Journal of Raman Spectroscopy最新文献

Raman spectroscopy can be effectively used for detection and analysis of chemical agents that are serious threats in modern warfare, but the detection and analysis performance is prone to deterioration due to noise. The existing denoising technique has limitations that there is no criterion for selecting the window length and that the filtering distorts the peaks, key features for Raman spectral data analysis. To overcome such limitations, in this paper, we propose the peak-aware adaptive denoising for Raman spectroscopy based on machine learning approach. The proposed technique utilizes the information of detected peaks to eliminate noise effectively using different window values optimal for each region in the Raman spectrum while preserving the shape of peaks. We conducted the various analyses and experiments, and the proposed technique showed a 28% lower Euclidean distance and a 48% lower Fréchet inception distance compared to the existing technique, meaning the proposed technique outperformed the existing one.

Tumors are characterized by abnormal cell growth, which leads to uncontrolled cell proliferation, invasion of surrounding tissues, and potential metastasis to other parts of the body. Current treatments for tumors include surgery, chemotherapy, radiotherapy, targeted therapy, and biological therapy. However, many tumors are detected at advanced stages, limiting the effectiveness of these treatments. Therefore, there is a need to develop more sensitive and efficient techniques to improve patient survival rates. Surface-enhanced Raman scattering (SERS) technology is a highly sensitive molecular detection and characterization technique. It can be combined with histomorphology, immunolabeling assays, and molecular hybridization to achieve quantitative diagnosis at morphological, molecular, and genetic levels. SERS offers advantages such as objectivity, reproducibility, and comparability. However, there are challenges to address, including complex substrate or probe preparation, cumbersome data analysis, and signal reproducibility and reliability. To fully utilize the potential of SERS in the biomedical field and for clinical translation, it is important to optimize the technology and develop more sensitive, accurate, and reliable substrate or probe preparation and analysis methods. This review aims to comprehensively explain the mechanism and unique advantages of SERS technology and discuss its current status, challenges, and prospects in tumor-related research.

Processing a graphene surface by irradiation with a fs-pulsed laser at energies below the ablation threshold allows the production of non-thermally modified regions with slightly different properties than pristine graphene. Oxidized nanoislands, optical forging, and nanopore networks are modifications of the graphene structure recently reported using a wide range of fs-laser energies. In this work, we first determined the pulse energy threshold of a fs-laser for the ablation of a commercial CVD graphene sample. Then we irradiated the sample in an extended range of pulse energies relative to the ablation threshold value. The irradiation process was simultaneously monitored by Raman spectroscopy, and the evolution of each Raman parameter (central position, bandwidth, and intensity) was analyzed. Special attention was given to the pulse energy that produced linear relationships between most Raman parameter pairs. These linear correlations evidence the interrelation between multiple Raman parameters and a soft processing method applicable to the controlled modification of the graphene lattice.

A three-dimensional (3D) plasmonic substrate was developed using gold nanorods (GNRs) onto a tapered fiber surface using optical tweezing. To determine the efficacy of the substrate, Raman spectra of two toxic chemicals Rhodamine 6G (R6G) and Crystal Violet (CV) were studied. The “dip and dry” method was used to adsorb the chemicals along the tapered fiber length. The minimum concentration detected for CV and R6G was 10⁻¹² M. We have reported the characteristics and unique features of the manufactured substrate.

In this publication, we demonstrate the extension of our loss-less library approach previously limited to fitting ro-vibrational N₂ CARS spectra for thermometry purposes to accurate and efficient fitting of dual-pump CARS spectra with multiple species. The fundamental reasoning behind the compression approach is to make use of finite resolution effects arising from the laser linewidths, which are typically larger than the transitional linewidths. For accurate reconstruction at runtime of the fit, in addition to the squared modulus and real component, also the imaginary component as well as intra-region species cross terms have to be compressed and tabulated for dual-pump multi-species spectra. The resulting libraries do not require to tabulate combinations of mole fractions, leading to a near linear growth of the library with respect to the number of species. The accuracy and computational efficiency of the method is benchmarked using a reference implementation provided alongside this publication. Library generation times, mainly depending on the underlying spectral model, are typically in the order of seconds to a few minutes. The simulation of a single dual-pump spectrum containing three species is sped up by a factor of >5000 without significantly affecting the accuracy of reconstruction. In a simulated experiment with Stokes-noise imposed data, the time required to it temperature, mole fraction of three resonant species and wavenumber shift on a single spectrum required $�\approx$90 ms.

The present study evaluated the eating quality of uncooked white rice using Raman spectroscopy, operating with a 532 nm excitation beam, in conjunction with multivariate calibration. This analysis was performed to establish correlations between features of the spectra and the results of conventional sensory tests with the aim of establishing calibration models. The accuracy of each model was confirmed based on the associated coefficient of determination (R²), root-mean-square error of calibration and root mean square error of prediction values. Models based on partial least-squares regression provided reasonable predictions (R² > 0.8) for the eating quality of white rice. In addition, the components affecting total evaluation were evaluated using the variable importance in projection technique, and the results showed that starch, amylose, amino acids, glucans, carbohydrates, and proteins are all crucial in terms of determining the quality of white rice. This newly developed method is likely to be suitable for the evaluation of rice quality and, in principle, could also be applied to the assessment of other foods.

The main structural building blocks that form manganese oxides are MnO₆ octahedra; these share corners and edges to construct specific structures, which can either be tunneled or layered. In the layered structures, that is, phyllomanganates, the MnO₆ octahedra form sheets, which, in turn, alternate with sheets of metal oxides and H₂O. These metal ions can vary (Zn, Co, Ni, Al, Li, …) and give rise to an entire range of different metal oxides. The characterization of these layered materials is important as they have various economical/industrial applications. Birnessite-type materials, a specific type of layered manganese oxides, are widely studied for their use as cathode materials in alkali-ion batteries. Phyllomanganates are also commonly found as constituents in sediments and soils or as coatings on rock surfaces. Their natural occurrence as black colored components have ensured that these minerals were also applied as pigments in archaeological and historical contexts. They are, for example, often found in rock art paintings and on pottery. As the oxides are used in unique archaeological objects, Raman spectroscopy is an evident choice for characterization due to its non-destructive nature of analysis. In the current study, five mineral samples of (layered) manganese oxides are analyzed with different Raman instrumentations, including mobile systems and a benchtop micro-Raman setup. The characterization of each selected manganese oxide and their comparison with literature data is discussed for the micro-Raman instrumentation. In addition, the ability of identifying and characterizing layered manganese oxides and the possible challenges when using mobile instrumentation are discussed as well.

The archaeological excavations in the site of ‘Piana di San Martino’ (Pianello Val Tidone, Piacenza, Italy) discovered several fragments of pietra ollare (soapstone) artefacts, dating back to the Medieval period. A selection of fragments was characterized with micro-Raman spectroscopy in order to determine their composition, in terms of main and accessory species. The morphology of the crystals and the mineral phases were also investigated with polarized-light microscopy observations, X-ray powder diffraction and Scanning Electron Microscopy with Energy-Dispersive System analyses, which corroborate the Raman results. A detailed characterization was obtained on 12 fragments ascribable to pots and a millstone, made of talc-schists or chlorite-schists, including garnet-bearing chlorite-schists. Interest findings about the activities related to the use of these artefacts and the alteration processes occurred during their burial period were highlighted by the identification of specific products. Additionally, mobile Raman measurements were performed on the fragments, and a quick and effective evaluation of their composition was successfully achieved. These results highlight the use of mobile Raman instruments in the field of archaeology, specifically referred to pietra ollare findings, for which a preliminary identification may be obtained directly in situ.

In this introduction to the Journal of Raman Spectroscopy special issue “Advanced Raman procedures applied to natural/cultural heritage and forensic questions: Mobile set-up, data treatment and associated techniques,” the aim is to assess the state of the art in the field and to highlight potential new perspectives. The novel approaches employed in the published papers are described and can be grouped as such: application of multivariate statistical analysis to Raman spectra, use of mobile instrumentations directly in situ for both cultural and forensic contexts, tackling with optics and spectral range issues, and coupling with mobile instrumentations based on different analytical techniques.