spectrum

In this paper, we have proposed a new strategy to fabricate surface enhanced Raman scattering (SERS) optical fiber optrodes with ordered gold nanocavities modified by silver nanoparticles (AgNPs) on the fiber tip. Such nanocavity ordered array (COA) structures have strong light trapping ability and improve the utilization of light through multiple reflections of light. Besides, COAs have larger specific surface area, which can provide a large amount of SERS “hot spots”, and also enable the absorption of more probe molecules. Furthermore, secondary deposited silver can result in strong coupling between the gold nanocavities and AgNPs. Consequently, the nanocavity arrays can further enhance local surface plasmon resonance (LSPR) effect to improve the sensitivity of SERS optrodes. We have also studied such nanocavity SERS optrodes for in-situ detection of 4-aminothiophenol (4-ATP) with detection limits of 10−10 M. The SERS optrode is highly sensitive, good reproducibility and acceptable stability, and shows excellent performance in liquid-phase in-situ and remote SERS detection. Thus, it is promising for water environmental monitoring applications. And this paper provides a simple and low cost technology suitable for the large-scale fabrication of highly sensitive optical fiber SERS optrodes.

SERS-based error calibration of a TMB-H2O2 colorimetric system.

3,3',5,5'-tetramethylbenzidine (TMB)-H2O2 is widely used as an effective colorimetric system, in which the color reaction is implemented with peroxidase-catalyzed TMB oxidation by H2O2 that usually measured UV-vis absorption spectra or Raman spectra. However, its low accuracy significantly limits its application. Blue charge transfer complex (CTC), which is the product of TMB and H2O2 reaction and is used as the basis for partial colorimetric methods, usually causes colorimetric error owing to changes in the UV-vis absorption and Raman spectra during TMB oxidation under various environmental conditions (catalyst type, temperature, H2O2 concentration). Herein, we propose a surface-enhanced Raman spectrum (SERS)-based error calibration method to improve the accuracy of the TMB-H2O2 colorimetric system. It is found that under 633 nm laser excitation, TMB has three Raman peaks at 1189, 1335 and 1609 cm-1 in the single-electron oxidation phase, and these peaks disappear completely in the two-electron oxidation phase. By comparing these Raman peaks, we can conveniently obtain the actual process information during TMB oxidation. Using the proposed method, the accuracy of the TMB-H2O2 colorimetric system improved by more than 15%. Importantly, this SERS-based TMB-H2O2 error calibration method will open a new horizon for enzyme-linked immunosorbent assay (ELISA) and other biomedical applications.

Thioglucose functionalized gold nanoparticles as active substrates for surface enhanced Raman spectroscopy of lectins

Vibrational spectroscopy methods display great potential in the study of biomolecules. The complexity of these molecular systems, though, is often a hindrance for the interpretation of the experimental spectra. Selective techniques should therefore be improved and applied extensively. This article presents surface enhanced Raman spectra of an important model protein, namely, wheat germ agglutinin. To obtain these spectra, a novel substrate for the protein has been developed. The substrate is based on gold nanospheroids, produced by wet synthesis. The nanoparticles are then functionalized by reaction with a solution of β-D-thioglucose to increase the affinity of the agglutinin for the surface. When nanoparticle films are placed in contact with diluted agglutinin solutions, vibrational bands of the protein appear and can be easily discriminated from those of the substrate. The Raman bands of the substrate and of the protein have then been assigned correlatively. On this basis, we conclude that the interaction between the agglutinin and the nanoparticles is selectively detected only when the metal surface is suitably functionalized.

Surface enhanced Raman spectra (SERS) and computational study of gemcitabine drug adsorption on to Au/Ag clusters with different complexes: Adsorption behavior and solvent effect (IEFPCM) – Anticancer agent

The present study pertains to the theoretical understanding of the adsorption mechanisms and energetics of interaction between the anticancer drug Gemcitabine (GEM) and nano-clusters (Au, Ag). The quantum mechanics calculations were conducted using the B3LYP level along with the LANL2DZ basis set to investigate GEM adsorption on Au and Ag cluster surfaces with surface-enhanced Raman scattering (SERS) technique. Nano metal clusters (nmCs) of the adsorbed GEM molecule have been studied with respect to their electronic, chemical, and UV–vis spectral properties. The contour of molecular electrostatic potential (MEP) and HOMO-LUMO bandgap energy analysis has been used to identify the molecule’s active site using the same level of theory. An electron localized function (ELF) and localized orbital locator (LOL) calculations were used to detect electron density at bonding and anti-bonding sites. A non-covalent interaction (NCI) analysis reveals weak Van der Waals interactions, hydrogen bonds, and repulsive steric interactions in GEM complexes with nmCs(Au/Ag). The study provided key information on designing a molecular structure with a good pharmacological profile by calculating bioactivity and drug similarity parameters for the title compound. Clustering of GEM with nmCs enhanced the therapeutic properties and nmC acts as a drug carrier of GEM.

Surface-enhanced Raman scattering of DNA molecules on silver electrodes modified with silver nanoparticles

High-quality surface-enhanced Raman spectra (SERS) of calf thymus DNA, apple single-stranded DNA, and rice single-stranded DNA are obtained by using rough silver electrodes modified with silver nanoparticles as the substrate. The appearance of fruitful Raman-active modes enables to identify the fine vibrational modes of DNA molecules of which the normal Raman spectra are not easy to be measured. It is concluded that the silver electrode modified by silver nanoparticles is a highly sensitive SERS substrate for DNA analysis, due to the uniformly aligned silver nanoparticles in combination with additional contributions of electrode potentials. Furthermore, the SERS spectra of these DNA molecules at varying potential conditions also provide information on the adsorption behavior of these DNA molecules on the silver. It is anticipated that the DNA molecules may tend to lie flat on the nanosilver surface; with increasing negative potentials, the spectra exhibit dramatic fluctuation, which could be associated with interface oxidation and changes of the adsorption behaviors in view of the different hydrophobicity/hydrophilic nature and electrostatic interactions of the phosphate base and the electrode surface.

Structural and spectroscopic analysis of L‐Proline monomer and dimer by DFT approach

AbstractIn this work we have analyzed the Fourier Transform Infrared (FTIR), Raman and Surface Enhanced Raman Spectra (SERS) of L‐Proline. The molecule under consideration L‐Proline in monomer and dimer states were optimized using DFT/B3LYP and DFT/M06‐2X methods with 6‐31G (d,p) basis set. In order to correlate the experimental SERS spectra we have calculated the Raman spectra of L‐Proline monomer and dimer with silver (Ag) clusters using Density Functional Theory (DFT) with B3LYP functional and LANL2DZ basis set. The vibrational spectra were interpreted by using vibrational energy distribution analysis (VEDA) program and potential Energy Distribution (PED) analysis of the vibrational modes have been performed to have a clear picture of the fragments of different states of the molecule. The equilibrium molecular geometry, harmonic vibrational wavenumbers, Frontier molecular orbitals, Mulliken charges, energy parameters and various bonding features have also been computed.