Vibrational Spectroscopy最新文献

The bis(chloro)-bis(1,10-phenanthroline)-manganese(II) crystalline complex, with the formula [Mn(phen)₂Cl₂], was synthesized by slow evaporation method. Structural, thermal, and vibrational properties of the crystal were obtained by X-ray powder diffraction (XRPD), thermal analysis, Raman, and Fourier-transform infrared (FT-IR) spectroscopy. XRPD results showed that the crystal belongs to a monoclinic system with P2₁/c ($C_{2h}^5$) space group. Thermal analyses revealed that the material presents good stability within 300–558 K temperature interval. In addition, Hirshfeld surface analysis revealed the sites involved in intermolecular interactions predominant in the crystal. Also, all Raman and IR-active bands were assigned from computational calculations based on density functional theory (DFT) to analyze intramolecular vibration modes. Additionally, the electronic and vibrational properties were investigated considering three different media (vacuum, methanol, and water) using the integral equations formalism of the polarizable continuum model (IEFPCM). Lastly, the bactericidal assays on Staphylococcus aureus (ATCC 6538), Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 27853) e Enterococcus faecalis (ATCC 25923) were carried out to evaluate the antimicrobial activity of this complex.

It is well known that polyphenols possess potent antioxidant qualities. However, the precise antioxidant action mechanism of phenolic compounds is still not well defined. It is evident that understanding the molecular mechanisms behind polyphenol-lipid interactions is necessary to comprehend this impact. The objective of this work is to examine the effect of phenolic compound coumarin on the physicochemical properties of cell membrane models. To accomplish this goal, model membranes made up of zwitterionic dimyristoylphosphatidylcholine (DMPC) and anionic dimyristoylphosphatidylglycerol (DMPG) lipids were used. These lipid species are the main component of the mammalian and gram-positive bacteria membranes, respectively. Differential scanning calorimetry (DSC) and Raman spectroscopy were applied for studying the interaction of coumarin with DMPC and DMPG. From the DSC results, it was found that pretransition was abolished for both lipid systems at 20 mol% coumarin. Main phase transition shifted to lower temperatures and broadened, but there was not a complete disappearance of main transition and coumarin was not fully miscible. A sharp peak at a higher temperature and a broad shoulder at a lower temperature of the main transition of DMPC were detected when compared to coumarin/DMPG binary system. A reduction in calorimetric enthalpy and entropy values of coumarin/DMPC system at 20 mol% was observed whereas an increase in these calorimetric parameters for coumarin/DMPG system occurred. Thus, the disorder was caused when 20 mol% coumarin interacts with DMPC lipid bilayers. The increase in enthalpy could be a result of the 20 mol% coumarin interactions with DMPG lipid bilayers or a possible generated partial interdigitation. From the Raman results, the peak height Raman intensity ratio I₁₀₉₀/I₁₁₃₀ showed that coumarin induces disorder in the DMPG bilayers in the gel phase due to the increasing gauche:trans ratio. According to the results obtained by DSC and Raman spectroscopy, it was found that coumarin has a varied effect on membranes made from lipids with choline and glycerol head groups. Thus, it is obvious that the polyphenol/membrane interactions can be significantly impacted by the lipids’ structural variations.

The rising possibilities of vibrational spectroscopy coupled with multivariate modeling, enables many applications of these well-established analytical techniques, easy-to-use for rapid and non-destructive analysis. Owing to the lack of need for hazardous solvents or reagents in sample preparation, FTIR, NIR and Raman spectroscopy belong to the group of environmentally friendly techniques, known as “green analytical techniques”. Such characteristics re-introduce them into the pharmaceutical industry, especially as part of process-analytical-technology (PAT) tools for both qualitative and quantitative analysis.

This research aimed to assess the potential of ATR-FTIR, NIR and Raman as a PAT for the quantification of Vitamins B1 (thiamine), B6 (pyridoxine) and B12 (cyanocobalamin) in a powder blend, using a partial least square (PLS) regression model, as well as to monitor the powder blend homogeneity.

Results from each of the vibrational spectroscopy techniques were compared with those obtained by HPLC, which served as the reference analytical technique for quantifying the active substances in complex matrices using multivariate analysis. The developed PLS models were evaluated for their ability to quantify each of the active substances in the powder blend. The ATR-FTIR, NIR and Raman spectrum segments, revealed by the Variable Importance for Projection (VIP) plot for each model, respectively, were linked to the band assignment of each active ingredient.

The statistical indicators of the models (interpretation rate (R2X and R2Y), predictive ability (Q2 and RMSEP) and accuracy (RMSEE)) demonstrated their suitability for in-process estimation of vitamin B1, B6 and B12 contents in powder blends. Estimating B12 content proved more challenging, likely due to sampling issues related to its low content in the powder blend. Nevertheless, the observed variability in the models aligns with the variability in results obtained by HPLC, indicating the lack of blend homogeneity. Therefore, the quantification models could be considered for a further upgrade as PAT for monitoring the powder blend homogeneity during the manufacturing of vitamin blends.

Biomacromolecules, which mainly include nucleic acids, proteins, sugars, and lipids, are extensively present in the somatic cells of organisms. These four types of biomacromolecules not only play a crucial role in various normal physiological processes of organisms but also draw increasing attention in the field of in vitro research, such as nucleic acid aptamers and nucleotide drugs. Consequently, the accurate detection of biomacromolecules holds immense importance and significance. Surface-enhanced Raman Scattering (SERS) possesses a natural advantage in the detection of biomacromolecules due to its “fingerprint” characteristics, non-destructive nature, high sensitivity, simplicity, and speed, and it is not influenced by water signals. This paper primarily discusses the research progress of SERS in the detection of biomacromolecules, elaborates on the application of SERS in detecting nucleic acids, proteins, sugars, and lipids, and anticipates the potential application of SERS in biomacromolecule detection. It is anticipated that this paper will provide researchers with innovative ideas and methods for developing and applying new biomacromolecular detection techniques.

Tuna fish oil (TO) is a valuable source of omega fatty acids and polyunsaturated fatty acids required for human growth and development. Triggered by economic reasons, TO can potentially be adulterated with pork oil (PO), which has a lower price. The adulteration is a serious problem because PO is a non-halal oil, which is truly prohibited to be consumed, especially for Muslim. This research aimed to develop an effective and efficient analytical technique for detecting PO adulteration in TO using Fourier transform infrared (FT-IR) spectroscopy aided by machine learning techniques. Various machine learning techniques were developed, including linear regression, support vector machine (SVM), k-nearest neighbor (kNN), artificial neural network (ANN), and gradient boosting. The result showed that SVM at the fingerprint region (1400–900 cm⁻¹) demonstrated the best model to detect and predict PO in TO with the highest R² (0.993) and the lowest root mean square error (RMSE) of 2.719 %. All levels of PO contained in TO could be accurately predicted, as indicated by the closeness between the actual value and predicted value of PO levels predicted by the model. In conclusion, machine learning could be a promising tool for detecting adulterants in fish oil samples. Further research on method standardization is important to propose the method as the method of choice for fish oil authentication, including halal authentication.

The intention of this review is to reflect on the development of ultrafast 2D-IR spectroscopy to date and to attempt to envisage how the technique might develop in the period between now and 2050. As ultrafast 2D-IR spectroscopy measurements were first-reported in 1998, the timing of this article represents a ‘halfway’ stage, allowing us to look back on 26 years of development to provide a perspective on what the next 26 years might bring. We begin by briefly introducing the method and summarising the development of 2D-IR experiments thus far, but then focus on the most recent advances in technology, sample handling and data analysis methods to inform a discussion on the direction of travel for the field in terms of measurement capabilities. Finally, we examine the most recent applications of 2D-IR, with a particular focus on emerging research areas to show how the field continues to explore new challenges and provide novel insights.

During emergency inspections, drug control institutions often encounter samples with unknown components. It is essential to develop a method for quickly identifying these unknown components. Transforming the component analysis problem into a multi-label classification problem, this study addresses this challenge by employing non-destructive spectroscopic technology combined with machine learning. Spectral data from 368 compounds were initially collected for modeling. The ResUCA model was developed based on the residual neural network and compared with other models. Using the same data enhancement method, ResUCA outperformed the other models in terms of accuracy, recall, precision and F1_score. Subsequently, optimization was performed, considering factors such as data augmentation, spectrum selection, and sample processing, all of which impact the model's construction. Finally, the model was expanded in two steps, maintaining a consistently high recall rate, albeit with an increase in false positives. This suggests that fine-tuning the model parameters can help mitigate this challenge in various scenarios, highlighting its potential for ongoing optimization in future research efforts. Additionally, its applicability extends across diverse fields, including food, cosmetics, and coating analysis.

The field of vibrational biospectroscopy has undergone continuous evolution, advancing from its earliest pioneers to the current innovators. Emerging frontier technologies have enabled vibrational biospectroscopy to reach new heights, expanding its applications in biomedical and clinical settings. Key advancements include the incorporation of multimodal spectroscopy, improvements in spatial resolution and the miniaturization of spectrometers coupled with machine learning. Multimodal spectroscopy is a growing subfield within vibrational biospectroscopy, offering different perspectives of the same sample to better understand the origins of vibrational modes. Meanwhile, the miniaturization of spectrometers has opened the door for field studies and personalized diagnostics, made possible by the integration of machine learning. The combination of miniaturized spectrometers and machine learning has paved the way for novel disease detection approaches. This review will discuss the historical progression of vibrational biospectroscopy and its potential for future applications, with a particular focus on the use of machine learning, multimodal spectroscopy, and miniaturized spectrometers in biomedicine. The primary goal of this review is to provide insight into the prospects of vibrational biospectroscopy, identify gaps in the current literature for future applications, and assess the potential impact of this field in the biomedical domain.

We report the simulations of coherent supercontinuum generation from 2.63 to 8.04 μm in a silicon germanium photonic waveguide. The influence of input quantum noise pulses on coherence of the generated spectra was investigated. A high value of first order degree of coherence (i.e. 0.98) on supercontinuum spectra was predicted numerically. Our mid-infrared simulated coherent chirped supercontinuum source was then used as the input light source in absorption spectroscopy of carbon dioxide and methane gases. The simulated absorbance spectra for these greenhouse gases have high molecular contrast, thanks to the intense, chirped supercontinuum used.

Liquid crystalline properties of the synthesized liquid crystal (LC) N-(o-hydroxybenzylidene)-N'-(4-n-alkoxybenzylidene) azines (HBDBA) are probed thoroughly using the comprehensive array of techniques e.g. differential scanning calorimetry (DSC), differential thermal analysis (DTA), polarizing optical microscopy (POM), temperature-dependent Raman spectroscopy and density functional theory (DFT) method. In this study, intricate molecular interactions crucial for mesophase formation of liquid crystalline system HBDBA and molecular rearrangement that occurs during LC transitions are unravelled comprehensively. Remarkably, at the Cr → SmA phase transition, the peak position, linewidth, and intensity of signature Raman bands are prominently changed. A thorough analysis of Raman marker bands and DFT calculation confirm the disruption of intramolecular hydrogen bonds in HBDBA at the Cr → SmA transition. The conclusion of the present study enriches the understanding of the underlying mechanisms of mesophase formation and intricate molecular interactions and arrangement at the molecular level of the thermotropic LC.