Applied Spectroscopy

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Raman spectroscopy using the mid-frequency (1800–1500 cm⁻¹) and low-frequency (200–8 cm⁻¹) spectral regions is used to study the transformation of amorphous indomethacin (IND) to the γ-crystalline form. The low-frequency spectral region provides access to collective vibrations of molecules in the crystalline and amorphous state, while the mid-frequency spectral region provides access to the molecular vibrations that are sensitive to the local functional group environment. Both spectral regions provide distinct Raman bands for the amorphous and crystalline forms of IND. The more intense low-frequency Raman bands provide greater sensitivity for detecting the onset of crystallization in an amorphous matrix. Subtle differences in the behavior of the initial crystalline process of IND are observed between the low-frequency and mid-frequency Raman bands. These observations suggest that different responses for mid- and low-frequency Raman bands occur for the microcrystalline domains present during the initial crystallization process. The suitability of low-frequency Raman spectroscopy to monitor IND in a suspension was demonstrated. This suggests that the technique will be a valuable tool for at-line and on-line monitoring of active pharmaceutical ingredient crystallization.

A new concentration series is proposed for the construction of a two-dimensional (2D) synchronous spectrum for orthogonal sample design analysis to probe intermolecular interaction between solutes dissolved in the same solutions. The obtained 2D synchronous spectrum possesses the following two properties: (1) cross peaks in the 2D synchronous spectra can be used to reflect intermolecular interaction reliably, since interference portions that have nothing to do with intermolecular interaction are completely removed, and (2) the two-dimensional synchronous spectrum produced can effectively avoid accidental collinearity. Hence, the correct number of nonzero eigenvalues can be obtained so that the number of chemical reactions can be estimated. In a real chemical system, noise present in one-dimensional spectra may also produce nonzero eigenvalues. To get the correct number of chemical reactions, we classified nonzero eigenvalues into significant nonzero eigenvalues and insignificant nonzero eigenvalues. Significant nonzero eigenvalues can be identified by inspecting the pattern of the corresponding eigenvector with help of the Durbin-Watson statistic. As a result, the correct number of chemical reactions can be obtained from significant nonzero eigenvalues. This approach provides a solid basis to obtain insight into subtle spectral variations caused by intermolecular interaction.

Attenuated total reflection Fourier transform infrared (FT-IR) spectroscopy was used to characterize 40 commercial tannins, including condensed and hydrolyzable chemical classes, provided as powder extracts from suppliers. Spectral data were processed to detect typical molecular vibrations of tannins bearing different chemical groups and of varying botanical origin (univariate qualitative analysis). The mid-infrared region between 4000 and 520 cm⁻¹ was analyzed, with a particular emphasis on the vibrational modes in the fingerprint region (1800-520 cm⁻¹), which provide detailed information about skeletal structures and specific substituents. The region 1800–1500 cm⁻¹ contained signals due to hydrolyzable structures, while bands due to condensed tannins appeared at 1300–900 cm⁻¹ and exhibited specific hydroxylation patterns useful to elucidate the structure of the flavonoid monomeric units. The spectra were investigated further using principal component analysis for discriminative purposes, to enhance the ability of infrared spectroscopy in the classification and quality control of commercial dried extracts and to enhance their industrial exploitation.

This study has investigated hydrophilicity changes and their inhomogeneity of TiO₂ films on Pyrex glasses by near-infrared (NIR) spectral imaging. Near-infrared spectra of TiO₂ films in the 9000–4000 cm⁻¹ region were measured using a newly developed NIR camera named Compovision. A band in the 5400–4800 cm⁻¹ region, which is assigned to a combination (v₂ + v₃) mode of bending (v₂) and antisymmetric stretching (v₃) modes of the H₂O molecule, was clearly identified and its intensity increased with time in the air. It is interesting that the increased rate rose with ultraviolet (UV) light irradiation (300–400 nm, 1 mW cm⁻²) compared to without UV light irradiation. This result suggested that the hydrophilicity of TiO₂ was enhanced about twice upon the UV light irradiation. Moreover, the NIR images clarified spatial distributions of the hydrophilicity on the TiO₂ surface with a significantly wide area (20 × 40 mm) and a high speed (within 5 s for one image). This rapid imaging system enabled us to detect the hydrophilicity change during only 1 min. The potential of this camera is quite superior, not only for basic research, but also for diverse industrial applications.

Using partial least square discriminate analysis (PLSDA), we studied the spectroscopic differences between the commonly used filler-binder microcrystalline cellulose (MCC) from five manufactures. These samples had subtle differences in the chemical and physical properties, which are often the cause of differences in excipient performance. Studying these differences allowed us to build and validate a model to classify five manufacturers of MCC using near-infrared (NIR) spectra. The sample training set includes 39 MCC samples collected from five manufactures with regions spanning the United States of America, Japan, Taiwan, Germany, and Brazil. The samples from individual manufacturers include diverse grades that differ in moisture content, particle size, and bulk density. Optimized pretreatment methods were identified as standard normal variate normalization, followed by Savitzky-Golay second derivative, mean centering, and orthogonal signal correction. The model was optimized with cross-validation and validated with an independent sample set comprising nine samples collected from those five manufacturers. The results showed that none of the samples in the independent validation set was misclassified. The score and loading plots revealed that the differences in content of oxidized cellulose group, water content and states, hydrogen bonding, and degree of polymerization of the MCC samples are responsible for the class differentiation. Permutation test demonstrated that the outcome of the PLSDA model was significantly different from that of the randomly generated model. The advantages and limitations of the method in this type of application were discussed.

Low aqueous solubility of active pharmaceutical ingredients (APIs) is an enduring problem in pharmaceutical development, and it is becoming increasingly prevalent among new drug candidates. It is estimated that about 40% of drugs in the development pipeline and approximately 60% of the drugs coming directly from discovery suffer from poor aqueous solubility and slow dissolution, thereby reducing their bioavailability and efficacy and thus preventing their commercialization. It is well known that utilizing the amorphous form of a drug can be a useful approach to improve the dissolution rate and solubility of poorly water-soluble APIs. Amorphous compounds are thermodynamically unstable, but they can be stabilized by combining them with a carrier polymer (excipient) to form a solid dispersion. High-throughput Raman spectroscopy was used in this study to identify excipients that promote formation and stabilization of the amorphous drug form in solid dispersions. Four model APIs were used as poorly soluble drug candidates: ketoprofen, danazol, griseofulvin, and probucol. The Raman signals of excipients were generally negligible, and therefore Raman bands from the drugs were used with minimal spectral pre-processing. By comparing Raman spectra collected from the APIs in the crystalline and molten state, appropriate spectral features and regions were identified for the development of semi-quantitative methods to determine the amorphous content for each API. It is demonstrated that methods based on peak intensity ratio, peak width, peak distance, and classical least squares can all be effective methods for the screening of excipients. Interesting excipient-dependent phase transformation behavior was also observed for probucol.

Second derivative and band simulation techniques are used in a synergetic relationship to identify components in the infrared (IR) spectra of liquid light and heavy water. Nine Gaussian components are retrieved in massive OH and OD stretch absorption. In this context, v₁ and v₃ are the principal components along with satellites derived from harmonic and combination bands. The Raman spectrum of light water matches the IR components with intensity variations as expected.

A fluorescence quenching model using copper(II) ion (Cu²⁺) ion selective electrode (Cu-ISE) is developed. It uses parallel factor analysis (PARAFAC) to model fluorescence excitation–emission matrices (EEMs) of humic acid (HA) samples titrated with Cu²⁺ to resolve fluorescence response of fluorescent components to Cu²⁺ titration. Meanwhile, Cu-ISE is employed to monitor free Cu²⁺ concentration ([Cu]) at each titration step. The fluorescence response of each component is fit individually to a nonlinear function of [Cu] to find the Cu²⁺ conditional stability constant for that component. This approach differs from other fluorescence quenching models, including the most up-to-date multi-response model that has a problematic assumption on Cu²⁺ speciation, i.e., an assumption that total Cu²⁺ present in samples is a sum of [Cu] and those bound by fluorescent components without taking into consideration the contribution of non-fluorescent organic ligands and inorganic ligands to speciation of Cu²⁺. This paper employs the new approach to investigate Cu²⁺ binding by Pahokee peat HA (PPHA) at pH values of 6.0, 7.0, and 8.0 buffered by phosphate or without buffer. Two fluorescent components (C1 and C2) were identified by PARAFAC. For the new quenching model, the conditional stability constants (logK₁ and logK₂) of the two components all increased with increasing pH. In buffered solutions, the new quenching model reported logK₁ = 7.11, 7.89, 8.04 for C1 and logK₂ = 7.04, 7.64, 8.11 for C2 at pH 6.0, 7.0, and 8.0, respectively, nearly two log units higher than the results of the multi-response model. Without buffer, logK₁ and logK₂ decreased but were still high (>7) at pH 8.0 (logK₁ = 7.54, logK₂ = 7.95), and all the values were at least 0.5 log unit higher than those (4.83 ∼ 5.55) of the multi-response model. These observations indicate that the new quenching model is more intrinsically sensitive than the multi-response model in revealing strong fluorescent binding sites of PPHA in different experimental conditions. The new model was validated by testing it with a mixture of two fluorescing Cu²⁺ chelating organic compounds, i.e., _l-tryptophan and salicylic acid mixed with one non-fluorescent binding compound oxalic acid titrated with Cu²⁺ at pH 5.0.

Mid-infrared (MIR) and near-infrared (NIR) spectroscopy provide useful information on the molecular composition of biological systems. Because they are sensitive to organic and mineral components, there is a growing interest in these techniques for the development of biomarkers that reflect intrinsic characteristics of plants and their mode of degradation. Due to their complexity and complementary nature, an important challenge is the combining of MIR and NIR information to identify discriminating wavenumbers in each wavenumber region, with the ultimate goal of assessing the biodegradation process of a lignocellulosic biomass at different time scales. This work investigates the potential of using the outer product to combine MIR and NIR spectra to highlight the connections between fundamental molecular vibrations and their combinations and bonds. Because this operation yields high-dimensional spectra, we propose to use a genetic algorithm to select the most discriminant wavenumbers within the degradation process. The results from two lignocellulosic biomasses with different biodegradation kinetics, miscanthus aerial parts and maize roots, confirm that the outer product combination of MIR and NIR spectral information allows a better discrimination of the biodegradation kinetic compared with the simple concatenation of MIR and NIR spectra or with the use of MIR or MIR spectral information separately. We show that the genetic algorithm selects wavenumbers that correspond to principal vibrations of chemical functional groups of compounds that undergo degradation/conversion during the biodegradation of the lignocellulosic biomass.

The noninvasive sensing of the blood glucose concentration is usually based on optical, electrical, or acoustical signals induced by blood glucose; these signals are extremely weak and subject to fluctuations caused by the variation in the body or surroundings. Therefore, it is challenging to detect blood glucose noninvasively with high accuracy, and no successful accurate and noninvasive clinical application has been reported. We found that there are two key measurement issues to be addressed: systematic errors, such as the errors induced by the drifts of devices or by variations in body temperature, among others, are too large to guarantee the trueness of measurement at present; and random disturbances in repeated tests, such as disturbances associated with variations in the human–machine interface, pulses, and the thermal noise of the devices, cause larger repeated measurement errors and compromise precision. Recent novel reference measurements based on differential near-infrared (NIR) spectroscopy are considered promising for solving the systematic error issue by establishing matched references, collected at another detection site or at another time, and subsequently differencing to remove the common systematic errors. However, differencing weakens the signal of interest itself and enlarges the effects of the second issue, random disturbances affecting the precision. It is understood that only reference measurements that can meet the precision requirement will be promising for future applications. Therefore, this study quantitatively evaluates the precision of the main differential NIR spectroscopy measurements considering similar conditions and minimized random disturbances. The precision of the measurements under these conditions should represent their optimal precision levels. After the evaluation, noninvasive glucose-sensing methods that hold promise for future clinical application are proposed. Finally, the evaluation criteria could be a reference for the noninvasive detection of other physiological components.

A series of chlorobutyl rubber/polyamide-12 (CIIR/PA-12) blends compatibilized by different amounts of maleic anhydride (MAH) grafted polypropylene (PP-g-MAH) were investigated by attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) mapping. Multivariate curve resolution (MCR) was used to process the FT-IR images. Both the spectra of pure components in the blends and their concentration distributions in a micro-region were acquired. Our results demonstrated that the blend with 15 parts per hundred rubber PP-g-MAH showed the best miscibility. An amide interphase and an imide interphase were inferred by analyzing the spectra of MCR component 3 of the blends with and without PP-g-MAH, respectively. Correspondingly, two different compatibilizing mechanisms were proposed for these blends.

Optical emission spectroscopy was performed during atmospheric pressure plasma needle helium jet treatment of various tooth-bleaching gels. When the gel sample was inserted under the plasma plume, the intensity of all the spectral features increased approximately two times near the plasma needle tip and up to two orders of magnitude near the sample surface. The color change of the hydroxylapatite pastille treated with bleaching gels in conjunction with the atmospheric pressure plasma jet was found to be in correlation with the intensity of OH emission band (309 nm). Using argon as an additive to helium flow (2 L/min), a linear increase (up to four times) of OH intensity and, consequently, whitening (up to 10%) of the pastilles was achieved. An atmospheric pressure plasma jet activates bleaching gel, accelerates OH production, and accelerates tooth bleaching (up to six times faster).

Serum samples taken from healthy individuals and pre- and post-operative esophageal cancer patients were analyzed using surface-enhanced Raman spectroscopy (SERS) to explore the feasibility of diagnosing esophageal cancer using the technique. The serum spectrum data were collected using a He–Ne laser of wavelength 632.8 nm. Differences in peaks assigned to nucleic acids, lipids, and proteins were found to be statistically significant between groups, which implies that corresponding serum alterations occur with the development of esophageal diseases. For quantitative analysis, the chemometric methods of hierarchical clustering analysis and principal component analysis were utilized on the obtained SERS spectra for classification with good results.

The technique of femtosecond laser-induced breakdown spectroscopy (FLIBS) was employed to investigate seven explosive molecules of nitropyrazole in three different atmospheres: ambient air, nitrogen, and argon. The FLIBS data illustrated the presence of molecular emissions of cyanide (CN) violet bands, diatomic carbon (C₂) Swan bands, and atomic emission lines of C, H, O, and N. To understand the plasma dynamics, the decay times of molecular and atomic emissions were determined from time-resolved spectral data obtained in three atmospheres: air, argon, and nitrogen. The CN decay time was observed to be longest in air, compared to nitrogen and argon atmospheres, for the molecules pyrazole (PY) and 4-nitropyrazole (4-NPY). In the case of C₂ emission, the decay time was observed to be the longest in argon, compared to the air and nitrogen environments, for the molecules PY, 4-NPY, and 1-methyl-3,4,5-trinitropyrazole. The intensities of the CN, C₂, C, H, O, and N emission lines and various molecular/atomic intensity ratios such as CN/C₂, CN^sum/C₂^sum, CN/C, CN^sum/C, C₂/C, C₂^sum/C, (C₂ + C)/CN, (C₂^sum + C)/CN^sum, O/H, O/N, and N/H were also deduced from the LIBS spectra obtained in argon atmosphere. A correlation between the observed decay times and molecular emission intensities with respect to the number of nitro groups, the atmospheric nitrogen content, and the oxygen balance of the molecules was investigated. The relationship among the LIBS signal intensity, the molecular/atomic intensity ratios, and the oxygen balance of these organic explosives was also explored.