Identification of Magnesium Oxychloride Cement Biomaterial Heterogeneity using Raman Chemical Mapping and NIR Hyperspectral Chemical Imaging

Anharmonic DFT Study of Near-Infrared Spectra of Caffeine: Vibrational Analysis of the Second Overtones and Ternary Combinations

Anharmonic quantum chemical calculations were employed to simulate and interpret a near-infrared (NIR) spectrum of caffeine. First and second overtones, as well as binary and ternary combination bands, were obtained, accurately reproducing the lineshape of the experimental spectrum in the region of 10,000–4000 cm⁻¹ (1000–2500 nm). The calculations enabled performing a detailed analysis of NIR spectra of caffeine, including weak bands due to the second overtones and ternary combinations. A highly convoluted nature of NIR spectrum of caffeine was unveiled, with numerous overlapping bands found beneath the observed spectral lineshape. To properly reflect that intrinsic complexity, the band assignments were provided in the form of heat maps presenting the contributions to the NIR spectrum from various kinds of vibrational transitions. These contributions were also quantitatively assessed in terms of the integral intensities. It was found that the combination bands provide the decisively dominant contributions to the NIR spectrum of caffeine. The first overtones gain significant importance between 6500–5500 cm⁻¹, while the second overtones are meaningful in the higher wavenumber regions, particularly in the 10,000–7000 cm⁻¹ region. The obtained detailed band assignments enabled deep interpretation of the absorption regions of caffeine identified in the literature as meaningful for analytical applications of NIR spectroscopy focused on quantitative analysis of caffeine content in drugs and natural products.

Synthesis, Structure, and Thermal Stability of Magnesium Oxychloride 5Mg(OH)2∙MgCl2∙8H2O

Today, low-energy and low-carbon footprint alternatives to Portland cement are searched because of huge CO2 emissions coming from Portland clinker calcination. Because of some superior properties of magnesium oxychloride cement (MOC) and the lower carbon footprint of its production, MOC became an intensively studied material with high application potential for the design and development of construction products. In this contribution, magnesium oxychloride with stoichiometry 5Mg(OH)2∙MgCl2∙8H2O (Phase 5) was prepared and characterized. The kinetics of formation and the phase composition of the material were determined using X-ray diffraction and consequent Rietveld analysis. The morphology was studied by scanning electron microscopy, and the chemical composition was determined by both energy-dispersive spectroscopy and X-ray fluorescence. Moreover, the simultaneous thermal analysis in combination with mass spectroscopy and Fourier-transform infrared spectroscopy was employed to study the thermal stability. Using mass spectroscopy, we were able to clarify the mechanism of water and hydrochloric acid release, which was not previously reported. The observed structural and chemical changes induced by exposure of studied samples to elevated temperatures were linked with the measured residual macro and micro parameters, such as bulk density, specific density, porosity, water absorption, compressive strength, and pore size distribution. The Phase 5 revealed a needle-like crystalline morphology which formed rapidly and was almost completed after 96 h, resulting in relatively high material strength. The four-day compressive strength of magnesium oxychloride cement was similar to the 28-day compressive strength of Portland cement. The thermal stability of Phase 5 was low as the observed disruptive thermal processes were completed at temperatures lower than 470 °C.

Simulated NIR spectra as sensitive markers of the structure and interactions in nucleobases

Near-infrared (near-IR; NIR) spectroscopy is continuously advancing in biophysical and biochemical fields of investigation. For instance, recent progresses in NIR hyperspectral imaging of biological systems may be noted. However, interpretation of NIR bands for biological samples is difficult and creates a considerable barrier in exploring the full potential of NIR spectroscopy in bioscience. For this reason, we carried out a systematic study of NIR spectra of adenine, cytosine, guanine, and thymine in polycrystalline state. Interpretation of NIR spectra of these nucleobases was supported by anharmonic vibrational analysis using Deperturbed Vibrational Second-Order Perturbation Theory (DVPT2). A number of molecular models of nucleobases was applied to study the effect of the inter-molecular interactions on the NIR spectra. The accuracy of simulated NIR spectra appears to depend on the intra-layer interactions; in contrast, the inter-layer interactions are less influential. The best results were achieved by combining the simulated spectra of monomers and dimers. It is of particular note that in-plane deformation bands are far more populated than out-of-plane ones and the importance of ring modes is relatively small. This trend is in contrast to that observed in mid-IR region. As shown, the local, short-range chemical neighborhood of nucleobase molecules influence their NIR spectra more considerably. This suggests that NIR spectra are more sensitive probe of the nucleobase pairing than mid-IR ones. The obtained results allow, for the first time, to construct a frequency correlation table for NIR spectra of purines and pyrimidines.

Tsallis-Entropy Segmentation through MRF and Alzheimer anatomic reference for Brain Magnetic Resonance Parcellation

Quantifying the intracranial tissue volume changes in magnetic resonance imaging (MRI) assists specialists to analyze the effects of natural or pathological changes. Since these changes can be subtle, the accuracy of the automatic compartmentalization method is always criticized by specialists. We propose and then evaluate an automatic segmentation method based on modified q-entropy (Mqe) through a modified Markov Random Field (MMRF) enhanced by Alzheimer anatomic reference (AAR) to provide a high accuracy brain tissues parcellation approach (Mqe-MMRF). We underwent two strategies to evaluate Mqe-MMRF; a simulation of different levels of noise and non-uniformity effect on MRI data (7 subjects) and a set of twenty MRI data available from MRBrainS13 as patient brain tissue segmentation challenge. We accessed eleven quality metrics compared to reference tissues delineations to evaluate Mqe-MMRF. MRI segmentation scores decreased by only 4.6% on quality metrics after noise and non-uniformity simulations of 40% and 9%, respectively. We found significant mean improvements in the metrics of the five training subjects, for whole-brain 0.86%, White Matter 3.20%, Gray Matter 3.99%, and Cerebrospinal Fluid 4.16% (p-values < 0.02) when Mqe-MMRF compared to the other reference methods. We also processed the Mqe-MMRF on 15 evaluation subjects group from MRBrainS13 online challenge, and the results held a higher rank than the reference tools; FreeSurfer, SPM, and FSL. Since the proposed method improved the precision of brain segmentation, specifically, for GM, and thus one can use it in quantitative and morphological brain studies.

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Several techniques rely on detection of fluorescence signals to identify or study phenomena or to elucidate functions. Separation of these fluorescence signals were proven cumbersome until the advent of hyperspectral imaging, in which fluorescence sources can be separated from each other as well as from background signals and autofluorescence (given knowledge of their spectral signatures). However, traditional, emission-scanning hyperspectral imaging suffers from slow acquisition times and low signal-to-noise ratios due to the necessary filtering of both excitation and emission light. It has been previously shown that excitation-scanning hyperspectral imaging reduces the necessary acquisition time while simultaneously increasing the signal-to-noise ratio of acquired data. Using commercially available equipment, this protocol describes how to assemble, calibrate, and use an excitation-scanning hyperspectral imaging microscopy system for separation of signals from several fluorescence sources in a single sample. While highly applicable to microscopic imaging of cells and tissues, this technique may also be useful for any type of experiment utilizing fluorescence in which it is possible to vary excitation wavelengths, including but not limited to: chemical imaging, environmental applications, eye care, food science, forensic science, medical science, and mineralogy.

Breakthrough Potential in Near-Infrared Spectroscopy: Spectra Simulation. A Review of Recent Developments

Near-infrared (12,500–4,000 cm⁻¹; 800–2,500 nm) spectroscopy is the hallmark for one of the most rapidly advancing analytical techniques over the last few decades. Although it is mainly recognized as an analytical tool, near-infrared spectroscopy has also contributed significantly to physical chemistry, e.g., by delivering invaluable data on the anharmonic nature of molecular vibrations or peculiarities of intermolecular interactions. In all these contexts, a major barrier in the form of an intrinsic complexity of near-infrared spectra has been encountered. A large number of overlapping vibrational contributions influenced by anharmonic effects create complex patterns of spectral dependencies, in many cases hindering our comprehension of near-infrared spectra. Quantum mechanical calculations commonly serve as a major support to infrared and Raman studies; conversely, near-infrared spectroscopy has long been hindered in this regard due to practical limitations. Advances in anharmonic theories in hyphenation with ever-growing computer technology have enabled feasible theoretical near-infrared spectroscopy in recent times. Accordingly, a growing number of quantum mechanical investigations aimed at near-infrared region has been witnessed. The present review article summarizes these most recent accomplishments in the emerging field. Applications of generalized approaches, such as vibrational self-consistent field and vibrational second order perturbation theories as well as their derivatives, and dense grid-based studies of vibrational potential, are overviewed. Basic and applied studies are discussed, with special attention paid to the ones which aim at improving analytical spectroscopy. A remarkable potential arises from the growing applicability of anharmonic computations to solving the problems which arise in both basic and analytical near-infrared spectroscopy. This review highlights an increased value of quantum mechanical calculations to near-infrared spectroscopy in relation to other kinds of vibrational spectroscopy.