Study on the Infrared and Raman spectra of Ti3AlB2, Zr3AlB2, Hf3AlB2, and Ta3AlB2 by first-principles calculations.

In this paper, the crystal geometry, electronic structure, lattice vibration, Infrared and Raman spectra of ternary layered borides M3AlB2 (M = Ti, Zr, Hf, Ta) are studied by using first principles calculation method based on the density functional theory. The electronic structure of M3AlB2 indicates that they are all electrical conductors, and the d orbitals of Ti, Zr, Hf, and Ta occupy most of the bottom of the conduction band and most of the top of the valence band. Al and B have lower contributions near their Fermi level. The lightweight and stronger chemical bonds of atom B are important factors that correspond to higher levels of peak positions in the Infrared and Raman spectra. However, the vibration frequencies, phonon density of states, and peak positions of Infrared and Raman spectra are significantly lower because of heavier masses and weaker chemical bonds for M and Al atoms. And, there are 6 Infrared active modes A2u and E1u, and 7 Raman active modes, namely A1g, E2g, and E1g corresponding to different vibration frequencies in M3AlB2. Furthermore, the Infrared and Raman spectra of M3AlB2 were obtained respectively, which intuitively provided a reliable Infrared and Raman vibration position and intensity theoretical basis for the experimental study.

Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra.

Raman spectroscopy is a rapid method for analysing the molecular composition of biological material. However, noise contamination in the spectral data necessitates careful pre-processing prior to analysis. Here we propose an end-to-end Convolutional Neural Network to automatically learn an optimal combination of pre-processing strategies, for the classification of Raman spectra of superficial and deep layers of cartilage harvested from 45 Osteoarthritis and 19 Osteoporosis (Healthy controls) patients. Using 6-fold cross-validation, the Multi-Convolutional Neural Network achieves comparable or improved classification accuracy against the best-performing Convolutional Neural Network applied to either the raw or pre-processed spectra. We utilised Integrated Gradients to identify the contributing features (Raman signatures) in the network decision process, showing they are biologically relevant. Using these features, we compared Artificial Neural Networks, Decision Trees and Support Vector Machines for the feature selection task. Results show that training on fewer than 3 and 300 features, respectively, for the disease classification and layer assignment task provide performance comparable to the best-performing CNN-based network applied to the full dataset. Our approach, incorporating multi-channel input and Integrated Gradients, can potentially facilitate the clinical translation of Raman spectroscopy-based diagnosis without the need for laborious manual pre-processing and feature selection.

Luminescence, XPS and Raman of crystalline quartz affected to high pressure by detonation.

The Raman spectra, x-ray photoelectron spectroscopy (XPS), and x-ray excited luminescence spectra of crystalline quartz samples subjected to different pressure levels through detonation were compared with the spectra of the original samples. In the samples under study, the luminescence of a self-trapped exciton (STE) was analyzed, which, when excited by x-rays, has a high energy yield (∼20%) in crystallineα-quartz not treated by detonation. The deviations of the luminescence spectrum are small in the pressure range from 9 to 27 GPa relative to untreated samples, which means the presence of crystalline quartz grains. A sharp change in the spectrum occurs for the sample subjected to a pressure of 34 GPa. The STE band practically disappeared and a band appeared at 350 nm. This band appears in thermally stimulated luminescence (in contrast to the STE band, which is not observed at all in thermally stimulated luminescence) and, therefore, can be attributed to some defects arising due to high pressure. This luminescence is not similar to the luminescence of a stishovite single crystal, but analysis of the XPS spectra suggests the formation of non-crystalline stishovite in detonated samples. In the Raman scattering spectra, a single sharp line at 465 cm-1, characteristic ofα-quartz, was observed in the samples after detonation pressure for the remaining small crystal grains. This line decreased greatly for the sample subjected to a pressure of 34 GPa. Against the structureless background of exposed samples of 'poor' optical quality, other Raman bands did not appear. It can be assumed that there are very broad bands of Raman scattering caused by the amorphization of stishovite under high detonation pressure. Amorphization explains the absence of luminescence, similar to the stishovite crystal.

Symbiodiniaceae and Ruegeria sp. Co-Cultivation to Enhance Nutrient Exchanges in Coral Holobiont.

The symbiotic relationship between corals and their associated microorganisms is crucial for the health of coral reef eco-environmental systems. Recently, there has been a growing interest in unraveling how the manipulation of symbiont nutrient cycling affects the stress tolerance in the holobiont of coral reefs. However, most studies have primarily focused on coral-Symbiodiniaceae-bacterial interactions as a whole, neglecting the interactions between Symbiodiniaceae and bacteria, which remain largely unexplored. In this study, we proposed a hypothesis that there exists an inner symbiotic loop of Symbiodiniaceae and bacteria within the coral symbiotic loop. We conducted experiments to demonstrate how metabolic exchanges between Symbiodiniaceae and bacteria facilitate the nutritional supply necessary for cellular growth. It was seen that the beneficial bacterium, Ruegeria sp., supplied a nitrogen source to the Symbiodiniaceae strain Durusdinium sp., allowing this dinoflagellate to thrive in a nitrogen-free medium. The Ruegeria sp.-Durusdinium sp. interaction was confirmed through 15N-stable isotope probing-single cell Raman spectroscopy, in which 15N infiltrated into the bacterial cells for intracellular metabolism, and eventually the labeled nitrogen source was traced within the macromolecules of Symbiodiniaceae cells. The investigation into Symbiodiniaceae loop interactions validates our hypothesis and contributes to a comprehensive understanding of the intricate coral holobiont. These findings have the potential to enhance the health of coral reefs in the face of global climate change.

Material and Microstructure Analysis of Wood Color Paintings from Shaanxi Cangjie Temple, China.

Cangjie Temple was built to commemorate Cangjie, the legendary inventor of Chinese characters. It stands as one of the few remaining temples in China dedicated to the invention and creation of writing. In this study, the material properties of wooden paintings from the Cangjie temple were characterized using Polarized Light Microscopy (PLM), Scanning Electron Microscopy coupled with Energy Dispersive X-ray Spectroscopy (SEM-EDS), Micro-confocal Raman Spectroscopy, X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Pyrolysis-Gas Chromatography-Mass Spectrometry (Py-GC/MS). It was confirmed that the pigments of the paintings included cinnabar, lapis lazuli, lead white, Paris green, and carbon black. The proteinaceous glue was used as an adhesive in the pigment samples, with tung oil likely being utilized as a primer for the wooden structures before painting. This study not only provides valuable data support for the conservation and restoration of the architectural features of Cangjie Temple but also provides useful reference for the maintenance and inheritance of similar ancient buildings.

Quantum Chemical Investigation into the Structural Analysis and Calculated Raman Spectra of Amylose Modeled with Linked Glucose Molecules.

This study presents a quantum chemical investigation into the structural analysis and calculated Raman spectra of modeled amylose with varying units of linked glucose molecules. We systematically examined the rotation of hydroxymethyl groups and intramolecular hydrogen bonds within these amylose models. Our study found that as the number of linked glucose units increases, the linear structure becomes more complex, resulting in curled, cyclic, or helical structures facilitated by establishing various intramolecular interactions. The hydroxymethyl groups were confirmed to form interactions with oxygen atoms and with hydroxymethyl and hydroxyl groups from adjacent rings in the molecular structures. We identified distinct peaks and selected specific bands applicable in various analytical contexts by comparing their calculated Raman spectra. Representative vibrational modes within selected regions were identified across the different lengths of amylose models, serving as characteristic signatures for linear and more coiled structural conformations. Our findings contribute to a deeper understanding of amylose structures and spectroscopic signatures, with implications for theoretical studies and potential applications. This work provides valuable reference points for the detailed assignment of Raman peaks of amylose structure, facilitating their application in broader research on carbohydrate structures and their associated spectroscopic properties.

Negative Thermal Expansion in ABC(MoO4)3 Compounds.

Negative thermal expansion (NTE) compounds provide a solution for the mismatch of coefficients of thermal expansion in highly integrated device design. However, the current NTE compounds are rare, and how to effectively design new NTE compounds is still challenging. Here, a new concept is proposed to design NTE compounds, that is, to increase the flexibility of framework structure by expanding the space in framework structure compounds. Taking the parent compound NaZr2(PO4)3 as a case, a new NTE system AIBIICIII(MoO4)3 (A = Li, Na, K, and Rb; B = Mg and Mn; C = Sc, In, and Lu) is designed. In these compounds, the large volume of MoO4 tetrahedron is used to replace the small volume of PO4 tetrahedron in NaZr2(PO4)3 to enhance structural space and NTE performance. Simultaneously, a joint study of temperature-dependent X-ray diffraction, Raman spectroscopy, and the first principles calculation reveals that the NTE in AIBIICIII(MoO4)3 series compounds arise from the coupled oscillation of polyhedral. Large-radius ions are conducive to enhancing the space and softening the framework structure to achieve the enhancement of NTE. The current strategy for designing NTE compounds is expected to be adopted in other compounds to obtain more NTE compounds.

Biosynthesis of carotenoids in Azospirillum brasilense Cd is mediated via squalene (C30) route.

Azospirillum brasilense is a non-photosynthetic α-Proteobacteria, belongs to the family of Rhodospirillaceae and produces carotenoids to protect itself from photooxidative stress. In this study, we have used Resonance Raman Spectra to show similarity of bacterioruberins of Halobacterium salinarum to that of A. brasilense Cd. To navigate the role of genes involved in carotenoid biosynthesis, we used mutational analysis to inactivate putative genes predicted to be involved in carotenoid biosynthesis in A. brasilense Cd. We have shown that HpnCED enzymes are involved in the biosynthesis of squalene (C30), which is required for the synthesis of carotenoids in A. brasilense Cd. We also found that CrtI and CrtP desaturases were involved in the transformation of colorless squalene into the pink-pigmented carotenoids. This study elucidates role of some genes which constitute very pivotal role in biosynthetic pathway of carotenoid in A. brasilense Cd.

Modification of WS2thin film properties using high dose gamma irradiation.

The tunability of the transition metal dichalcogenide properties has gained attention from numerous researchers due to their wide application in various fields including quantum technology. In the present work, WS2has been deposited on fluorine doped tin oxide substrate and its properties have been studied systematically. These samples were irradiated using gamma radiation for various doses, and the effect on structural, morphological, optical and electrical properties has been reported. The crystallinity of the material is observed to be decreased, and the results are well supported by x-ray diffraction, Raman spectroscopy techniques. The increase in grain boundaries has been supported by the agglomeration observed in the scanning electron microscopy micrographs. The XPS results of WS2after gamma irradiation show evolution of oxygen, carbon, C=O, W-O and SO4-2peaks, confirming the addition of impurities and formation of point defect. The gamma irradiation creates point defects, and their density increases considerably with increasing gamma dosage. These defects crucially altered the structural, optical and electrical properties of the material. The reduction in the optical band gap with increased gamma irradiation is evident from the absorption spectra and respective Tauc plots. TheI-Vgraphs show a 1000-fold increase in the saturation current after 100 kGy gamma irradiation dose. This work has explored the gamma irradiation effect on the WS2and suggests substantial modification in the material and enhancement in electrical properties.

A novel method for quantitative determination of multiple substances using Raman spectroscopy combined with CWT.

The identification of mixed solutions is a challenging and important subject in chemical analysis. In this paper, we propose a novel workflow that enables rapid qualitative and quantitative detection of mixed solutions. We use a methanol-ethanol mixed solution as an example to demonstrate the superiority of this workflow. The workflow includes the following steps: (1) converting Raman spectra into Raman images through CWT; (2) using MobileNetV3 as the backbone network, improved multi-label and multi-channel synchronization enables simultaneous prediction of multiple mixture concentrations; and (3) using transfer learning and multi-stage training strategies for training to achieve accurate quantitative analysis. We compare six traditional machine learning algorithms and two deep learning models to evaluate the performance of our new method. The experimental results show that our model has achieved good prediction results when predicting the concentration of methanol and ethanol, and the coefficient of determination R2 is greater than 0.999. At different concentrations, both MAPE and RSD outperform other models, which demonstrates that our workflow has outstanding analytical capabilities. Importantly, we have solved the problem that current quantitative analysis algorithms for Raman spectroscopy are almost unable to accurately predict the concentration of multiple substances simultaneously. In conclusion, it is foreseeable that this non-destructive, automated, and highly accurate workflow can further advance Raman spectroscopy.

Relationships between conformational and vibrational features of tryptophan characteristic Raman markers.

Tryptophan (Trp) residue provides characteristic vibrational markers to the middle wavenumber spectral region of the Raman spectra recorded from peptides and proteins. In this report, we were particularly interested in eight Trp Raman markers, referred to as Wi (i = 1,…,8). All responsible for pronounced Raman lines, these markers originate from indole moiety, a bicyclic conjugated segment involved in the Trp structure. Numerous investigations have previously attempted to relate the variations observed in the spectral features of these markers to the environmental changes of Trp residues. To emphasize the most important points we can mention (i) the variations in the Raman profile of W4 (∼1360 cm-1) and W5 (∼1340 cm-1), frequently observed as a doublet with variable intensity ratio. These two markers were thought to result from a Fermi-resonance effect between certain planar and nonplanar modes; (ii) the changes observed in the wavenumbers and relative intensities of W4, W7 (∼880 cm-1) and W8 (∼760 cm-1) were supposed to be related to the accessibility of Trp to surrounding water molecules; and (iii) the wavenumber fluctuations of W3 (∼1550 cm-1), taken as a Trp side chain orientational marker. However, some ambiguities still exist regarding the interpretation of these markers, needing further clarification. Herein, upon a joint experimental and theoretical analysis based on a multiconformational approach, attention was paid to the relationships between structural and vibrational features of three indole-containing compounds with increasing structural complexity, i.e., skatole (3-methylindole), tryptophan, and tripeptide Gly-Trp-Gly. This study clearly shows that the existing assignments given to certain Trp Raman markers should be reconsidered, especially those based on the Fermi-resonance origin of W4-W5 (∼1360-1340 cm-1) doublet, as well as the purely environmental dependence of W7 and W8 markers.

Adsorption Structures, Vibrational Raman Spectra and Chemical Binding Properties of Thioglycolic Acid on Cu(111) Surfaces: A DFT Study.

Copper is widely used in everyday life and industrial production because of its good electrical and thermal conductivity. To overcome copper oxidation and maintain its good physical properties, small organic molecules adsorbed on the surface of copper make a passivated layer to further avoid copper corrosion. In this work, we have investigated thioglycolic acid (TGA, another name is mercaptoacetic acid) adsorbed on copper surfaces by using density functional theory (DFT) calculations and a periodical slab model. We first get five stable adsorption structures, and the binding interaction between TGA and Cu(111) surfaces by using density of states (DOS), indicating that the most stable configuration adopts a triple-end binding model. Then, we analyze the vibrational Raman spectra of TGA adsorbed on the Cu(111) surface and make vibrational assignments according to the vibrational vectors. Finally, we explore the temperature effect of the thermodynamically Gibbs free energy of TGA on the Cu(111) surface and the antioxidant ability of the small organic molecular layer of copper oxidation on the copper surface. Our calculated results further provide evidences to interpret the stability of adsorption structures and antioxidant properties of copper.

Introducing hafnium to atomically small- and medium-sized tin clusters (HfSnn0/-/2- (n = 4-17)): A computational investigation of geometrical and growth behavior, spectral properties, electronic configuration and thermochemistry.

The global and local minimum configurations of single Hf atom doped Sn clusters are conducted via density function theory (DFT) combined with artificial bee colony algorithm (ABCluster). Furthermore, DFT method is also used to systematically investigate on their structural growth evolution, spectral and electronic information, thermochemical properties following the size of tin clusters doped Hf atom. Structurally, the ground-state geometries of neutral, anion and di-anion are discovered that, from n = 4, the number of Sn atoms in cluster, HfSnn0/-/2- adsorb additional Sn atom on the prior architecture one by one until forming n = 17 for HfSnn-10/-, as well as forming n = 16 for HfSnn-12-. And for the HfSn110/- and HfSn102- as beginning the species veritably develop sealed architectures. The strongest vibrational modes of sealed nanoclusters are stretching modes of Hf atom with infrared actives and breathing modes of the Sn cage framework with Raman actives, respectively. The natural population analysis (NPA) elucidates the stronger relationship between the Hf atoms and the tin frameworks in sealed clusters than that in unsealed clusters. The results of thermochemical properties, molecular orbital shell (MOs), adaptive natural density partitioning (AdNDP) and ultraviolet visible absorption spectrum (UV-Vis) indicate that, the HfSn16 with high symmetry of Td exhibits thermochemical stability and optoelectronic properties, which is utilized potentially as zero-dimensional unit of self-assembling fluorescent nanomaterials.

Constructing Chainmail-Structured CoP/C Nanospheres as Highly Active Anodic Electrocatalysts for Oxygen Evolution Reaction.

Constructing highly active and noble metal-free electrocatalysts is significant for the anodic oxygen evolution reaction (OER). Herein, uniform carbon-coated CoP nanospheres (CoP/C) are developed by a direct impregnation coupling phosphorization approach. Importantly, CoP/C only takes a small overpotential of 230 mV at the current density of 10 mA cm-2 and displays a Tafel slope of 56.87 mV dec-1. Furthermore, the intrinsic activity of CoP/C is 21.44 times better than that of commercial RuO2 under an overpotential of 260 mV. In situ Raman spectroscopy studies revealed that a large number of generated Co-O and Co-OH species could facilitate the *OH adsorption, effectively accelerating the reaction kinetics. Meanwhile, the carbon shell with a large number of mesoporous pores acts as the chainmail of CoP, which could improve the active surface area of the catalyst and prevent the Co sites from oxidative dissolution. This work provides a facile and effective reference for the development of highly active and stable OER catalysts.

An electron density clustering based adaptive segmentation method for protein Raman spectrum calculation.

Raman spectroscopy is a powerful technique for protein detection, but the calculation of Raman spectrum is a longstanding challenging problem due to the large sizes and complex structures of protein molecules. Dividing proteins into fragments can greatly accelerate the calculation, but this usually introduces large errors originating from ignored interactions between fragments into obtained spectra. In this paper, we proposed a new adaptive segmentation method based on the strength of interactions and molecular shapes and structures, i.e., electron density clustering, to divide proteins. It can reduce errors of obtained Raman spectra by about 20% compared to the uniform segmentation method without a significant increase in computational cost. This method can facilitate the validation and analysis of detected Raman spectra of proteins and promote the application of Raman spectroscopy in biological detection.

Exploring the Influence of Morphology on Bipolaron-Polaron Ratios and Conductivity in Polypyrrole in the Presence of Surfactants.

This research aims to deepen the understanding of the relationship between conductivity and morphology in polypyrrole (PPy) via a comparison of the bipolaron to polaron ratios with a focus on the C-H deformation area. PPy samples were synthesized with different surfactants: sodium dodecyl sulfate (SDS), cetyltrimethylammonium bromide (CTAB), and tween 80 (TW). This study revealed that SDS significantly altered the bipolaron and polaron in the C-H deformation region and showed higher conductivity than other surfactants. Notably, the morphological shifts to a sheet-like structure when using ammonium sulfate (APS) contrasted with the particle-like form observed with ferric chloride (FeCl3). These results showed that if the oxidant changed, the bipolaron and polaron ratios in C-H deformation were unrelated to PPy morphology. However, this work showed a consistent relationship between SDS use, the bipolaron and polaron ratios in the C-H deformation, and the conductivity properties. Moreover, the natural positive charge of PPy and negatively charged SDS molecules may lead to an electrostatic interaction between PPy and SDS. This work assumes that this interaction might cause the transformation of polaron to bipolaron in the C-H deformation region, resulting in improved conductivity of PPy. This work offers more support for the future investigation of PPy characteristics.

Spectroscopic and thermal investigations on Zn2+ and Ba2+ ions modified 30TeO2-39.5B2O3-(30-x)ZnO-xBaO-0.5V2O5 (0 ≤ x ≤ 30 mol %) glass system.

Melt quenching technique was employed to prepare glasses with compositional formula 30TeO2-39.5B2O3-(30-x)ZnO-xBaO-0.5V2O5 (0 ≤ x ≤ 30 mol%). Various characterization tools viz., X-ray diffraction (XRD), Energy dispersive X-ray (EDX) includes color mapping images, X-ray photoelectron spectroscopy (XPS), Fourier transform infrared (FTIR), Raman, Differential scanning calorimetry (DSC), UV-Vis absorption and Electron paramagnetic resonance (EPR) were used in this investigation for the characterization of these glasses. The XRD patterns together with DSC thermograms asserted the amorphous nature of all glasses. FTIR and Raman vibrational analyses has unveiled the formation of B-O--Ba2+-O- and Te-O---Ba2+-O- wherein the bonds with Ba2+ ions are mostly ionic. DSC investigations disclosed that the increase of BaO at the cost of ZnO declined the crystal phases and favored the amorphosity and this behavior causes these glasses more advantageous for fiber drawing. The Urbach energy (ΔE) lies in between 0.28 and 0.57 eV and suggested the glasses containing high ZnO has less defects. EPR data validated that Ba2+ ions might surround V4+ ions as Ba2+-O-V4+=O by replacing Zn2+-O-V4+=O linkages. The other optical properties were discussed in detail by correlating the structural variations noticed from both FTIR and Raman data analyses.

Effect of particle size and composition on local magnetic hyperthermia of chitosan-Mg1-xCoxFe2O4 nanohybrid.

In this study, Mg1-xCoxFe2O4 (0≤x ≤ 1 with ∆x = 0.1) or MCFO nanoparticles were synthesized using a chemical co-precipitation method and annealed at 200, 400, 600, and 800°C respectively to investigate the structural properties of the materials by X-ray diffractometer (XRD), transmission electron microscopy (TEM), and Fourier-transform infrared spectroscopy (FTIR). Controlled annealing increased particle size for each value of x. The aim was to investigate how specific loss power (SLP) and maximum temperature (Tmax) during local magnetic hyperthermia were affected by structural alterations associated with particle size and composition. The lattice parameter, X-ray density, ionic radius, hopping length, bond length, cation-cation distance, and cation-anion distance increase with an increase in Co2+ content. Raman and FTIR spectroscopy reveal changes in cation distribution with Co2+ content and particle size. Magnetic properties measured by the physical property measurement system (PPMS) showed saturation magnetization (Ms), coercivity (Hc), remanent magnetization (Mr/Ms), and anisotropy constant (K1) of the Mg1-xCoxFe2O4 nanoparticles increase with Co2+ content and particle size. When exposed to an rf magnetic field, the nanohybrids experienced an increase in both the SLP (specific loss power) and Tmax (maximum temperature) as the particle size initially increased. However, these values reached their peak at critical particle size and subsequently decreased. This occurs since a modest increase in anisotropy, resulting from the presence of Co2+ and larger particle size, facilitates Néel and Brownian relaxation. However, for high anisotropy values and particle size, the Néel and Brownian relaxations are hindered, leading to the emergence of a critical size. The critical size increases as the Co2+ content decreases, but it decreases as the Co2+ content increases, a consequence of higher anisotropy with the increase in Co2+. Additionally, it is noteworthy that the maximum temperature (Tmax) rises as the concentration of nanohybrids grows, but the specific loss power (SLP) decreases. An increased concentration of chitosan-MCFO nanohybrids inhibits both the Néel and Brownian relaxation processes, reducing specific loss power.

Deep-Ultraviolet and Helicity-Dependent Raman Spectroscopy for Carbon Nanotubes and 2D Materials.

Recent progress of Raman spectroscopy on carbon nanotubes and 2D materials is reviewed as a topical review. The Raman tensor with complex values is related to the chiral 1D/2D materials without mirror symmetry for the mirror in the propagating direction of light, such as chiral carbon nanotube and black phosphorus. The phenomenon of complex Raman tensor is observed by the asymmetric polar plot of helicity-dependent Raman spectroscopy using incident circularly-polarized lights. First-principles calculations of resonant Raman spectra directly give the complex Raman tensor that explains helicity-dependent Raman spectra and laser-energy-dependent relative intensities of Raman spectra. In deep-ultraviolet (DUV) Raman spectroscopy with 266 nm laser, since the energy of the photon is large compared with the energy gap, the first-order and double resonant Raman processes occur in general k points in the Brillouin zone. First-principles calculation is necessary to understand the DUV Raman spectra and the origin of double-resonance Raman spectra. Asymmetric line shapes appear for the G band of graphene for 266 nm laser and in-plane Raman mode of WS2 for 532 nm laser, while these spectra show symmetric line shapes for other laser excitation. The interference effect on the asymmetric line shape is discussed by fitting the spectra to the Breit-Wigner-Fano line shapes.

Distinguishing brain tumors by Label-free confocal micro-Raman spectroscopy.

BACKGROUND: Brain tumors have serious adverse effects on public health and social economy. Accurate detection of brain tumor types is critical for effective and proactive treatment, and thus improve the survival of patients. METHODS: Four types of brain tumor tissue sections were detected by Raman spectroscopy. Principal component analysis (PCA) has been used to reduce the dimensionality of the Raman spectra data. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) methods were utilized to discriminate different types of brain tumors. RESULTS: Raman spectra were collected from 40 brain tumors. Variations in intensity and shift were observed in the Raman spectra positioned at 721, 854, 1004, 1032, 1128, 1248, 1449 cm-1 for different brain tumor tissues. The PCA results indicated that glioma, pituitary adenoma, and meningioma are difficult to differentiate from each other, whereas acoustic neuroma is clearly distinguished from the other three tumors. Multivariate analysis including QDA and LDA methods showed the classification accuracy rate of the QDA model was 99.47 %, better than the rate of LDA model was 95.07 %. CONCLUSIONS: Raman spectroscopy could be used to extract valuable fingerprint-type molecular and chemical information of biological samples. The demonstrated technique has the potential to be developed to a rapid, label-free, and intelligent approach to distinguish brain tumor types with high accuracy.