Advances in Molecular Structure and Interaction Studies Using Near-Infrared Spectroscopy

Binding and distribution regularity of water molecules in high-moisture textured Antarctic krill (Euphausia superba) meat

High-moisture extrusion technique with the advantage of high efficiency and low energy consumption is a promising strategy for processing Antarctic krill meat. Consequently, this study aimed to prepare high-moisture textured Antarctic krill meat (HMTAKM) with a rich fiber structure at different water contents (53 %, 57 %, and 61 %) and to reveal the binding and distribution regularity of water molecules, which is closely related to the fiber structure of HMTAKM and has been less studied. The hydrogen-bond network results indicated the presence of at least two or more types of water molecules with different hydrogen bonds. Increasing the water content of HMTAKM promoted the formation of hydrogen bonds between the water molecules and protein molecules, leading to the transition of the β-sheet to the α-helix. These findings offer a novel viable processing technique for Antarctic krill and a new understanding of the fiber formation of high-moisture textured proteins.

Soft confinement of water in aliphatic alcohols: MIR/NIR spectroscopic and DFT studies

Here, we present the first examination of the state of water under a soft confinement in eight aliphatic alcohols including cyclopentanol, 1-pentanol, 1-hexanol, 1-heptanol, 1-octanol, 1-decanol, 2-octanol and 3-octanol. Due to relatively large size of the aliphatic part, water has limited solubility in all studied alcohols. Water content in saturated solutions was determined by Karl Fischer titration and correlated with the spectroscopic data. This way, we determined the molar absorptivity of the ν2+ν3 combination mode. The effect of addition of water and temperature variation was monitored by ATR-IR and NIR spectroscopy. Analysis of the experimental results was guided by DFT calculations, which provided the structures, harmonic MIR spectra and binding energies of selected alcohol-water complexes. Our studies demonstrated that the state of water in alcohols is related to its solubility, which depends on structure of solvent molecules. The solubility of water in 1-alcohols decreases on increasing of the chain length, but for long chain alcohols this effect is less evident. More apparent solubility reduction appears in going from the primary to secondary alcohols. The effective shielding of the OH group in the linear alcohols is achieved when on both sides of the OH group are ethyl or longer substituents, while the shielding by methyl groups is less efficient. Water is much better soluble in the cyclic alcohols as compared with the linear ones due to better accessibility of the OH group. The soft confinement of water in aliphatic alcohols allows for flexible structural arrangements and interactions. Even at low water content, we did not observe free molecules of water. At these conditions, the molecules of water are singly or doubly bonded to the OH groups from the alcohol. Increasing solubility of water reduces the number of the free OH groups and leads to formation of water clusters. Obtained results allow concluding that in alcohols with sizable aliphatic part the molecules of water are confined in the vicinity of the OH groups.

Understanding the structures and interactions in gaseous mixtures of water-alcohol by high-resolution infrared spectroscopy

Interactions of water and chemical or bio-compound have a universal concern and have been extensively studied. For spectroscopic analysis, the complexity and the low resolution of the spectra make it difficult to obtain the spectral features showing the interactions. In this work, the structures and interactions in gaseous water and water-alcohol mixtures were studied using high-resolution infrared (HR-IR) spectroscopy. The spectral features of water clusters of different sizes, including dimer, trimer, tetramer and pentamer, were observed from the measured spectra of the samples in different volume concentrations, and the interactions of water and methanol/ethanol in the mixtures were obtained. In the analysis, a method based on principal component analysis was used to separate the overlapping spectra. In water-alcohol mixtures, when water is less, water molecules tend to interact with the OH groups on the exterior of the alcohol aggregate, and with the increase of water, a water cage forms around the aggregates. Furthermore, the ratio of the molecule number of methanol in the aggregate to that of water in the cage is around 1:2.3, and the ratio for ethanol is about 1:3.2.

Nondestructive discrimination of Potentilla anserina L. from different production areas based on near-infrared spectroscopy

INTRODUCTION

The traditional Chinese medicine (TCM) Potentilla anserina L. can use both as food and medicine. At present, the market mainly depends on experience to identify the species and determine the production areas of P. anserina. To ensure the quality of P. anserina, it is essential to improve the level of quality control.

OBJECTIVE

We aimed to establish a rapid and nondestructive discrimination model to identify P. anserina from different production areas by near-infrared spectroscopy.

METHODS

The spectra of complete P. anserina medicinal materials and their powder of the same variety from four production areas were collected, and principal component analysis discriminant analysis and partial least squares discriminant analysis (PLS-DA) were conducted based on different pretreatment methods and band selection methods. Then, the spectra of complete medicinal materials were converted into the spectra of medicinal powder for nondestructive identification.

RESULTS

The correct recognition rate (CRR) of the PLS-DA discriminant model was the best after spectral preprocessing using autoscaling and competitive adaptive reweighted sampling for band selection. The CRRs of the calibration set and validation set were 100%, the CRRs of the external test set were 95%, 90%, 82%, and 88%, respectively, and the CRRs of the transfer external test set were 84%, 80%, 82%, and 86%, respectively.

CONCLUSION

We realized the nondestructive and effective identification of P. anserina from different origins and laid a foundation for the industrialization and upgrading of TCM.

Identification of near-infrared characteristic bands of small bowel necrosis based on cellwise detection algorithm

The near-infrared spectroscopy is often used to distinguish small bowel necrosis due to necrotizing enterocolitis (NEC). The characteristic bands of small bowel necrosis, as an important basis for evaluating the confidence of the differentiation results, are challenging to identify quickly. In this study, we proposed to identify characteristic bands of lesion samples based on hyperspectral imaging (HSI) and cellwise outlier detection. Rabbits were used as an animal model to simulate the clinical symptoms of NEC. The rabbits were detected at intervals of 10, 30, 60, and 90 min. The characteristic bands were identified within the same rabbit, between different rabbits and at different times. The result showed the bands near 763 nm, corresponding to the absorption peak of deoxyhemoglobin, were the characteristic bands separating samples with NEC. The identification result was plausible because hypoxia was the main cause of NEC. The method was easy to perform.

Accelerated Bayesian Inference for Molecular Simulations using Local Gaussian Process Surrogate Models

While Bayesian inference is the gold standard for uncertainty quantification and propagation, its use within physical chemistry encounters formidable computational barriers. These bottlenecks are magnified for modeling data with many independent variables, such as X-ray/neutron scattering patterns and electromagnetic spectra. To address this challenge, we employ local Gaussian process (LGP) surrogate models to accelerate Bayesian optimization over these complex thermophysical properties. The time-complexity of the LGPs scales linearly in the number of independent variables, in stark contrast to the computationally expensive cubic scaling of conventional Gaussian processes. To illustrate the method, we trained a LGP surrogate model on the radial distribution function of liquid neon and observed a 1,760,000-fold speed-up compared to molecular dynamics simulation, beating a conventional GP by three orders-of-magnitude. We conclude that LGPs are robust and efficient surrogate models poised to expand the application of Bayesian inference in molecular simulations to a broad spectrum of experimental data.

Rapid characterization of sulfur and phosphorus in organic waste by near infrared spectroscopy

Near-infrared spectroscopy (NIRS) has recently emerged as a valuable tool for monitoring organic waste utilized in anaerobic digestion processes. Over the past decade, NIRS has significantly improved the characterization of organic waste by enabling the prediction of several crucial parameters such as biochemical methane potential, carbohydrate, lipid and nitrogen contents, Chemical Oxygen Demand, and kinetic parameters. This study investigates the application of NIRS for predicting the levels of Sulfur (S) and Phosphorus (P) within organic waste materials. The results for sulfur prediction exhibited a high level of accuracy, yielding an error of 1.21 g/Kg[TS] in an independently validated dataset, coupled with an R-squared value of 0.84. Conversely, the prediction of phosphorus proved to be slightly less successful, showing an error of 1.49 g/Kg[TS] with an R-squared value of 0.70. Furthermore, the disparities in performance seem to stem from the inherent correlation between the spectral data and the sulfur or phosphorus contents. Significantly, a variable selection technique known as CovSel was employed, shedding light on the differing approaches used for sulfur and phosphorus predictions. In the case of sulfur, the prediction was achieved through a direct correlation with wavelengths associated with sulfur-related functional groups (such as R - S(=O)2 - OH, -SH, and R-S-S-R) present in the NIR spectra. In contrast, phosphorus prediction relied on an indirect correlation with absorption bands related to organic matter (including CH, CH2, CH3, -CHO, R-OH, C = O, -CO2H, and CONH).

Ultrastrong Electron-Phonon Coupling in Uranium-Organic Frameworks Leading to Inverse Luminescence Temperature Dependence

Electron-phonon interactions, crucial in condensed matter, are rarely seen in Metal-Organic Frameworks (MOFs). Detecting these interactions typically involves analyzing luminescence in lanthanide- or actinide-based compounds. Prior studies on Ln- and Ac-based MOFs at high temperatures revealed additional peaks, but these were too faint for thorough analysis. In our research, we fabricated a high-quality, crystalline uranium-based MOF (KIT-U-1) thin film using a layer-by-layer method. Under UV light, this film showed two distinct "hot bands," indicating a strong electron-phonon interaction. At 77 K, these bands were absent, but at 300 K, a new emission band appeared with half the intensity of the main luminescence. Surprisingly, a second hot band emerged above 320 K, deviating from previous findings in rare-earth compounds. We conducted a detailed ab-initio analysis employing time-dependent density functional theory to understand this unusual behaviour and to identify the lattice vibration responsible for the strong electron-phonon coupling. The KIT-U-1 film's hot-band emission was then utilized to create a highly sensitive, single-compound optical thermometer. This underscores the potential of high-quality MOF thin films in exploiting the unique luminescence of lanthanides and actinides for advanced applications.

Detection and analysis of hyaluronic acid raw materials from different sources by NIR and aquaphotomics

Hyaluronic acid (HA), a polysaccharide, is widely used for its essential physiological functions. Although the structures of low molecular weight HA produced by both acid and enzyme degradation methods are extremely similar, there are still differences due to the different degradation principles. There is currently no clear way to distinguish between HA prepared by acidolysis and enzymatic hydrolysis. Based on near-infrared (NIR) spectroscopy and aquaphotomics technology, a method for distinguishing HA raw materials and their mixtures from different sources was proposed, and HA with different mixed ratios was accurately quantified. First, NIR spectra of the HA samples were collected. The spectra were then preprocessed to improve the spectral resolution. Spectral information was extracted based on wavelet transform and principal component analysis, resulting in a final selection of 12 characteristic wavelengths containing classification information. The discriminative and quantitative models were then constructed using the 12 wavelengths. The discriminative model achieved a 100% identification rate for HA from different sources. The correlation coefficient of calibration (Rc), validation (Rp), external test (Rt), root mean square error of cross validation (RMSECV), calibration (RMSEC), validation (RMSEP), and external test (RMSET) of the mixed proportion quantitative model were 0.9876, 0.9876, 0.9898, 0.0546, 0.0433, 0.0440, and 0.0347, respectively. In this study, the problem of structural similarity and non-identifiability of HA produced by acidolysis and enzymatic hydrolysis was addressed, and quality monitoring of HA feedstock in HA circulating links was achieved. This is the first time to achieve accurate quantification of solid mixtures using the aquaphotomics method.

A low-cost discrete Vis-NIR optical sensing method for the determination of pear internal blackheart

In this study, a moldy crown pear core detection system based on a micro-optical sensor was developed. The micro-optical sensor has seven specific wavelengths, 425, 455, 515, 615, 660, 700, and 850 nm, and a cost-effective advantage. For the discrete spectrum, 7 kinds of preprocessing methods were compared. Traditional preprocessing methods, such as the standard normal transform (SNV) and multiple scattering correction (MSC) methods, cannot improve the efficiency of the spectrum. It was verified that the Savitzky - Golay (SG) convolution smoothing preprocessing method could be applied to preprocess discrete spectral data. The correlation of the spectrum after SG preprocessing in the partial least squares regression (PLSR) prediction model was 0.86, and the root mean square error (RMSE) was 0.19. Furthermore, the difference between the nonlinear modeling method without preprocessing and the PLS prediction model after preprocessing was compared. The results showed that the accuracy of the nonlinear modeling method for the discrete spectrum was much higher than that of the PLS linear modeling. The average model accuracy was above 0.9, and the k nearest neighbor (KNN) algorithm had the best effect, reaching an accuracy of 0.96. Finally, a prediction model accuracy of 0.98 was obtained by combining SG + KNN. In summary, the micro-optical sensor system had the advantages of low-cost performance and high precision, which are convenient for popularization and application in practice.

A review on current diagnostic tools and potential optical absorption spectroscopy for HFMD detection

Hand, Foot, and Mouth Disease (HFMD) is an outbreak infectious disease that can easily spread among children under the age of five. The most common causative agents of HFMD are enterovirus 71 (EV71) and coxsackievirus A16 (CVA16), but infection caused by EV71 is more associated with fatalities due to severe neurological disorders. The present diagnosis methods rely on physical examinations by the doctors and further confirmation by laboratories detection methods such as viral culture and polymerase chain reaction. Clinical signs of HFMD infection and other childhood diseases such as chicken pox, and allergies are similar, yet the genetics and pathogenicity of the viruses are substantially different. Thus, there is an urgent need for an early screening of HFMD using an inexpensive and user-friendly device that can directly detect the causative agents of the disease. This paper reviews current HFMD diagnostic methods based on various target types, such as nucleic acid, protein, and whole virus. This was followed by a thorough discussion on the emerging sensing technologies for HFMD detection, including surface plasmon resonance, electrochemical sensor, and surface enhanced Raman spectroscopy. Lastly, optical absorption spectroscopic method was critically discussed and proposed as a promising technology for HFMD screening and detection.

State of water in various environments: Aliphatic ketones. MIR/NIR spectroscopic, dielectric and theoretical studies

This work provides new insight into the state of water in a series of aliphatic ketones. For our studies, we selected nine aliphatic ketones of different size and structure to examine the effect of various structural motifs on behavior of water in the mixtures. Our results reveal that conformational flexibility of aliphatic chains in the linear ketones allows for effective shielding of the carbonyl group, and this flexibility is the main reason for poor solubility of water. Hence, in the linear ketones molecules of water are involved mostly in ketone-water interactions, while the water-water interactions are rare. Higher solubility of water in the cyclic ketones allows for creation of clusters of water, where the molecules are in water-like environment. The temperature rise in wet cyclic ketones increases population of ketone-water interactions at the expense of the water-water ones, while in the linear ketones and 2,6-dimethylcyclohexanone at an elevated temperature there is an increase in the population of singly bonded water at the expense of the doubly bonded one. DFT calculations reveal that the substitution of cyclohexanone by a single methyl group does not affect the strength of the ketone-water interactions, while it has a significant impact on the solubility of water in the ketone. The most important conclusion from this study is that the accessibility of the carbonyl group is the most important factor determining the intermolecular interactions and solubility of water in aliphatic ketones.

Variations in the Protein Hydration and Hydrogen-Bond Network of Water Molecules Induced by the Changes in the Secondary Structures of Proteins Studied through Near-Infrared Spectroscopy

This study investigated how the secondary structural changes of proteins in aqueous solutions affect their hydration and the hydrogen-bond network of water molecules using near-infrared (NIR) spectroscopy. The aqueous solutions of three types of proteins, i.e., ovalbumin, β-lactoglobulin, and bovine serum albumin, were denatured by heating, and changes in the NIR bands of water reflecting the states of hydrogen bonds induced via protein secondary structural changes were investigated. On heating, the intermolecular hydrogen bonds between water molecules as well as between water and protein molecules were broken, and protein molecules were no longer strongly bound by the surrounding water molecules. Consequently, the denaturation was observed to proceed depending on the thermodynamic properties of the proteins. When the aqueous solutions of proteins were cooled after denaturation, the hydrogen-bond network was reformed. However, the state of protein hydration was changed owing to the secondary structural changes of proteins, and the variation patterns were different depending on the protein species. These changes in protein hydration may be derived from the differences in the surface charges of proteins. The elucidation of the mechanism of protein hydration and the formation of the hydrogen-bond network of water molecules will afford a comprehensive understanding of the protein functioning and dysfunctioning derived from the structural changes in proteins.

A new apparatus and the relevant method to retrieve IR spectra of solutes from the corresponding aqueous solutions

An apparatus and relevant approach to obtaining IR spectra of solutes from the corresponding aqueous solution were developed. In the experiment, aqueous solutions were converted into aerosols using an ultrasonic or a pneumatic device. Subsequently, water in the nebulized solution is completely gasified under a high-speed flow and low vacuum environment. Via this process, the aqueous solution changes into a mixture of a solute or solutes and gaseous water, whose single-beam IR spectra are collected. Then, the newly developed RMF (retrieving moisture-free IR spectrum) method and the relevant approach described in our recent papers have been adopted to treat the resultant single-beam sample spectrum. As a result, the spectral contribution of the vibrational-rotational peaks of gaseous water can be removed or significantly attenuated, and IR spectra of solutes can be obtained. The approach shows an obvious advantage in retrieving the IR spectrum of volatile solutes from its aqueous solution. This capability is showcased by obtaining IR spectra of isopropanol and ethyl acetate successfully. IR spectra of these compounds can be retrieved even if the concentration of the solute is below 10 wt%. Moreover, atomization via ultrasonic/pneumatic methods offers a mild way to gasify solutes whose boiling points are remarkably higher than that of water. This advantage is manifested by acquiring IR spectra of 1-butanol and 1,2-propanediol in the gaseous phase under ambient conditions.

Structures of water on the surface of anatase TiO2 studied by diffuse reflectance near-infrared spectroscopy

Investigating the structures of water on metal oxides is helpful for understanding the mechanism of the adsorptions in the presence of water. In this work, the structures of adsorbed water molecules on anatase TiO₂ (101) were studied by diffuse reflectance near-infrared spectroscopy (DR-NIRS). With resolution enhanced spectrum by continuous wavelet transform (CWT), the spectral features of adsorbed water at different sites were found. In the spectrum of dried TiO₂ powder, there is only the spectral feature of the water adsorbed at 5-coordinated titanium atoms (Ti_5c). With the increase of the adsorbed water, the spectral feature of the water at 2-coordinated oxygen atoms (O_2c) emerges first, and then that of the water interacting with the adsorbed water can be observed. When adenosine triphosphate (ATP) was adsorbed on TiO₂, the intensity of the peaks related to the adsorbed water decreases, indicating that the adsorbed water is replaced by ATP due to the strong affinity to Ti_5c. Therefore, there is a clear correlation between the peak intensity of the adsorbed water and the adsorbed quantity of ATP. Water can be a NIR spectroscopic probe to detect the quantity of the adsorbed ATP. A partial least squares (PLS) model was established to predict the content of adsorbed ATP by the spectral peaks of water. The recoveries of validation samples are in the range of 92.00-114.96% with the relative standard deviations (RSDs) in a range of 2.13-5.82%.

Real-time and accurate calibration detection of gout stones based on terahertz and Raman spectroscopy

Gout is a metabolic disease that can result in the formation of gout stones. It is essential to promptly identify and confirm the type of gout stone to alleviate pain and inflammation in patients and prevent complications associated with gout stones. Traditional detection methods, such as X-ray, ultrasound, CT scanning, and blood uric acid measurement, have limitations in early diagnosis. Therefore, this article aims to explore the use of micro Raman spectroscopy, Fourier transform infrared spectroscopy, and Terahertz time-domain spectroscopy systems to detect gout stone samples. Through comparative analysis, Terahertz technology and Raman spectroscopy have been found to provide chemical composition and molecular structure information of different wavebands of samples. By combining these two technologies, faster and more comprehensive analysis and characterization of samples can be achieved. In the future, handheld portable integrated testing instruments will be developed to improve the efficiency and accuracy of testing. Furthermore, this article proposes establishing a spectral database of gout stones and urinary stones by combining Raman spectroscopy and Terahertz spectroscopy. This database would provide accurate and comprehensive technical support for the rapid diagnosis of gout in clinical practice.

A new approach to recognizing the correct pattern of cross-peaks from a noisy 2D asynchronous spectrum by detecting intrinsic symmetry via the Kolmogorov-Smirnov test

The characteristic cluster pattern of cross-peaks in a 2D asynchronous spectrum provides an effective way to reveal the specific physicochemical nature of subtle spectral changes caused by intermolecular interactions. However, the inevitable presence of noise in the 1D spectra used to construct a 2D asynchronous spectrum is significantly amplified, which poses a serious challenge in identifying the correct cluster pattern of the cross-peaks. While mirror symmetry occurs in some types of cross-peaks, it does not occur in other types. The Kolmogorov-Smirnov test provides a statistical means to check whether the mirror symmetry exists or not between a pair of cross-peaks covered by heavy noise. Thus, different types of cross-peak clusters can be distinguished by excavating intrinsic spectral features from the noisy 2D asynchronous spectrum. The effectiveness of this approach in investigating the nature of intermolecular interactions was showcased in both a simulated model system and a real artemisinin/N-methyl pyrrolidone system.

Fast-Training Deep Learning Algorithm for Multiplex Quantification of Mammalian Bioproduction Metabolites via Contactless Short-Wave Infrared Hyperspectral Sensing

Within the biopharmaceutical sector, there exists the need for a contactless multiplex sensor, which can accurately detect metabolite levels in real time for precise feedback control of a bioreactor environment. Reported spectral sensors in the literature only work when fully submerged in the bioreactor and are subject to probe fouling due to a cell debris buildup. The use of a short-wave infrared (SWIR) hyperspectral (HS) cam era allows for efficient, fully contactless collection of large spectral datasets for metabolite quantification. Here, we report the development of an interpretable deep learning system, a convolution metabolite regression (CMR) approach that detects glucose and lactate concentrations using label-free contactless HS images of cell-free spent media samples from Chinese hamster ovary (CHO) cell growth flasks. Using a dataset of <500 HS images, these CMR algorithms achieved a competitive test root-mean-square error (RMSE) performance of glucose quantification within 27 mg/dL and lactate quantification within 20 mg/dL. Conventional Raman spectroscopy probes report a validation performance of 26 and 18 mg/dL for glucose and lactate, respectively. The CMR system trains within 10 epochs and uses a convolution encoder with a sparse bottleneck regression layer to pick the best-performing filters learned by CMR. Each of these filters is combined with existing interpretable models to produce a metabolite sensing system that automatically removes spurious predictions. Collectively, this work will advance the safe and efficient adoption of contactless deep learning sensing systems for fine control of a variety of bioreactor environments.

Application of Spectroscopy Techniques for Monitoring (Bio)Catalytic Processes in Continuously Operated Microreactor Systems

In the last twenty years, the application of microreactors in chemical and biochemical industrial processes has increased significantly. The use of microreactor systems ensures efficient process intensification due to the excellent heat and mass transfer within the microchannels. Monitoring the concentrations in the microchannels is critical for a better understanding of the physical and chemical processes occurring in micromixers and microreactors. Therefore, there is a growing interest in performing in-line and on-line analyses of chemical and/or biochemical processes. This creates tremendous opportunities for the incorporation of spectroscopic detection techniques into production and processing lines in various industries. In this work, an overview of current applications of ultraviolet–visible, infrared, Raman spectroscopy, NMR, MALDI-TOF-MS, and ESI-MS for monitoring (bio)catalytic processes in continuously operated microreactor systems is presented. The manuscript includes a description of the advantages and disadvantages of the analytical methods listed, with particular emphasis on the chemometric methods used for spectroscopic data analysis.

Ultra-high resolution near-infrared spectrum by wavelet packet transform revealing the hydrogen bond interactions

Resolution is always an obstacle to analyzing the fine structure of a spectrum. The problem is particularly serious in the analysis of the near-infrared (NIR) spectra of aqueous solutions, because the spectrum is generally composed of overlapping broad peaks making the understanding of the structures and the interactions notoriously difficult. In this work, wavelet packet transform (WPT) was adopted to enhance the resolution of the NIR spectra of aqueous mixtures. Due to the microscopic ability of WPT in both position and frequency, the fine details of a spectrum can be observed in the spectral components of different frequencies obtained by WPT decomposition. Ultra-high resolution spectrum can be obtained from the high-frequency component representing the spectral features. Spectral features of different hydrogen-bonded OH, as well as the OH in HOH and HOD, were identified from the high-resolution NIR spectra of water and heavy water mixtures and validated by the variation of the spectral intensity with the mole ratio of H₂O and D₂O. The high-resolution spectrum was further applied in analyzing the interaction of amine and water. The spectral features of the hydrogen bonding between CH/NH in tert-butylamine (TBA) and OH in water were observed. The structures of CH bonded to one water molecule, and the structures of NH connecting with one and two water molecules were identified.

Rapid detection of hepatitis B virus DNA level based on interval-point data fusion of infrared spectra

Hepatitis B is an infectious disease cause by the hepatitis B virus (HBV). In recent years, HBV-DNA level clinically gets more attention for its detailed information than other serological markers. Unfortunately, common clinical method for HBV-DNA level detection is limited for its hours consuming. This study combined infrared spectroscopy with machine learning to investigate the feasibility of near-infrared (NIR) and mid-infrared (MIR) spectra for rapid detection of HBV-DNA level. Based on partial least squares-discriminant analysis (PLS-DA) modeling method, the optimal NIR and MIR models and traditional data fusion models were constructed, respectively. Considering inequal weight between interval and point data in machine learning, interval-point data fusion method was used to compare with other traditional date fusion methods. The results of the study illustrate that interval-point data fusion of NIR and MIR spectra combined with PLS-DA modeling can provide a rapid method for HBV-DNA level detection.

Comprehensive modified approaches to reducing the interference of moisture from an FTIR spectrum and the corresponding second derivative spectrum

We proposed a modified and improved approach to removing the interference of moisture from an IR spectrum and the corresponding second derivative spectrum. The temperature fluctuation in the air of the optical path and baseline-drift lead to the small but persistent presence of the interference of moisture. The problem has been successfully addressed by adopting a double-matching strategy. Additionally, two-dimensional correlationspectra (2D-COS) are generated using the second derivative or third derivative spectrum of the negative base 10 logarithms of the single-beam spectra, thereby removing the linear slope or quadratic portion of baseline-drift. Using the newly adopted approach, the residual interferences of moisture are attenuated. We applied the new approach to the IR spectra and the second derivative spectra of neat hexadecanol and biaxially oriented polypropylene (BOPP) film, and some promising preliminary results are obtained. In hexadecanol, two highly overlapping peaks at 1464 and 1463 cm^-1 are revealed. In BOPP, the envelope at 1458 cm^-1 is found to be composed of a number of sub-peaks.

Site-Selective Occupancy Control of Cr Ions toward Ultrabroad-Band Infrared Luminescence with a Spectral Width up to 419 nm

Infrared-emitting phosphor-converted light-emitting diodes (LEDs) are desirable light sources for a very wide range of applications such as spectroscopy analysis, nondestructive monitoring, covert information identification, and night-vision surveillance. The most important aspect of infrared emitters for spectroscopy is to cover the widest possible wavelength range of emitted light. However, developing ultrabroad-band infrared emitters based on converter technology is still a challenging task due to the lack of suitable phosphor materials that emit in a wide wavelength range upon excitation from blue-emitting chips. Herein, this work demonstrates Cr³⁺-activated Mg₂SiO₄ infrared phosphors with a super wide infrared spectral range of 600 to 1400 nm and high internal quantum yield up to 80.4% upon 460 nm excitation. Site-selective occupancy of Cr³⁺ emitters in two different Mg sites in the Mg₂SiO₄ lattice results in two distinct broad emission bands peaking at 760 and 970 nm, both of which contribute to the ultrabroad-band infrared luminescence with a full width at half maximum (FWHM) of 419 nm. This is by far the broadest infrared emission to the best of our knowledge. On this basis, an ultrabroad-band infrared LED prototype has been fabricated by the combination of the Mg₂SiO₄:Cr³⁺ phosphor with a blue LED chip, which shows great potential for imaging and sensing applications. This work demonstrates that site-selective occupancy control of Cr ions is an effective strategy for developing ultrabroad-band Cr³⁺-doped phosphors.

Vibrational dynamics of ethosuximide polymorphs. Infrared absorption and inelastic neutron scattering spectroscopy and model calculations

Commercially available and administered to the patients ethosuximide is a racemic mixture of two enantiomers, each of them exist in different conformations. The presence of the species mentioned are proven by the title experimental methods aided by DFT model calculations. Results of the latter are matched against spectroscopic data by the clustering window analysis. One type of hydrogen bonds exist in the solid forms of ethosuximide NH⋯O, leading to the polymorphic variety of the substance studied.

In silico NIR spectroscopy - A review. Molecular fingerprint, interpretation of calibration models, understanding of matrix effects and instrumental difference

Quantum mechanical calculations are routinely used as a major support in mid-infrared (MIR) and Raman spectroscopy. In contrast, practical limitations for long time formed a barrier to developing a similar synergy between near-infrared (NIR) spectroscopy and computational chemistry. Recent advances in theoretical methods suitable for calculation of NIR spectra opened the pathway to modeling NIR spectra of various molecules. Accurate theoretical reproduction of NIR spectra of molecules reaching the size of long-chain fatty acids was accomplished so far. In silico NIR spectroscopy, where the spectra are calculated ab initio, provides substantial improvement in our understanding of the overtones and combination bands that overlap in staggering numbers and create complex lineshape typical for NIR spectra. This improves the comprehension of the spectral information enabling access to rich and detail molecular footprint, essential for fundamental research and useful in routine analysis by NIR spectroscopy and chemometrics. This review article summarizes the most recent accomplishments in the emerging field with examples of simulated NIR spectra of molecules reaching long-chain fatty acids and polymers. In addition to detailed NIR band assignments and new physical insights, simulated spectra enable innovative support in applications. Understanding of the difference in the performance observed between miniaturized NIR spectrometers and chemical interpretation of the chemometric models are noteworthy here. These new elements integrated into NIR spectroscopy framework enable a knowledge-based design of the analysis with comprehension of the processed chemical information.

Harnessing Polymer-Matrix-Mediated Manipulation of Intermolecular Charge-Transfer for Near-Infrared Security Applications

Precise recognition of near-infrared (NIR) signals holds great prospects in optical communication, remote sensing, information security, and anti-counterfeiting. For these applications, filters with good NIR transparency are typically essential components. Currently, such NIR transparent filters are dominated by inorganic materials such as chalcogenide glasses. There are, so far, only a handful of organic molecules with suitable optical properties due to the rarity of organic materials with good NIR transparency and relatively flat absorption over the UV-visible region. Here, it is found that the library of NIR-transparent organic materials can be expanded by forming a charge-transfer complex (CTC) between a donor (D) and an acceptor (A) molecule that are commercially available. Via regulating the DA interaction, the CTC filter shows tunable absorption from the visible to NIR region with a relatively high penetration of NIR radiation (≈80%). The CTC filter can successfully highlight NIR information hidden in a complex environment and allow reading of NIR security images for advanced anti-counterfeiting. Moreover, the CTC filter can be used for viewing protected NIR information with good resolution, and thus provide a convenient tool for different security applications using NIR-encoded information.

A Study of C=O…HO and OH…OH (Dimer, Trimer, and Oligomer) Hydrogen Bonding in a Poly(4-vinylphenol) 30%/Poly(methyl methacrylate) 70% Blend and its Thermal Behavior Using Near-Infrared Spectroscopy and Infrared Spectroscopy

Inter- and intramolecular hydrogen bonding and their temperature-dependent changes in a poly(4-vinylphenol)/poly(methyl methacrylate)(PVPh 30%/PMMA 70%) blend were investigated using near-infrared (NIR) and infrared (IR) spectroscopy. Band assignments of the fundamentals and first overtones of the OH stretching mode of a free OH group and OH groups in C=O···HO and OH···OH (dimer, trimer, and oligomer) hydrogen bonding of PVPh 30%/PMMA 70% were carried out by comparison between its NIR and IR spectra and comparison with NIR and IR spectra of phenol. The comparison of the NIR spectra of the PVPh 30%/PMMA 70% blend (hereafter, we denote it as PVPh30%) with the corresponding IR spectra reveals that to observe bands arising from the free OH and OH···OH dimer, which is a weaker hydrogen bonding, NIR is better while to investigate bands originating from OH groups in the OH···O=C and OH···OH (oligomer) hydrogen bonds, which are stronger hydrogen bonding, IR is better. Thus, a combination of IR and NIR spectroscopy has provided convincing results for the hydrogen bonding of PVPh30%. The relative intensity of the two bands at 7058 and 6921 cm^-1 (I₇₀₅₈/I₆₉₂₁) due to the first overtones of the OH stretching modes of the free OH group and the OH group in the dimer, respectively, increases significantly above 90 °C, which is close to Tg of PVPh. In concomitance with the intensity increase in the relative intensity of the free OH band, the intensity of a band at 1706 cm^-1 due to the C=O stretching mode of the C=O···HO hydrogen bond of PVPh30% decreases above 90°C. These results suggest that above the Tg of PVPh the C=O···HO hydrogen bond is broken gradually and that the free OH increases. Of note is that below Tg the intensities of NIR bands due to the OH first overtones of free OH group and OH groups in the OH···OH dimer gain intensity in parallel with temperature increase, and above Tg the intensity of the band derived from the OH···OH group increases linearly much slower than that of the band due to the free OH. Moreover, a band due to an OH···OH oligomer decreases linearly. Hence, it is very likely that the OH···OH oligomers dissociate into free OH groups. Anharmonicity of O-H bonds, which is sensitive to a hydrogen bond, was estimated for the free OH and OH bonds in the C=O···HO and OH···OH (dimer, trimer, and oligomer) hydrogen bonding by comparison between the NIR and IR spectra in the OH stretching band regions.

Analyzing the Water Confined in Hydrogel Using Near-Infrared Spectroscopy

Analysis of the confined water in hydrogels is essential for understanding the chemical and physical properties. Methods to quantify the content and study the structure of water in hydrogel using near-infrared (NIR) spectroscopy were proposed. The NIR spectra of poly-N,N-dimethylacrylamide (PDMAA) hydrogel with different water contents were measured at different temperatures. A partial least squares (PLS) model was established using the spectra of the samples with water content (w_h) from 0.9 to 387.6%. Continuous wavelet transform (CWT) was adopted to calculate the resolution enhanced spectra from which the spectral features of water species with free OH (S₀) and with one or two hydrogen bonds (S₁ and S₂) was obtained. The variation of these water species with water content suggests the existence of the water molecules bonding to NH groups by one hydrogen bond (S_1NH) and hydrating the CH groups of the polymer network and bulk-like water. Moreover, the variation of water structures with temperature shows that the release of bulk-like water occurs in the phase transition of the hydrogel, but the S_1NH and the hydration water stay unchanged. The former explains the sudden volume shrinkage for the phase transition and the latter may be the reason for the shape memory effect in the repeated swelling and deswelling of hydrogels.

Selection of the Effective Characteristic Spectra Based on the Chemical Structure and Its Application in Rapid Analysis of Ethanol Content in Gasoline

Near-infrared (NIR) spectroscopy analysis is one of the most rapid detection methods for determining ethanol content in gasoline. Wavelength selection is a key step in the multivariate calibration analysis of NIR spectroscopy. To improve detection accuracy of ethanol content in gasoline and provide a simpler interpretation, we established NIR spectroscopy, a rapid analysis method based on the effective characteristic spectra. Five effective characteristic spectral bands were used according to the molecular structure of ethanol, followed by the development of four modeling schemes. The four modeling schemes spectra, NIR full spectra, and variable importance projection (VIP) spectra were used for modeling and analysis. The model was established based on the effective characteristic spectra without the interference spectra of aromatic hydrocarbons, achieving the best model performance. In addition, the model was further evaluated by internal cross-validation and external validation. The model's evaluation parameters were as follows: the root mean square error of cross-validation (RMSECV) was 0.6193, the correlation coefficient of internal cross-validation (R CV 2) was 0.9995, the root mean square error of prediction (RMSEP) was 0.5572, and the correlation coefficient of external prediction validation (R P 2) was 0.9995. The effective characteristic spectra model had smaller RMSEP and RMSECV values, and larger R CV 2 and R P 2 values compared to the full spectra and VIP spectra models. In conclusion, the effective characteristic spectra model had the highest accuracy and could provide rapid analysis of the ethanol content in gasoline.

Association and solubility of chlorophenols in CCl4: MIR/NIR spectroscopic and DFT study

This work provides new information on the effect of position and number of substituents on association and solubility of chlorophenols in CCl₄. Using MIR and NIR spectroscopy we examined solutions of 12 chlorophenols at several concentrations. In addition, we calculated (DFT) theoretical spectra and structures of monomers and associates of chlorophenols from dimer to tetramer. The number of substituents at positions 2 and 6 allows to divide studied chlorophenols into three Groups: I (3; 4; 3,4; 3,5), II (2; 2,3; 2,4; 2,5; 2,4,5), and III (2,6; 2,4,6; 2,3,4,5,6). An equilibrium between intermolecular OH⋅⋅⋅OH and intramolecular OH⋅⋅⋅Cl hydrogen bonding depends on position and number of substituents. The extent of association decreases in going from Group I to Group III due to growing steric hindrance near the OH group and the resonance effect from Cl. In chlorophenols of Group I, Cl at positions 3 or 5 weakens the OH⋅⋅⋅OH intermolecular hydrogen bonding, while for Group II it strengthens the OH⋅⋅⋅⋅Cl intramolecular bonding. In contrast, Cl at position 4 has minor effect on association. In the case of Group I, increasing concentration shifts the equilibrium towards solute-solute interactions, whereas for Groups II and III dominate the species with intramolecular OH⋅⋅⋅Cl bonding. The theoretical calculations predict that for monosubstituted chlorophenols of Group I the most stable are non-planar cyclic tetramers, while for disubstituted ones, the non-planar cyclic tetramers and linear trimers have similar binding energies. Chlorophenols of Group II prefer the cyclic non-planar trimers, whereas those of Group III form the planar dimers with an antiparallel orientation of the OH groups. Our study reveals that chlorophenols creating the cyclic associates are better soluble in CCl₄ as compared with those forming the linear ones. Hence, one can conclude that in an inert or weakly interacting solvents the solubility is closely related to the structure of the solute associates.

Random swapping, an effective and efficient way to boost the intensities of cross peaks in a 2D asynchronous spectrum

Analysis of mixture via chromatographic-spectroscopic and analogous experiments is a common task in analytical chemistry. A 2D/nD asynchronous spectrum is effective in retrieving spectra of pure substances even if different components cannot be separated. However, noise in the 2D/nD asynchronous spectrum becomes a bottleneck in the analysis. Finding a suitable sequence of the 1D spectra used in constructing the 2D/nD asynchronous spectrum is helpful to improve the signal-to-noise level. A 2D/nD asynchronous spectrum is often produced via a large number of 1D spectra. The resultant colossal number of the possible sequences makes stochastic search the only possible way to find a suitable sequence. Random changing (RC) and random swapping (RS) are two ways to obtain a new sequence. We found that the possibility of finding a better sequence via an RS is significantly higher than that via an RC in the advanced stage of stochastic searching. This is the reason why the performance of RS is superior to that of RC in two model systems where 2D asynchronous spectra are used. We applied the RS approach on the analysis of water/isopropanol mixtures, and satisfactory sequences are acquired with affordable computational cost. Thus, the RS approach brings about an opportunity increase the signal-to-noise level of a 2D asynchronous spectrum in the analysis of the bilinear data from complex mixed samples.

Insight into the stability of protein in confined environment through analyzing the structure of water by temperature-dependent near-infrared spectroscopy

To understand the stability of protein in confined environment, the near-infrared (NIR) spectra of aqueous solutions and reverse micelles (RMs) containing bovine serum albumin (BSA), human serum albumin (HSA) and ovalbumin (OVA) were measured at different temperature. With the resolution enhanced spectra calculated by continuous wavelet transform (CWT), the intensity change of the α-helix band at 4617 cm^-1 with temperature shows a clear denaturation of the protein in aqueous solution but not in RMs. The effect of the confined environment on the stability of the proteins is indicated. More importantly, the intensity change of the spectral bands of water around 6956 and 6842 cm^-1 provide an evidence for the denaturation, suggesting that water can be a probe exhibiting the structural change of proteins. Furthermore, comparing the spectral features of different water structures obtained by principal component analysis (PCA) from the spectra of RM with and without BSA, it is demonstrated that the bridging water connecting NH in protein and SO in the inner surface of RM may be the reason for the stabilization.

Revealing the interactions of water with cryoprotectant and protein by near-infrared spectroscopy

Taking formamide (FA) as a model compound of protein, the water structure in the ternary mixtures of dimethyl sulfoxide (DMSO)-water-FA was studied by near-infrared (NIR) spectroscopy. The interaction of DMSO and water, and the effect of FA on the interaction, were analyzed with the help of chemometric methods. Continuous wavelet transform (CWT) was used to enhance the resolution of the spectra. A peak at 6437 cm^-1 depicting the interaction of DMSO and water through hydrogen bonding (SO…HO) was observed in the transformed spectra. When FA exists in the mixture, the intensity of the peak decreases with the increase of formamide content, showing that FA may replace the water to form the hydrogen bond of SO and HN. In addition, temperature-dependent NIR spectroscopy was used to analyze the effect of the three components on the spectral variation with temperature. Analyzing the spectral data by alternating trilinear decomposition (ATLD) and multiple linear regression, two varying spectral features were obtained that are related to water and DMSO, but no spectral feature was found that significantly varies with the content of FA. The result implies that DMSO is still the key component to prevent the water from icing, although FA may reduce slightly the anti-freezing effect.

A new approach to removing interference of moisture from FTIR spectrum

An approach is developed to remove the interference of moisture from FTIR spectra. The interference arises from two aspects: the fluctuation on the temperature of the HeNe laser and the fluctuation on the transient concentration of moisture in the light - path of an FTIR spectrometer. The temperature fluctuation on the HeNe laser produces a systematic spectral shift between single-beam sample and background spectra, which often makes spectral subtraction method invalid in removing the interference of moisture. Herein, the Carbo similarity metric (the C_AB value) is used to reflect the subtle spectral shift. A database of single-beam background spectra is established based on the concept of big-data and the pigeon-hole theory. The spectral shift is corrected by selecting suitable single-beam background spectra from the database to match with the given single-beam sample spectrum according to the C_AB value. The interference caused by the fluctuation of the transient concentration of moisture is removed using a comprehensive 2D-COS method. We apply the approach on two polymeric samples to retrieve high-quality spectra and reliable second derivative spectra without the interference of moisture. The present work provides a new opportunity of obtaining the reliable second derivative spectra in the spectral region masked by moisture.

Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy

Temperature-dependent near-infrared (NIR) spectroscopy has been developed and taken as a powerful technique for analyzing the structure of water and the interactions in aqueous systems. Due to the overlapping of the peaks in NIR spectra, it is difficult to obtain the spectral features showing the structures and interactions. Chemometrics, therefore, is adopted to improve the spectral resolution and extract spectral information from the temperature-dependent NIR spectra for structural and quantitative analysis. In this review, works on chemometric studies for analyzing temperature-dependent NIR spectra were summarized. The temperature-induced spectral features of water structures can be extracted from the spectra with the help of chemometrics. Using the spectral variation of water with the temperature, the structural changes of small molecules, proteins, thermo-responsive polymers, and their interactions with water in aqueous solutions can be demonstrated. Furthermore, quantitative models between the spectra and the temperature or concentration can be established using the spectral variations of water and applied to determine the compositions in aqueous mixtures.

Solvent Effect on Assembling and Interactions in Solutions of Phenol: Infrared Spectroscopic and Density Functional Theory Study

This work provides new insight into assembling of phenol in various solvents and competition between different kinds of interactions. To examine both weak and strong interactions, we selected a series of non-aromatic and aromatic solvents. Infrared spectra were measured at low (0.05 M) and high (2 M) phenol content. In addition, we performed density functional theory calculations of the structures and harmonic vibrational spectra of 1:1 complexes of phenol with the solvents and the associates of phenol from dimer to tetramer. Based on these results, we divided the solvents into three groups. The first group consists of non-aromatic solvents weakly interacting with phenol. Depending on the concentration, molecules of phenol in these solvents remain non-bonded or self-associated. In diluted solutions of phenol in chlorinated non-aromatic solvents do not appear free OH groups, since they are involved in a weak OH···Cl interaction. It is of note that in diluted solutions of phenol in tetramethyl ethylene both the non-bonded and bonded OH coexists due to solvent-solvent interactions. The second group consists of aromatic solvents with methyl or chlorine substituents. At low concentration, the molecules of phenol are involved in the phenol-solvent OH···π interaction and the strength of these interactions depends on the solvent properties. At a higher phenol content an equilibrium exists between phenol-solvent OH···π and phenol-phenol OH···OH interactions. Finally, the third group includes the aromatic and non-aromatic solvents with highly polar group (C≡N). In these solvents, regardless of the concentration all molecules of phenol are involved in the solute-solvent OH···NC interaction. Comparison of the experimental and theoretical band parameters reveals that molecules of phenol in non-aromatic solvents prefer the cyclic associates, while in the aromatic solvents they tend to form the linear associates.

Quantification of Silymarin in Silybi mariani fructus: Challenging the Analytical Performance of Benchtop vs. Handheld NIR Spectrometers on Whole Seeds

The content of the flavonolignan mixture silymarin and its individual components (silichristin, silidianin, silibinin A, silibinin B, isosilibinin A, and isosilibinin B) in whole and milled milk thistle seeds (Silybi mariani fructus) was analyzed with near-infrared spectroscopy. The analytical performance of one benchtop and two handheld near-infrared spectrometers was compared. Reference analysis was performed with HPLC following a Soxhlet extraction (European Pharmacopoeia) and a more resource-efficient ultrasonic extraction. The reliability of near-infrared spectral analysis determined through partial least squares regression models constructed independently for the spectral datasets obtained by the three spectrometers was as follows. The benchtop device NIRFlex N-500 performed the best both for milled and whole seeds with a root mean square error of CV between 0.01 and 0.17%. The handheld spectrometer MicroNIR 2200 as well as the microPHAZIR provided a similar performance (root mean square error of CV between 0.01 and 0.18% and between 0.01 and 0.23%, respectively). We carried out quantum chemical simulation of near-infrared spectra of silichristin, silidianin, silibinin, and isosilibinin for interpretation of the results of spectral analysis. This provided understanding of the absorption regions meaningful for the calibration. Further, it helped to better separate how the chemical and physical properties of the samples affect the analysis. While the study demonstrated that milling of samples slightly improves the performance, it was deemed to be critical only for the analysis carried out with the microPHAZIR. This study evidenced that rapid and nondestructive quantification of silymarin and individual flavonolignans is possible with miniaturized near-infrared spectroscopy in whole milk thistle seeds.

Spectra-structure correlations in NIR region of polymers from quantum chemical calculations. The cases of aromatic ring, C=O, C≡N and C-Cl functionalities

Near-infrared (NIR) spectroscopy is a valued analytical tool in various applications involving polymers. However, complex nature of NIR spectra imposes difficulties in their direct interpretation. Here, anharmonic quantum chemical calculations are used to simulate NIR spectra of nine polymers; acrylonitrile butadiene styrene (ABS), ethylene-vinyl acetate (EVAC), polycarbonate (PC), polyethylene terephthalate (PET), polylactide or polylactic acid (PLA), polymethylmethacrylate (PMMA), polyoxymethylene (POM), polystyrene (PS) and polyvinylchloride (PVC). The generalized spectra-structure correlations are derived for these systems with focus given to the manifestation in NIR spectra of aromatic ring, C=O, C≡N and C-Cl functionalities. It is concluded that the nature of NIR polymer bands is only moderately sensitive to the remote chemical neighborhood. The majority of NIR absorption of polymers originates from binary combination bands, while the first overtones are meaningful only in ca. 6200-5500 cm^-1 region. The contribution of the overtone bands is relatively higher for the polymers bearing aromatic rings because of higher intensity of C-H stretching overtones. Highly characteristic combination bands of the modes localized in aromatic ring (ring deformation and CH stretching) are relatively independent on the remaining structure of the polymer. The combination bands originating from C=O group are more sensitive to the chemical neighborhood in near proximity, forming a useful fingerprint for a specific polymer. In contrast, the vibrational bands of C≡N functionality are far less useful in NIR region than in infrared (IR) region. With aid of the calculated absorption bands, structural specificity of NIR spectroscopy of polymers can be markedly improved.

Anharmonicity and Spectra-Structure Correlations in MIR and NIR Spectra of Crystalline Menadione (Vitamin K3)

Mid-infrared (MIR) and near-infrared (NIR) spectra of crystalline menadione (vitamin K3) were measured and analyzed with aid of quantum chemical calculations. The calculations were carried out using the harmonic approach for the periodic model of crystal lattice and the anharmonic DVPT2 calculations applied for the single molecule model. The theoretical spectra accurately reconstructed the experimental ones permitting for reliable assignment of the MIR and NIR bands. For the first time, a detailed analysis of the NIR spectrum of a molecular system based on a naphthoquinone moiety was performed to elucidate the relationship between the chemical structure of menadione and the origin of the overtones and combination bands. In addition, the importance of these bands during interpretation of the MIR spectrum was demonstrated. The overtones and combination bands contribute to 46.4% of the total intensity of menadione in the range of 3600-2600 cm-1. Evidently, these bands play a key role in shaping of the C-H stretching region of MIR spectrum. We have shown also that the spectral regions without fundamentals may provide valuable structural information. For example, the theoretical calculations reliably reconstructed numerous overtones and combination bands in the 4000-3600 and 2800-1800 cm-1 ranges. These results, provide a comprehensive origin of the fundamentals, overtones and combination bands in the NIR and MIR spectra of menadione, and the relationship of these spectral features with the molecular structure.

Nondestructive Detection of Weight Loss Rate, Surface Color, Vitamin C Content, and Firmness in Mini-Chinese Cabbage with Nanopackaging by Fourier Transform-Near Infrared Spectroscopy

A nondestructive optical method is described for the quality assessment of mini-Chinese cabbage with nanopackaging during its storage, using Fourier transform-near infrared (FT-NIR) spectroscopy. The sample quality attributes measured included weight loss rate, surface color index, vitamin C content, and firmness. The level of freshness of the mini-Chinese cabbage during storage was divided into three categories. Partial least squares regression (PLSR) and the least squares support vector machine were applied to spectral datasets in order to develop prediction models for each quality attribute. For a comparative analysis of performance, the five preprocessing methods applied were standard normal variable (SNV), first derivative (lst), second derivative (2nd), multiplicative scattering correction (MSC), and auto scale. The SNV-PLSR model exhibited the best prediction performance for weight loss rate (Rp2 = 0.96, RMSEP = 1.432%). The 1st-PLSR model showed the best prediction performance for L* value (Rp2 = 0.89, RMSEP = 3.25 mg/100 g), but also the lowest accuracy for firmness (Rp2 = 0.60, RMSEP = 2.453). The best classification model was able to predict freshness levels with 88.8% accuracy in mini-Chinese cabbage by supported vector classification (SVC). This study illustrates that the spectral profile obtained by FT-NIR spectroscopy could potentially be implemented for integral assessments of the internal and external quality attributes of mini-Chinese cabbage with nanopacking during storage.

Solvent effect on the competition between weak and strong interactions in phenol solutions studied by near-infrared spectroscopy and DFT calculations

Near-infrared (NIR) spectra of phenol in a series of non-aromatic and aromatic solvents were recorded to study the competition between various types of solute-solute and solute-solvent interactions. Depending on the phenol concentration, the free OH and OH involved in the OH⋯OH interactions in the dimers and higher associates are present in cyclohexane solutions. On the other hand, free OH does not appear in Cl-containing solvents since at a low phenol content the OH groups participate in the OH⋯Cl interactions. In CCl₄ and tetrachloroethylene this interaction is weak, while in chlorobenzene the strength of this interaction is higher. In the aromatic solvents the solute-solute OH⋯OH interactions compete with the solute-solvent OH⋯π and aromatic CH⋯OH ones. Consequently, the degree of self-association of phenol in aromatic solvents is smaller than that in non-aromatic ones. The strength of the OH⋯π interactions increases with growing electron-donating ability of the substituents in the benzene derivatives. This observation obtained from the NIR spectra is in line with the results of the theoretical calculations (DFT). A clear correlation appears between the number of methyl groups in aromatic solvents and the population of the free OH groups. The methyl groups are steric hindrances and impede the formation of the OH⋯OH and OH⋯π interactions. Our results suggest the presence of aromatic CH⋯OH solute-solvent interactions, not observed in previous studies. NIR spectroscopy appears to be a powerful tool for exploration of free and weakly-bonded OH groups.

Artificial Intelligence for Pigment Classification Task in the Short-Wave Infrared Range

Hyperspectral reflectance imaging in the short-wave infrared range (SWIR, “extended NIR”, ca. 1000 to 2500 nm) has proven to provide enhanced characterization of paint materials. However, the interpretation of the results remains challenging due to the intrinsic complexity of the SWIR spectra, presenting both broad and narrow absorption features with possible overlaps. To cope with the high dimensionality and spectral complexity of such datasets acquired in the SWIR domain, one data treatment approach is tested, inspired by innovative development in the cultural heritage field: the use of a pigment spectral database (extracted from model and historical samples) combined with a deep neural network (DNN). This approach allows for multi-label pigment classification within each pixel of the data cube. Conventional Spectral Angle Mapping and DNN results obtained on both pigment reference samples and a Buddhist painting (thangka) are discussed.

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.

Advances, challenges and perspectives of quantum chemical approaches in molecular spectroscopy of the condensed phase

The purpose of this review is to demonstrate advances, challenges and perspectives of quantum chemical approaches in molecular spectroscopy of the condensed phase. Molecular spectroscopy, particularly vibrational spectroscopy and electronic spectroscopy, has been used extensively for a wide range of areas of chemical sciences and materials science as well as nano- and biosciences because it provides valuable information about structure, functions, and reactions of molecules. In the meantime, quantum chemical approaches play crucial roles in the spectral analysis. They also yield important knowledge about molecular and electronic structures as well as electronic transitions. The combination of spectroscopic approaches and quantum chemical calculations is a powerful tool for science, in general. Thus, our article, which treats various spectroscopy and quantum chemical approaches, should have strong implications in the wider scientific community. This review covers a wide area of molecular spectroscopy from far-ultraviolet (FUV, 120-200 nm) to far-infrared (FIR, 400-10 cm-1)/terahertz and Raman spectroscopy. As quantum chemical approaches, we introduce several anharmonic approaches such as vibrational self-consistent field (VSCF) and the combination of periodic harmonic calculations with anharmonic corrections based on finite models, grid-based techniques like the Numerov approach, the Cartesian coordinate tensor transfer (CCT) method, Symmetry-Adapted Cluster Configuration-Interaction (SAC-CI), and the ZINDO (Semi-empirical calculations at Zerner's Intermediate Neglect of Differential Overlap). One can use anharmonic approaches and grid-based approaches for both infrared (IR) and near-infrared (NIR) spectroscopy, while CCT methods are employed for Raman, Raman optical activity (ROA), FIR/terahertz and low-frequency Raman spectroscopy. Therefore, this review overviews cross relations between molecular spectroscopy and quantum chemical approaches, and provides various kinds of close-reality advanced spectral simulation for condensed phases.