Search Results (434)

The year 2024 marks the 30-year anniversary of the quantum cascade laser (QCL), which is becoming the leading laser source in the mid-infrared (mid-IR) range. Since the first demonstration, QCL has undergone tremendous development in terms of the output power, wall plug efficiency, spectral coverage, wavelength tunability, and beam quality. Owing to its unique intersubband transition and fast gain features, QCL possesses strong nonlinearities that makes it an ideal platform for nonlinear photonics like terahertz (THz) difference frequency generation and direct frequency comb generation via four-wave mixing when group velocity dispersion is engineered. The feature of broadband, high-power, and low-phase noise of QCL combs is revolutionizing mid-IR spectroscopy and sensing by offering a new tool measuring multi-channel molecules simultaneously in the μs time scale. While THz QCL difference frequency generation is becoming the only semiconductor light source covering 1–5 THz at room temperature. In this paper, we will introduce the latest research from the Center for Quantum Devices at Northwestern University and briefly discuss the history of QCL, recent progress, and future perspective of QCL research, especially for QCL frequency combs, room temperature THz QCL difference frequency generation, and major challenges facing QCL in the future. Full article

Studying the mechanisms and effects of rejuvenators on SBS-modified bitumen is crucial for repairing degraded SBS and recycling aged SBS-modified bitumen (ASMB), thereby contributing to the sustainable development of bitumen pavements. This research examines the roles of mono-epoxy Alkyl (C12-C14) glycidyl ether (AGE) and di-epoxy 1,6-Hexanediol diglycidyl ether (HDE) under the catalysis of N,N-dimethyl benzyl amine (BDMA) in repairing degraded SBS chains. Aromatic oil (ORSMB)-, AGE–aromatic oil (ARSMB)-, and HDE–aromatic oil (HRSMB)-rejuvenated bitumen are analyzed for their chemical structures, physical properties, and rheological properties. Fluorescence microscopy (FM) and Fourier transform infrared spectroscopy (FTIR) reveal that HDE chemically reconnects degraded SBS chains, enhancing ASMB properties, while AGE improves ASMB properties through physical softening. HDE balances high-temperature properties and improves mid-temperature fatigue resistance through a rigid repair effect and flexible chain structure. AGE enhances mid-temperature fatigue resistance but significantly reduces high-temperature rutting resistance due to a softening effect. The findings demonstrate that HDE restores ASMB ductility chemically, while AGE improves crack resistance through physical softening. These differences in rejuvenation mechanisms provide a theoretical basis for optimizing rejuvenator design and advancing bitumen pavement recycling. Full article

Different sulfates (Ca-, Mg, and Fe- sulfates) have been extensively detected on the Martian surface. As one of the Martian sulfates, the presence of ferrous sulfates will provide valuable clues about the redox environment, hydrological processes, and climatic history of ancient Mars. In this study, three hydrated ferrous sulfates were prepared in the laboratory by heating dehydration reactions. These samples were analyzed using X-ray Diffraction (XRD) to confirm their phase and homogeneity. Subsequently, Raman, mid-infrared (MIR) spectra, visible near-infrared (VNIR) spectra, and laser-induced breakdown spectroscopy (LIBS) were measured and analyzed. The results demonstrate that the spectra of three hydrated ferrous sulfates exhibit distinctive features (e.g., the v₁ and v₃ features of SO42− tetrahedra in their Raman and MIR spectra) that can offer new insights for identifying different ferrous sulfates on Mars and aid in the interpretation of in-situ data collected by instruments such as the Scanning Habitable Environments with Raman & Luminescence for Organics & Chemicals (SHERLOC), SuperCam, and ChemCam, etc. Full article

Vitamin E is an essential nutrient, but its poor water solubility limits food and pharmaceutical applications. The usability of vitamin E can be enhanced via modification methods such as encapsulation, which transforms the physical state of vitamin E from a liquid to a powder. This study examined the efficacy of near-infrared (NIR) and mid-infrared (MIR) spectroscopy in identifying and predicting various vitamin E derivatives in vitamin E-encapsulated powder (VEP). An MIR analysis revealed the fundamental C–H vibrations of vitamin E in the range of 2700–3250 cm⁻¹, whereas an NIR analysis provided information about the corresponding combination, first, and second overtones in the range of 4000–9000 cm⁻¹. The MIR and NIR data were analyzed using a principal component analysis to characterize the VEP. Partial least squares (PLS) regression was applied to predict the content of individual vitamin E derivatives. PLS cross-validation revealed that NIR analysis provides more reliable predictive accuracy and precision for the contents of vitamin E derivatives, achieving a higher coefficient of determination for prediction (Q²) (0.92–0.99) than MIR analysis (0.20–0.85). For test set validation, the NIR predictions exhibited a significant level of accuracy, as indicated by a high ratio of prediction to deviation (RPD) and Q². Furthermore, the PLS models developed using the NIR data had statistically significant predictive performance, with a high RPD (1.54–3.92) and Q² (0.66–0.94). Thus, NIR spectroscopy is a valuable nondestructive technique for analyzing vitamin E samples, while MIR spectroscopy serves as a useful method for confirming its presence. Full article

Milk analysis is critical to determine its intrinsic quality, as well as its nutritional and economic value. Currently, the advancements and utilization of spectroscopy-based techniques combined with machine learning algorithms have made the development of analytical tools and real-time monitoring and prediction systems in the dairy ruminant sector feasible. The objectives of the current review were (i) to describe the most widely applied spectroscopy-based and supervised machine learning methods utilized for the evaluation of milk components, origin, technological properties, adulterants, and drug residues, (ii) to present and compare the performance and adaptability of these methods and their most efficient combinations, providing insights into the strengths, weaknesses, opportunities, and challenges of the most promising ones regarding the capacity to be applied in milk quality monitoring systems both at the point-of-care and beyond, and (iii) to discuss their applicability and future perspectives for the integration of these methods in milk data analysis and decision support systems across the milk value-chain. Full article

Cyclic peptides have higher stability and better properties as therapeutic agents than their linear peptide analogues. Consequently, intramolecular click chemistry is becoming an increasingly popular method for the synthesis of cyclic peptides from their isomeric linear peptides. However, assessing the purity of these cyclic peptides by mass spectrometry is a significant challenge, as the linear and cyclic peptides have identical masses. In this paper, we have evaluated the analytical capabilities of energy-resolved mass spectrometry (ER MS) and mid-infrared microscopy (IR) to address this challenge. On the one hand, mixtures of both peptides were subjected to collision-induced dissociation tandem mass spectrometry (CID MS/MS) experiments in an ion trap mass spectrometer at several excitation energies. Two different calibration models were used: a univariate model (at a single excitation voltage) and a multivariate model (using multiple excitation voltages). The multivariate model demonstrated slightly enhanced analytical performance, which can be attributed to more effective signal averaging when multiple excitation voltages are considered. On the other hand, IR microscopy was used for the quantification of the relative amount of linear peptide. This was achieved through univariate calibration, based on the absorbance of an alkyne band specific to the linear peptide, and through Partial Least Squares (PLS) multivariate calibration. The PLS calibration model demonstrated superior performance in comparison to univariate calibration, indicating that consideration of the full IR spectrum is preferable to focusing on the specific peak of the linear peptide. The advantage of IR microscopy is that it is linear across the entire working interval, from linear peptide molar ratios of 0 (equivalent to pure cyclic peptide) up to 1 (pure linear peptide). In contrast, the ER MS calibration models exhibited linearity only up to 0.3 linear peptide molar ratio. However, ER MS showed better performances in terms of the limit of detection, intermediate precision and the root-mean-square-error of calibration. Therefore, ER MS is the optimal choice for the detection and quantification of the lowest relative amounts of linear peptides. Full article

The detection and quantification of additives in tobacco products are critical for ensuring consumer safety and compliance with regulatory standards. Traditional analytical techniques, like gas chromatography–mass spectrometry (GC–MS), liquid chromatography–mass spectrometry (LC–MS), and others, although effective, suffer from drawbacks, including complex sample preparation, high costs, lengthy analysis times, and the requirement for skilled operators. This study addresses these challenges by evaluating the efficacy of mid-infrared (MIR) spectroscopy and near-IR (NIR) spectroscopy, coupled with multivariate analysis, as potential solutions for the detection and quantification of additives in tobacco products. So, a representative set of tobacco products was selected and spiked with the targeted additives, namely caffeine, menthol, glycerol, and cocoa. Multivariate analysis of MIR and NIR spectra consisted of principal component analysis (PCA), hierarchical clustering analysis (HCA), partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) to classify samples based on targeted additives. Based on the unsupervised techniques (PCA and HCA), a distinction could be made between spiked and non-spiked samples for all four targeted additives based on both MIR and NIR spectral data. During supervised analysis, SIMCA achieved 87–100% classification accuracy for the different additives and for both spectroscopic techniques. PLS-DA models showed classification rates of 80% to 100%, also demonstrating robust performance. Regression studies, using PLS, showed that it is possible to effectively estimate the concentration levels of the targeted molecules. The results also highlight the necessity of optimizing data pretreatment for accurate quantification of the target additives. Overall, NIR spectroscopy combined with SIMCA provided the most accurate and robust classification models for all target molecules, indicating that it is the most effective single technique for this type of analysis. MIR, on the other hand, showed the overall best performance for quantitative estimation. Full article

Photodetectors play a critical role in space lidars designed for scientific investigations from orbit around planetary bodies. The detectors must be highly sensitive due to the long range of measurements and tight constraints on the size, weight, and power of the instrument. The detectors must also be space radiation tolerant over multi-year mission lifetimes with no significant performance degradation. Early space lidars used diode-pumped Nd:YAG lasers with a single beam for range and atmospheric backscattering measurements at 1064 nm or its frequency harmonics. The photodetectors used were single-element photomultiplier tubes and infrared performance-enhanced silicon avalanche photodiodes. Space lidars have advanced to multiple beams for surface topographic mapping and active infrared spectroscopic measurements of atmospheric species and surface composition, which demand increased performance and new capabilities for lidar detectors. Higher sensitivity detectors are required so that multi-beam and multi-wavelength measurements can be performed without increasing the laser and instrument power. Pixelated photodetectors are needed so that a single detector assembly can be used for simultaneous multi-channel measurements. Photon-counting photodetectors are needed for active spectroscopy measurements from short-wave infrared to mid-wave infrared. HgCdTe avalanche photodiode arrays have emerged recently as a promising technology to fill these needs. This paper gives a review of the photodetectors used in past and present lidars and the development and outlook of HgCdTe APD arrays for future space lidars. Full article

Processing sustainability and the concept of zero waste discharge are of great interest for many industries. Every year, fruit and vegetable processing industries generate huge amounts of by-products, which are often intended for animal feed or discarded as waste, posing a problem to both environmental and economic points of view. However, to minimize the waste burden, the valorization of these residues received increased interest. In fact, fruit and vegetable by-products are an excellent source of valuable compounds, such as proteins, dietary fibers, lipids, minerals, vitamins, phenolic acids, flavonoids, anthocyanins, carotenoids, and pigments, which can be recovered and reused, creating new business prospects from a circular economy perspective. Understanding the chemical characteristics of these materials is a key concern for their valorization and the identification of their most appropriate intended use. In this study, the phytochemical and functional properties of fruit and vegetable processing by-products (peel and pomace) were investigated. Samples of different plants (i.e., apple, black and orange carrot, cucumber, kumquat, mango, parsnip, peach, black plum) were analyzed using chemical analytical methods and characterized using Fourier Transform Mid-Infrared spectroscopy (FT-MIR). The results highlighted their high nutritional composition in terms of protein, lipids, fiber, and ash, as well as bioactive and antioxidant profiles. These characteristics make these residues suitable as natural ingredients for the development of high-added-value products in food, cosmetic, and pharmaceutical industries. Full article

Fourier Transform Mid-Infrared Spectroscopy (FT-MIRS) can be used for quantitative detection of milk components. Here, milk samples of 458 Chinese Holstein cows from 11 provinces in China were collected and we established a total of 22 quantitative prediction models in milk fatty acids by FT-MIRS. The coefficient of determination of the validation set ranged from 0.59 (C18:0) to 0.76 (C4:0). The models were adopted to predict the milk fatty acids from 2138 cows and a new high-throughput computing software HiBLUP was employed to construct a multi-trait model to estimate and analyze genetic parameters in dairy cows. Finally, genome-wide association analysis was performed and seven novel SNPs significantly associated with fatty acid content were selected, investigated, and verified with the FarmCPU method, which stands for “Fixed and random model Circulating Probability Unification”. The findings of this study lay a foundation and offer technical support for the study of fatty acid trait breeding and the screening and grouping of characteristic dairy cows in China with rich, high-quality fatty acids. It is hoped that in the future, the method established in this study will be able to screen milk sources rich in high-quality fatty acids. Full article

This study, conducted a spectroscopic analysis of 10 gem-quality blue tourmaline samples from Minas Gerais, Brazil, focused on detailed variations in their infrared, Raman, and UV-VIS spectra. Conventional gemological tests, electron-probe microanalysis, infrared spectroscopy (mid- and near-infrared), Raman spectroscopy, and UV-visible spectroscopy were used to systematically analyze the chemical composition and spectral characteristics of the samples. The infrared spectra revealed vibrations of [YO₆], [TO₄], [BO₃], [OH], and H₂O groups, indicating different bonding profiles, with the [OH] vibrational frequency showing a direct correlation with FeO and MnO content. The Raman spectra primarily reflected the stretching vibrations of metal–oxygen bonds and hydroxyl groups, indicating the complexity of the local environment in the crystal structure. The UV-VIS spectra showed that the broad absorption band around 725 nm was due to intermetallic charge transfer between Fe²⁺ and Fe³⁺. This work provides new insights into the local bonding environment within the crystal structure by providing precise spectral data of natural blue tourmaline, and a more accurate classification and evaluation of blue tourmaline through fine spectral change characteristics related to crystal chemistry has important implications for both academic research and the gemstone industry. Full article

The modern analytical technique of Fourier-transform mid-infrared spectroscopy (FT-MIR) has found its place in routine wine quality control. It allows rapid and nondestructive analysis, with easy sample preparation and without the need for chemical pretreatment or expensive reagents. The objective of this research was to apply these advantages to fruit wines in order to create a tool for the authentication of fruit wines produced from different fruit species (chokeberry, blackberry, and raspberry). The aim of this work was to establish a chemometric model from FT-MIR spectra and to find a “fingerprint” of specific fruit wines, enabling the classification of fruit wines by plant species. Physicochemical analysis of 111 Croatian fruit wine samples (38 liqueur fruit wines and 73 fruit wines) revealed content levels of the following parameters: alcoholic strength (5.0–15.2% vol.), total dry extract (60.4–253.3 g/L), total sugars (1.2–229.9 g/L), pH (3.13–4.98), total acidity (4.2–18.3 g/L) and volatile acidity (0.2–1.5 g/L). For statistical data processing, spectral ranges between 926 and 1450 cm⁻¹ and between 1801 and 2951 cm⁻¹ were used. The first principal component (PC1) explained 70.4% of the observed variation, and the second component (PC2) explained 16.7%, clearly separating chokeberry fruit wines from blackberry and raspberry fruit wines. Soft Independent Modeling Class Analogy (SIMCA) was performed following the development of a PCA model showing that the chokeberry and blackberry wine samples form clearly separated clusters. Key discriminators for classifying chokeberry vs. blackberry wines were identified at 1157, 1304, and 1435 cm⁻¹, demonstrating high discrimination power (DP 26, 17, and 14, respectively). FT-MIR spectroscopy, in combination with chemometric methods, has shown promising potential for the authenticity assessment of fruit wines. Full article

The investigation of the central and external zones of ten industrial and artisanal Maroilles cheeses showed differences in their physicochemical parameters, namely fat, pH, moisture content, ash, and color. This difference significantly impacted the rheological properties of the investigated cheeses, which depended on the protein network englobing lipid and water and its interaction with the other components. Overall, Maroilles cheeses had an elastic-like behavior, with the central zones exhibiting the greatest viscoelastic modules (G′ and G″). The mid-infrared (MIR) spectra highlighted the presence of lipids, proteins, and sugars. A significant difference in α-helix and β-sheet levels in the central zones was noted between artisanal and industrial Maroilles cheeses. It is suggested that the difference between artisanal and industrial Maroilles cheeses observed at the macroscopic level, due to the cheese-making procedure and ripening stage, affects the structure at the molecular level, which can be determined by MIR spectroscopy. This trend was confirmed by the FDA when applied to the MIR spectra, since 96.67% correct classification was noted between artisanal and industrial cheeses. The present study indicates that MIR spectroscopy can be used successfully to study Maroilles cheese samples belonging to different production chains. Full article

Fatty acid is an important factor affecting the nutritional quality of milk. In this study, we collected and assessed 78,086 milk samples from 12,065 Chinese Holstein cows from 11 farms in Northern China from November 2019 to September 2022. The contents of eight fatty acid groups were predicted using FT-MIRS-based models. The contents of TFAs, SFAs, UFAs, MUFAs, PUFAs, and LCFAs in milk reached the highest at 96–125 DIM, and SCFA and MCFA contents reached the highest at 276–305 DIM. With the increase in somatic cell score, the contents of various fatty acid groups in milk gradually decreased, and the nutritional value of milk and flavor of dairy products gradually deteriorated. The contents of high-quality fatty acids in milk, particularly UFAs and MUFAs, were significantly higher in the non-pregnant state than in the pregnant state. However, SCFA and MCFA contents exhibited the opposite pattern. Our findings provided valuable information on the content and distribution range of fatty acid groups in milk from Chinese Holstein cows. Further analysis is warranted to explore the breeding of Chinese Holstein cows providing milk with abundant beneficial fatty acids. Full article

Phosphorus is a key element for identifying past human activity. Recently, phosphorus analyses have been extended to archaeological objects, aiming at distinguishing how depositional contexts contribute to its enrichment. In archaeological pottery, phosphorus might depend on several manufacturing and postdepositional processes (i.e., addition of organic temper, pigments, diagenetic incorporation). We analyzed by XRD, XRF, and mid-infrared (FTIR-ATR) spectroscopy 178 pots from eight NW Spain archaeological sites. These sites encompass different chronologies, contexts, and local geology. The phosphorus content was highly variable (224–27,722 mg kg⁻¹) overall but also between archeological sites (1644 ± 487 to 13,635 ± 6623 mg kg⁻¹) and within archaeological sites (4–36, max/min ratio). No phosphate minerals were identified by XRD nor FTIR-ATR, but correlations between phosphorus content and MIR absorbances showed maxima at 1515 and 980 cm⁻¹, suggesting the presence of two sources: one organic (i.e., phosphorylated aromatic compounds) and another inorganic (i.e., albite and K-feldspar). Phosphorylated aromatics were most likely formed during pottery firing and were preserved due to their high resistance to temperature and oxidation. Meanwhile, albite and K-feldspar are among the P-bearing minerals with higher P concentrations. Our results suggest that P content is related to intentional and non-intentional actions taken in the pottery production process. Full article