Raman Spectrograms Research Articles

Self-immunological disease aid diagnosis with ConvSANet and Eu-clidean distance

BackgroundAnkylosing spondylitis (AS), Osteoarthritis (OA), and Sjögren's syndrome (SS) are three prevalent autoimmune diseases. If left untreated, which can lead to severe joint damage and greatly limit mobility. Once the disease worsens, patients may face the risk of long-term disability, and in severe cases, even life-threatening consequences. ResultIn this study, the Raman spectral data of AS, OA, and SS are analyzed to auxiliary disease diagnosis. For the first time, the Euclidean distance(ED) upscaling technique was used for the conversation from one-dimensional(1D) disease spectral data to two-dimensional(2D) spectral images. A dual-attention mechanism network was then constructed to analyze these two-dimensional spectral maps for disease diagnosis. The results demonstrate that the dual-attention mechanism network achieves a diagnostic accuracy of 100 % when analyzing 2D ED spectrograms. Furthermore, a comparison and analysis with s-transforms(ST), short-time fourier transforms(STFT), recurrence maps(RP), markov transform field(MTF), and Gramian angle fields(GAF) highlight the significant advantage of the proposed method, as it significantly shortens the conversion time while supporting disease-assisted diagnosis. Mutual information(MI) was utilized for the first time to validate the 2D Raman spectrograms generated, including ED, ST, STFT, RP, MTF, and GAF spectrograms. This allowed for evaluation of the similarity between the original 1D spectral data and the generated 2D spectrograms. SignificantThe results indicate that utilizing ED to transform 1D spectral data into 2D images, coupled with the application of convolutional neural network(CNN) for analyzing 2D ED Raman spectrograms, holds great promise as a valuable tool in assisting disease diagnosis. The research demonstrated that the 2D spectrogram created with ED closely resembles the original 1D spectral data. This indicates that ED effectively captures key features and important information from the original data, providing a strong descript.

High-precision bladder cancer diagnosis method: 2D Raman spectrum figures based on maintenance technology combined with automatic weighted feature fusion network

BackgroundRaman spectroscopy has been extensively utilized as a marker-free detection method in the complementary diagnosis of cancer. Multivariate statistical classification analysis is frequently employed for Raman spectral data classification. Nevertheless, traditional multivariate statistical classification analysis performs poorly when analyzing large samples and multicategory spectral data. In addition, with the advancement of computer vision, convolutional neural networks (CNNs) have demonstrated extraordinarily precise analysis of two-dimensional image processing. ResultCombining 2D Raman spectrograms with automatic weighted feature fusion network (AWFFN) for bladder cancer detection is presented in this paper. Initially, the s-transform (ST) is implemented for the first time to convert 1D Raman data into 2D spectrograms, achieving 99.2% detection accuracy. Second, four upscaling techniques, including short time fourier transform (STFT), recurrence map (RP), markov transform field (MTF), and grammy angle field (GAF), were used to transform the 1D Raman spectral data into a variety of 2D Raman spectrograms. In addition, a particle swarm optimization (PSO) algorithm is combined with VGG19, ResNet50, and ResNet101 to construct a weighted feature fusion network, and this parallel network is employed for evaluating multiple spectrograms. Class activation mapping (CAM) is additionally employed to illustrate and evaluate the process of feature extraction via the three parallel network branches. The results demonstrate that the combination of a 2D Raman spectrogram along with a CNN for the diagnosis of bladder cancer obtains a 99.2% accuracy rate，which indicates that it is an extremely promising auxiliary technology for cancer diagnosis. SignificanceThe proposed two-dimensional Raman spectroscopy method has an improved precision than one-dimensional spectroscopic data, which presents a potential methodology for assisted cancer detection and providing crucial technical support for assisted diagnosis.

Characteristics and significance of the solid bitumen in the second member of Dengying Formation of Sinian system in the north of central Sichuan Basin, China

With ongoing advancements in natural gas exploration, the second member of the Sinian Dengying Formation (Deng 2 Member) has emerged as a crucial region for providing natural gas reserves in the north of the central Sichuan Basin. The Deng 2 Member has a significant volume of reservoir solid bitumen. Geochemical characteristics and development mechanism of the solid bitumen were determined through measurements and analyses of the Deng 2 Member samples collected from primary exploration wells by using optical microscopy, SEM, gas chromatograph-mass spectrometer, and laser Raman spectrometer. The results show that the Deng 2 Member has a generally high content of solid bitumen, ranging from 2.96% to 5.13% on average in single wells. The solid bitumen mainly occurs as the fillings of dissolved pores (caves) and fractures, followed by intergranular pores, in the shape of spots, balls, plates, and veins dominantly. Diasteranes content and laser Raman spectrograms indicate that the solid bitumen is in the high maturity stage. The bitumen reflectance calculated by laser Raman spectroscopy is distributed between 2.49% and 4.09%, indicating the major source of the thermal cracking of crude oil. Solid bitumen in the Deng 2 Member has different contents of 21α(H)–C29 norhopane, C35 hopane, and C34 hopane, and Ts/Tm values from the Deng 4 Member in the Gaoshiti Moxi area. It is inferred that some solid bitumen is from the source rocks of the Lower Cambrian Maidiping Formation and the Sinian Doushantuo Formation. Two stages of bitumen were developed in the Deng 2 Member, indicating possible two stages of oil filling and thermochemical sulfate reduction (TSR) in the geologic history.

Coherent anti-Stokes Raman scattering microspectroscopy: an emerging technique for non-invasive optical assessment of a local bio-nano-environment.

Raman spectroscopy provides a non-invasive, chemically-specific optical imaging of biological objects without relying on endogenous labels. Nonlinear Raman spectroscopy allows non-invasive imaging at much faster speed with an improved spatial resolution and axial sectioning capability. In this report we propose a novel use of nonlinear Raman spectroscopy as a sensor of local nano-environment. Time-resolved coherent anti-Stokes Raman spectrograms are found to be sensitive to small variations of local structural changes, which are not normally observed using conventional Raman spectroscopy.

Accurate diagnosis of lung tissues for 2D Raman spectrogram by deep learning based on short-time Fourier transform

Multivariate statistical analysis methods have an important role in spectrochemical analyses to rapidly identify and diagnose cancer and the subtype. However, utilizing these methods to analyze lager amount spectral data is challenging, and poses a major bottleneck toward achieving high accuracy. Here, a new convolutional neural networks (CNN) method based on short-time Fourier transform (STFT) to diagnose lung tissues via Raman spectra readily is proposed. The models yield that the accuracies of the new method are higher than the conventional methods (principal components analysis -linear discriminant analysis and support vector machine) for validation group (95.2% vs 85.5%, 94.4%) and test group (96.5% vs 90.4%, 93.9%) after cross-validation. The results illustrate that the new method which converts one-dimensional Raman data into two-dimensional Raman spectrograms improve the discriminatory ability of lung tissues and can achieve automatically accurate diagnosis of lung tissues.

Preparation and characterization of sintered polycrystalline diamond (PCD) with 15 wt% Nb binder

This study aimed to obtain and characterize a polycrystalline diamond body (PCD) sintered with 15 wt% Nb binder, through the high-pressure high-temperature (HPHT) sintering techniques at three different temperatures of 1650 °C, 1750 °C, and 1850 °C, with a pressure of 7.7 GPa. Characterizations on the starting powders were performed before and after high energy ball milling, and then the obtained mixture was sintered. The results showed that niobium could perform as a good binder for the sintering PCD at the specified concentration, achieving relative densities in the range of 96% to 100% for all three sintering temperatures. Also, analyses of the electron micrographs and the Raman spectrograms showed that there was no graphitization, a common problem in this type of material, and there was uniform dispersion of the niobium at the interfaces of the diamond particles, and no cracking.

Preparation, characterization of highly dispersed reduced graphene oxide/epoxy resin and its application in alkali-activated slag composites

A highly dispersed reduced graphene oxide/epoxy resin composites (HD-RGO/EP) were synthesized and applied in alkali-activated slag based composites firstly. The synthesis, characterization and application in alkali-activated slag cementitious materials of this synthesized graphene are reported in this paper. The dispersion states of the reduced graphene oxide in epoxy resin and alkali activated slag paste are proved to be sound by observation by TEM and Metallographic Microscope respectively. Both FTIR and Raman spectrograms verifies that there is no new reaction products generated under HD-RGO dispersing in the epoxy resin. It is confirmed that HD-RGO/EP increases the fracture toughness of alkali-activated slag mortar 75 times the most compared with the one blend with EP, the bonding behavior of the alkali-activated slag composite blended with HD-RGO/EP is enhanced significantly as well. HD-RGO/EP alkali-activated slag mortar is believed to have broad application prospects in repair and rehabilitation of reinforced concrete structures.

(17)O NMR and Raman Spectroscopies of Green Tea Infusion with Nanomaterial to Investigate Their Properties.

(17)O NMR and Raman spectrograms of green tea infusions with nanomaterial were investigated. Different green tea infusions were prepared by steeping tea powder with different concentrations of nanomaterial aqueous solution. The tea infusions were tested with (17)O NMR and Raman spectroscopies. The (17)O NMR results showed that line width increased to 90 in the tea infusions after nanomaterial was added as a result of the effects of the self-association of Ca(2+) and tea polyphenol. The results of Raman spectroscopy showed that, in tea infusions, the enhancement of C─C and C─O stretching vibrations suggest an increase in the number of effective components in water.

The Effect of Carbon Rod—Specimens Distance on the Structural and Electrical Properties of Carbon Nanotube

The research studies the effect of the distance between the sample and the plasma sputtering source on the properties of the junction (silicon wafer-carbon nanotubes). The silicon wafer is fixed at (near, medium and far distances from the plasma source which is in the form of high purity graphite rod heated electrically). For the three cases, thickness of the sample is constant (20 nm). The samples were studied by scanning electron (SEM) and atomic force microscopes (AFM), X-ray and Raman spectra. For optimum distances the carbon layer is in the form of multi wall carbon nanotube (MWCNT). SEM images shows no formation of CNT on the Si wafer for near distance, which is consistent with the AFM images, X-ray and Raman spectrograms and no existence of characteristics (002) peaks whereas it appears for medium and longer distances, and by experience the optimum distance was found. This means that at closer distance high energy and high intensity plasma particles prevent the formation of CNT. This effect decreases with increasing distance of substrate from the graphite rod.

Identification of Silver Nanoparticles on Polyester Fiber on Raman Spectrograms of the in the Conditions of Information Uncertainty

The paper shows the results of method development identification of colloidal silver nanoparticles on the components of the Raman spectra, using the conditions information uncertainty decision to increase the reliability evaluating the presence nanoparticles at the surface polyester fibers.

FT-IR, FT-Raman, ab initio and DFT structural and vibrational frequency analysis of 6-aminopenicillanic acid

Quantum mechanical calculations of energies, geometries and vibrational wavenumbers of 6-aminopenicillanic acid were carried out by using ab initio HF and density functional theory (DFT/B3LYP) methods with 6-311G(d,p) basis set. The optimized geometrical parameters obtained by HF and DFT calculations are in good agreement with experimental X-ray data. A detailed interpretation of the infrared spectra has also been reported. The theoretical IR and Raman spectrograms have been constructed and compared with the experimental FT-IR and FT-Raman spectra. The differences between the observed and scaled wavenumber values of most of the fundamentals are very small. The thermodynamic parameters have also been computed.

Raman characteristics of hydrocarbon and hydrocarbon inclusions

The Raman spectrograms of hydrocarbon standard samples show that: (1) the Raman spectrogram of normal paraffin has very strong peaks of methyl and methylene (from 2700 cm−1 to 2970 cm−1); (2) branch methyl has the particular peak of 748 cm−1±; (3) six cyclic has the particular peak of 804 cm−1±; (4) phenyl has two particular peaks of 988 cm−1± and 3058 cm−1± and the 988 cm−1± peak is stronger than the 3058 cm−1± peak; and (5) hexene has three alkenyl spectrum peaks of 1294 cm−1±, 1635 cm−1± and 2996 cm−1±, with the 1635 cm−1± peak being the strongest, showing that the number of carbon in hydrocarbon does not affect its Raman spectrogram, and the hydrocarbon molecular structure and base groups affect its Raman spectrogram, the same hydrocarbons (such as normal paraffin) have the same Raman spectrogram; the types (such as CH4, C2H6, C3H8) and the content of hydrocarbon in oil inclusions are not estimated by their characteristic Raman peaks. According to the Raman spectrograms of hydrocarbon compositions, the Raman spectrogram of hydrocarbon inclusion can be divided into five types: saturated hydrocarbon Raman spectrogram, fluoresce Raman spectrogram, saturated hydrocarbon bitumen Raman spectrogram, bitumen Raman spectrogram, and ethane Raman spectrogram. And according to the characteristics of Raman spectrogram, hydrocarbon inclusions can be divided into five types: saturated hydrocarbon inclusion, less saturated hydrocarbon (oil or gas) inclusion, saturated hydrocarbon bitumen inclusion, bitumen inclusion, and methane water inclusion.

Limitation of mercury doping and Raman spectra of doped Mg 1− xHg xB 2 superconductor

The undoped and mercuric-doped samples are having general formula Mg 1− x Hg x B 2 (where, x = 0.0, 0.02, 0.04 and 0.08 mole%) were prepared via high temperature solid state reaction route. The synthesis was depending upon diffusion mechanism of both Mg and Hg-vapour ions through boron-matrix. The solubility limits of mercury was found to be too tide to substitute higher than 0.08 mole% which emphasises that dopings or substitutions on MgB 2 regime is too limited and needs many precautions to be chemically successful. X-ray diffraction analysis for investigated samples proved that all samples were found mainly belong to single hexagonal phase with P6/ mmm symmetry with very small traces from MgO as secondary phase in minor. From SE-microscopy and EDX analyses only MgO was detected in between grains and no existence for any aggregations of expected HgO secondary phase. Magnetic susceptibility measurements indicated that only the sample with maximum mercuric doping ratio x = 0.08 mole% exhibited slight depression on its value of T c-offset which found to be 36.1 K Raman spectrograms recorded for samples c, d those with dopant ratio x = 0.04 and 0.08 mole%, respectively, exhibited broad lines lies at ∼430 and 550 cm −1 is attributable to strong electronic scattering caused by MgO secondary phase.

Ab initio spectrograms of the molecular vibrational spectrum

Theoretical spectrograms of the vibrational spectrum of 3,3-dimethylcyclopropene were constructed and juxtaposed with the experimental Raman and IR spectrograms. The theoretical spectrograms are represented as sets of vertical lines starting from the points corresponding to the values of the vibrational frequencies calculated from the scaled quantum-mechanical (QM) force field obtained at the HF/6-31G*//HF/6-31G* level. Two theoretical Raman spectrograms were constructed. In the first case, the heights of the vertical lines correspond to the QM values of the Raman scattering activities. In the second case they represent the relative differential Raman cross-sections calculated using the QM values of Raman scattering activities. The initial vibrational mode matrix remains virtually unchanged upon scaling of the QM force constant matrix because the dispersion of the scale factor values is low. Therefore, the heights of the theoretical lines for the IR spectrogram represent the QM intensities directly. The theoretical spectrogram based on the relative differential Raman cross-sections was shown to depict the experimental Raman spectrum more adequately. This makes it possible to use the results of the corresponding QM calculations more completely and obtain well-substantiated assignments of the vibrational frequencies.

Effects of noise on parameter recovery from Raman spectrograms

AbstractNoisy light‐based Raman spectrograms are simulated to model a single Raman‐active mode with known spectroscopic parameters. Gaussian white noise is added to the spectrograms to mimic experimental data. Two‐dimensional slices of the χ2 surface for the simulated noisy spectrograms are calculated. From the minima of a number of these surfaces, the precision of the recovered spectroscopic parameters from simulated experimental data is obtained. Three different studies dealing with various aspects of the effects of noise on the recovered parameters are presented. The advantage of noisy light‐based Raman spectrograms in yielding exquisite precision, as suggested by previous work, is verified. Furthermore, the advantage of Raman spectrograms in yielding good precision even for poor signal‐to‐noise levels is quantified. Copyright © 2001 John Wiley & Sons, Ltd.

Raman spectrograms in fifth order coherent Raman scattering: The sequential CARS process in liquid benzene

The first Raman spectrograms are reported for fifth order coherent anti-Stokes Raman scattering. The 992 cm −1 `ring breathing' mode of liquid benzene is examined using broadband, nontransform-limited, quasi-cw noisy laser light. The fifth order signal is entirely dominated by a sequential CARS process called I (3)SCARS. The vibrational Raman frequency and the dephasing rate constant for this mode is extracted from combined I (3)SCARS and I (2)CARS spectrograms with high precision and potentially high accuracy.

Raman Effect from Powdered Crystals

MAY I make the following remarks concerning Mr. A. C. Menzies' letter in NATURE of Oct. 5, p. 511, on the “Raman Effect from Powdered Crystals”. For several months I have been engaged in studying the Raman effect from different crystalline powders, and I can corroborate Mr. Menzies' statement that the reflection of the incident radiation by such powders is no obstacle in observing at least the stronger Raman lines. I tried several ways of obtaining Raman spectrograms, and found that the best results could be secured when the powdered crystals were filled into a rectangular plate-glass vessel of a few cubic centimetres contents, on which the light of a mercury arc was focused through one side surface, while the secondary radiation was observed by putting the spectrograph as close as possible to another side of the vessel perpendicular to that where the primary radiation entered.