Journal of Spectroscopy
 Journal metrics
See full report
Acceptance rate41%
Submission to final decision79 days
Acceptance to publication23 days
CiteScore3.500
Journal Citation Indicator0.490
Impact Factor1.750

Effect of Laser Heating on Partial Decomposition of Bi12SiO20 (BSO) Single Crystal: Raman Study

Read the full article

 Journal profile

Journal of Spectroscopy publishes research into the theory and application of spectroscopy across all disciplines, including biology, chemistry, engineering, earth sciences, medicine, materials science, physics, and space science.

 Editor spotlight

Chief Editor Dr Daniel Cozzolino is based at the University of Queensland, Australia. His research focuses on the developments of chemometric and spectroscopic methods for use in agriculture and food applications.

 Special Issues

Do you think there is an emerging area of research that really needs to be highlighted? Or an existing research area that has been overlooked or would benefit from deeper investigation? Raise the profile of a research area by leading a Special Issue.

Latest Articles

More articles
Research Article

Multivariate Image Analysis Applied to Cross-Laminated Timber: Combined Hyperspectral Near-Infrared and X-ray Computed Tomography

Engineered wood products, such as cross-laminated timber (CLT), are becoming more popular in the designs of modern sustainable buildings. This increased production of CLT requires more robust, yet less labour-intensive means to assess the material characteristics of whole CLT panels. In exploring ways of improving efficiency, this study explores multivariate image analysis (MIA) via partial least squares discriminant analysis (PLS-DA) machine learning as a means to classify CLT material features. CLT panels underwent nondestructive testing using near-infrared (NIR) hyperspectral imaging and X-ray computed tomography (CT) analysis. MIA was performed on these results to build predictive models for wood features, such as fibre alignment and knot type. The models showed that it was possible to classify material features on the surface of CLT using NIR alone; whilst when combined with X-ray data, it enhanced the predictive ability of material features throughout the CLT volume. These first results from such modelling have the potential to help map the chemical and physical material properties of CLT, improving the manufacturing efficiency of the product and allowing greater sustainability of engineered wood products.

Research Article

Optical Design and Simulation of Snapshot Hyperspectral Dental Imaging Spectrometer with One-Dimensional Random Coding

To achieve perfect teeth color reproduction, we propose the design of a snapshot hyperspectral imaging spectrometer that can accurately measure the teeth spectrum. In this paper, the optical system of a snapshot hyperspectral dental imaging spectrometer is designed. In particular, to encode images in both the spatial and spectral dimensions, a one-dimensional random coding mask rotated 45 degrees around the optical axis is used. The system has a spectral resolution of approximately 2.2∼10 nm in the 450∼700 nm spectral range, and the total length of the system is less than 150 mm. The whole design can be used as a miniaturized handheld instrument. To verify the feasibility of whiteness measuring, a simulation experiment is carried out. The target spectral information is reconstructed through the reconstruction algorithm. The simulation result shows that spectral imaging has the potential to improve the accuracy and precision of teeth whiteness measurements.

Research Article

The Ultraviolet-Visible Luminescence of Ce3+ in Ca2Mg(BO3)2 Phosphors with Potential Applications

New phosphors Ca2Mg(BO3)2: Ce3+ were synthesized by the solid-state reaction method at a high temperature. The phase purity was characterized by powder X-ray diffraction (XRD). The ultraviolet-visible (UV-Vis) optical properties of Ce3+ have been investigated, and the lowest 5d levels, the emission, and the Stokes shifts of Ce3+ in the host lattice were identified. In addition, its concentration quenching process was also studied. The results show that Ce3+ ions enter Ca2+ sites with only one emission in a UV-Vis range and that the optimum doping concentration is x = 0.05. The excitation and emission spectra were evaluated to clearly reveal luminescence features.

Research Article

Study of the Hydration Mechanism of Portland Cement with Raman Spectroscopy Applying CO2 Laser Radiation

This work presents the results by irradiating fresh Portland cement pastes with CO2 laser, at powers of 1.6, 2.0, and 2.4 W, at different water-to-cement (w/c) ratios 0.4, 0.45, and 0.5. Raman spectra show the evolution and accelerated growth of the main hydration products through the intensity changes of the Raman signal. The Raman shifts reveal that the C-S-H, CH, AFt, and CaCO3 bands are detected in a shorter time, which means that the setting times are also reduced. The detected band of calcium carbonate, which is due to the incorporation of limestone during the grinding process, shows that it is responsible largely for the acceleration in the reactions during the hydration of the cement. The Raman signals of the hydration products of nonirradiated cement pastes present a delay in their evolution with respect to the irradiated pastes. The curves obtained from the Raman spectra can be used to model the mechanism of hydration as well as to understand the setting process.

Research Article

Study of the Binding of Cuminaldehyde with Bovine Serum Albumin by Spectroscopic and Molecular Modeling Methods

Here, we investigated the interaction of cuminaldehyde with a model carrier protein, bovine serum albumin (BSA). The formation of the BSA–cuminaldehyde complex was confirmed through ultraviolet–visible (UV–Vis) spectroscopy and further proven by detailed intrinsic fluorescence spectroscopic measurements. As observed, cuminaldehyde quenched the intrinsic tryptophanyl fluorescence of BSA. The fluorescence data, before the analyses, were corrected for the inner filter effect (IFE) because of the significant absorption of cuminaldehyde at the excitation wavelength that was employed in the measurements. The typical Stern–Volmer plots were slightly nonlinear; they exhibited negative deviation toward the x-axis, a typical phenomenon that is observed with proteins possessing more than one tryptophan residue. Thus, the modified Stern–Volmer equation was employed to analyze the data. The analyzed data revealed that the interaction of cuminaldehyde with BSA proceeded via a static quenching mechanism and that there was a fair 1 : 1 binding between them. The interaction was strengthened by hydrophobic forces and hydrogen bonding. A lowered concentration of cuminaldehyde did not affect the secondary structure of BSA, although an increased one partially exposed the protein by decreasing its α-helical contents. The molecular dockings and simulations of BSA and cuminaldehyde further confirmed the formation of the stable BSA–cuminaldehyde complex. The in silico results also revealed that the contributions of the hydrophobic interaction and hydrogen bonding were the driving forces that imparted the stability.

Research Article

Quantitative Detection of Quartz Sandstone SiO2 Grade Using Polarized Infrared Absorption Spectroscopy with Convolutional Neural Network Model

As an independent characteristic of electromagnetic radiation, the polarization of light is sensitive to the scattering and absorption characteristics of the mineral particles. The combination of polarization and infrared absorption spectroscopy is conducive to rapidly and accurately detecting the SiO2 content of metallurgical sandstone deposits. In this study, the 8–14 μm polarized infrared absorption spectra and the grade of the sandstone ore samples were used to analyse the spectral characteristics of the sandstone powder samples. Principal component analysis (PCA) and the successive projection algorithm (SPA) were used to reduce the dimension of the original data, first-order derivative, reciprocal logarithm, and multivariate scattering correction (MSC) data. Then, generalized regression neural network (GRNN), partial least squares regression (PLSR), and convolutional neural network (CNN) were employed to establish a hyperspectral prediction model of SiO2 grade. The results show that the quantitative model by the PCA-CNN algorithm has the better prediction precision for the reciprocal logarithm data, with a coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to interquartile range (RPIQ) of 0.907, 0.023, and 5.11, respectively. This method indicates that the polarized infrared absorption spectra and the PCA-CNN model can provide a more robust and significant spectral interpretation than single infrared spectra, and it is expected to be applied to any high-purity quartz deposit type for in situ and rapid analysis.

Journal of Spectroscopy
 Journal metrics
See full report
Acceptance rate41%
Submission to final decision79 days
Acceptance to publication23 days
CiteScore3.500
Journal Citation Indicator0.490
Impact Factor1.750
 Submit

Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.