Vibrational Spectroscopy最新文献

As a dihydrochalcone natural sweetener extracted from Lithocarpus litseifolius, trilobatin is an emerging functional sweetener in the international arena in recent years and is gaining attention in the food industry. The detection of trilobatin has also gradually received the attention of researchers, however, the detection means for trilobatin still remain in the traditional high performance liquid chromatography (HPLC) and other traditional methods, which are costly and have a large detection range. In this work, a method based on the principle of surface-enhanced Raman (SERS) using a composite substrate of silver nanoparticles (Ag NPs) and covalent organic frameworks (COFs) materials is proposed for the detection of trilobatin in tea beverages. After Gaussian simulation and a series of spectral analysis methods for validation, the functionalized SERS substrates contain abundant hydroxyl groups on the surface, which can be combined with trilobatin through hydrogen bonding and greatly enhance the Raman signal of trilobatin. The specific detection of trilobatin in tea beverages has been realized and the problem of weak SERS signal of trilobatin in liquid environment has been solved. The limit of detection (LOD) of trilobatin in tea beverage was 2.8 nM, and the correlation coefficient (R²) was 0.995. The recoveries were in the range of 100.6∼106.0% with the RSD of 1.756∼4.921%. In conclusion, the experimental method is highly sensitive and specific, and can realize the nondestructive detection of trilobatin in samples with high practical value.

We report results from a study of the local structure of hydrated nanocrystalline 2 $\mu$m films of the well known proton conductor BaZr_1-xSc_xO_3-x/2 with x = 0.45, 0.54 and 0.64, using infrared (IR) spectroscopy. The films were prepared by magnetron sputtering. Analysis of the IR spectra focused on the O–H stretching region (2000—3700 cm^-1), which reveals the presence of several distinct O–H stretching bands for which the intensity and frequency of each band vary in an unsystematic manner with Sc concentration. The spectra for the two higher Sc concentrations, x = 0.54 and 0.64, exhibit a distinct, highly intense O–H stretching band centered at around 3400–3500 cm^-1, which is assigned to relatively symmetric, weakly hydrogen-bonding, proton configurations. The spectrum for the lower Sc concentration, x = 0.45, does not feature such a band but a broader, weaker, O–H stretching band between approximately 2500 and 3700 cm^-1, suggesting that the protons are more homogeneously distributed over a range of different local proton coordinations in this relatively weakly doped material. A comparison to the IR spectra of powder samples of similar compositions suggests that for x = 0.45, the spectra and proton coordination of films and powder samples are similar, whereas for x = 0.54 and 0.64, a larger fraction of protons seems to be located in weakly hydrogen-bonding proton configurations in the films compared to the respective powder samples.

As a traditional Chinese medicine, Panax notoginseng (Burk.) F.H.Chen (P. notoginseng) is abundant in chemical compounds, particularly the high content of saponin compounds, which have been extensively implemented in clinical treatment. The traditional chemical methods have drawbacks of destroying samples and taking a long time to analyze the saponin compounds content. In this study, we investigated the viability of employing Fourier transform near infrared spectroscopy (FT-NIR) to assess the saponin compounds content of P. notoginseng rapidly. The partial least squares regression (PLSR) prediction model was established based on spectral information from 252 samples. The effects of various variable selection methods, including variable importance in projection (VIP), competitive adaptive reweighted sampling (CARS), uninformative variables elimination (UVE), and correlation coefficients (Correlation) on the model performance, were compared. One examined variable selection algorithm that stood out was the correlation coefficient method. The Correlation-PLSR model’ calibration and prediction sets had a high coefficient of determination (Rc²: 0.966-0.989; Rp²: 0.968-0.999) and low root mean square error (RMSEC: 1.293-5.984; RMSEP: 0.291-1.810). It was indicated it can rapidly predict saponin compounds in P. notoginseng. This study offers a rapid and reliable quantitative method for P. notoginseng quality control.

Laser-induced photo damage of the optically confined microorganism is known to affect the bacterial membrane. We record the Raman spectra of a live, optically trapped Bacillus subtilis at different trapping time lapses to determine the changes in the bacterial membrane, which in turn impacts the flagellar rotation. A 1064 nm tightly focused laser traps a single de-flagellated bacterium and Surface Enhanced Raman Scattering (SERS) signals are recorded with silver nanoparticles (AgNPs) inserted into bacteria via the internal colloid method. The internal colloid method, albeit resulting in a modest signal increase, is employed in preference here to prevent undesirable cell aggregation or instabilities in trapping or compromised cell integrity resulting from the conventional nanoparticle dressing of the cell membrane. The second derivative of the Raman spectrum reveals subtle changes in the molecular structure of the bacterial membrane manifested by shifts in the phospholipid peak (1462 cm⁻¹), amide III peak (1245 cm⁻¹) and cytosine peak (792 cm⁻¹), with increased trapping duration. This is followed by a Principal Component Analysis (PCA) to examine the changes occurring in the Raman spectral range (600 cm⁻¹–1800 cm⁻¹). By comparing the spectral shifts at specific time lapses from the moment of trapping, with the diminishing frequency of rotation of the body and flagella of the trapped flagellated counterpart bacterium at these same time lapses, we establish a direct correlation between the changes in membrane structure and compromised rotation of the bacterium during photodamage. Our results confirm that the subtle changes that occur at the biomolecular level in a cell when subjected to photodamage can be identified with good sensitivity, and moreover, that the changes occurring at the biomembrane have a role to play in reduced rotation of the trapped bacterium during exposure to the laser.

Escherichia coli, Listeria monocytogenes, and Salmonella typhi are three pathogens commonly found in food. Label-free enhanced substrates have limitations in achieving high sensitivity in three bacteria detection. To enable low-concentration detection and differentiation of foodborne pathogens, this research presents an optimized detection strategy using Au @Ag NPs as the enhancing substrate for SERS technology. The impact of the particle size of Au @Ag NPs and the pH of the borate buffer solution on enhancing the Raman signals of these bacteria was investigated through electromagnetic and chemical enhancement mechanisms. By evaluating the intensity of bacterial Raman spectra, and employing chemometric techniques, the concentration and classification of the three bacterial species were predicted and analyzed. The research findings revealed that the optimized detection method was able to detect three pathogens at the concentration lower than 3 lg CFU/mL. Logarithmic fitting of the bacteria enabled prediction correlations above 0.98 and prediction root mean square errors below 0.17. After normalizing, efficient discrimination of low-concentration bacteria was achieved using the PLS-DA, with a classification prediction correlation greater than 0.94. The fabrication process of the proposed enhancement substrate is simple, but the stability of signal detection needs further improvement in subsequent experimental testing steps.

This work reports the potential use of surface-enhanced Raman spectroscopy (SERS) in rapid, label-free assaying of testosterone (TE) and growth hormone (GH) in whole blood. Biomarker SERS spectral bands from the two hormones (TE and GH) in intentionally spiked water for injection and in male Sprague-Dawley (SD) rat’s blood are reported. These concentration-sensitive Raman bands as deduced through Principal Component Analysis (PCA) and Analysis of Variance (ANOVA), were centered around 1490 and 1510 cm⁻¹ for GH, 1614 and 1636 cm⁻¹ for TE; and 684 cm⁻¹ for the hormone mixture (GH+TE) in blood. These bands exhibited significant intensity changes with the concentration of GH and TE hormones in blood. They were tentatively assigned to C-C stretching (684, 786, 856, 1614 and 1636 cm⁻¹), CH₂ bending (1490 cm⁻¹) and CH₂ stretching (1510 cm⁻¹). These bands may be used in SERS assaying of the respective hormones in blood using a customized and calibrated Raman system thus utilizing the strengths of the SERS method that include, being label-free, rapid (<1 min), chemically specific, minimal sample preparation among others. Besides, the method may potentially be used in detecting abuse of TE and GH in sports where they are often abused concurrently.

We used Raman spectroscopy to analyze amorphous polyetherketoneketone (PEKK) and identified the conditions to obtain this material’s exploitable Raman spectrum. Our study assigns the vibrational modes observed from 100 spectra recorded on the amorphous PEKK’s surface, obtained by injection moulding. The peaks recorded on this polymer are specific to its amorphous microstructure. The vibration modes are similar to PEK and PEEK since they belong to the same family of materials, the polyaryletherketones. However, PEKK has a unique molecular structure with a ketone content of 67 % and an ether content of 33 %, resulting in an amplification or appearance of vibration modes associated with the ketone group’s vibrations and a decrease in the modes related to the ether group. This work provides a valuable database for those studying the microstructure of PEKK and its evolution with processing conditions and ageing.

Fungi are responsible for significant crop losses every year. Due to the modernization and high demand for agriculture, chemical control is used to manage diseases caused by these microorganisms. Triadimenol (TN) is a triazole fungicide widely used to combat these pests, so the characterization of its physical and chemical properties is crucial. However, despite its extensive use, the vibrational study of TN has yet to be published in the literature. In this work, TN was studied by DFT-based analysis and FT-IR, Raman, and SERS spectroscopy. The simulated vibrational spectra of TN obtained from these analyses exhibited good concordance with the experimental spectrum, and the vibrational assignments were consistent with analogous molecules documented in previous studies. The interaction between TN and the surface of silver nanoparticles (AgNPs) was inferred by comparing the theoretical SERS spectrum with experimental SERS and solid-state spectra. Similar to other triazole fungicides, TN also interacts with AgNPs through the triazole functional group.

Alzheimer's disease (AD) is an irreversible neurodegenerative brain disorder and the most common cause of dementia with significant social and economic impact. Despite the severity and prevalence of AD, early diagnosis of AD remains quite challenging. One of the important markers of neuropathology in AD patients is the aggregation of Aβ1–42 monomers into oligomers, which then become fibrils and eventually form beta-amyloid plaques. Herein, a highly sensitive surface-enhanced Raman spectroscopy (SERS) method based on graphene oxide/gold nanoparticles (GO/Au NPs) for the detection of Aβ 1–42 is proposed. Specifically, Au NPs were deposited on the GO surface by in situ reduction to form high-density hot spots for SERS. The limits of detection are 0.0232 ng mL^-1 and 0.0192 ng mL^-1 for Aβ1–42 monomer and fibrils. In addition, support vector machine (SVM) and one-dimensional convolutional neural network (1DCNN) algorithm were used to identify samples with different fibrils degrees. SERS is expected to be used for label-free diagnosis and early detection of AD, which has exciting potential for biomedical detection.

The control over various vacancy and substitutional defects by ion implantation provides many interesting properties for the modulation of materials. In this report, we studied the effect of defects and anionic vacancies produced by MeV Ni ion implanted single crystal MgO on different vibrational active modes. The breathing mode of D bands is observed for most of the Raman peaks, and simultaneously, the overlapping of D and G bands is confirmed from Raman spectra. The Fourier Transform Infrared spectra identified the stretching and bending vibrations of Mg, O, and Ni atoms and compared them with pristine. The presence of atmospheric constituents and their role in affecting the vibrational modes are well justified. The phonon band and density of states calculation in the framework of density functional theory confirms the presence of T_1u and T_2u Raman active mode that arises due to vibration from different vacancy and substitutional defect associated in MgO structures, agrees well with experimental results. The tunable anionic vacancies produced in MgO by ion implantation can be beneficial to form the filament in valance charge memory-based resistive random-access memory (RRAM).