Applied Spectroscopy

Proniewicz, Edyta

doi: 10.1177/00037028261433049pmid: 41919770

This work presents a systematic analysis of solid–liquid interface interactions of cancer-relevant compounds using surface-enhanced Raman spectroscopy (SERS) combined with two-dimensional correlation spectroscopy (2D-COS). Experimental SERS data and 2D-COS maps for (diphenylphosphoryl)(pyridin-4-yl)methanol adsorbed on copper oxide (CuO) nanostructures (CuONSs) are reported for the first time, while previously published spectra of neurotensin (NT) and neuromedin C (NMC) were re-analyzed to construct corresponding 2D-COS maps. A novel approach was adopted, involving a generalized 2D-COS methodology, in which all data sets were processed using the same preprocessing steps and 2D-COS parameters. This strategy departs from conventional, case-dependent 2D-COS analyses and enables direct comparability across different molecular systems, even for complex spectra characterized by relatively low signal-to-noise ratios. As a result, the proposed workflow provides a reproducible, transferable, and broadly applicable analytical framework rather than system-specific analyses. Analysis of intensity variations, as well as synchronous and asynchronous correlations, allowed the identification of subtle spectral changes related to adsorption geometry and molecular orientation. Observed trends in band intensities provide a consistent and cross-system basis for assigning molecular interactions and surface orientations, demonstrating that 2D-COS can yield robust and mechanistically interpretable insights beyond what is accessible from conventional SERS spectra. These findings underscore the power of combining SERS and a standardized 2D-COS analysis to reveal dynamic molecular behavior at interfaces, offering a general framework for future studies on biologically and chemically relevant systems.

Shinzawa, Hideyuki; Yamane, Shogo; Kanayama, Naoki

doi: 10.1177/00037028261445431pmid: 42138333

This paper describes a method that can be utilized for pre-sorting in chemical recycling processes. Namely, the blend ratios of polymers are determined by employing a low-cost near-infrared (NIR) spectrometer and a spectral deconvolution technique called the classical least squares (CLS) method. The determination of the blend ratio of polymer blends by CLS assumes that the raw material composition of the post-consumer or post-industrial materials is often not completely unknown; rather, it is generally partially known or can be reasonably inferred thanks to prior knowledge of product specifications or manufacturing processes. In short, we can often use the pure component spectra of the constituents in the polymer samples. The NIR spectra effectively capture the structural features of styrene–butadiene–styrene (SBS)/polyethylene (PE) and polypropylene (PP)/PE blend samples, which are complicated by greatly overlapping peaks arising from the components. The near-infrared (NIR) spectra were then subjected to CLS to obtain so-called concentration profile, e.g., the blend ratio of the polymer constituents, by using pure component spectra of SBS, PE, and PP. The pure component spectra were successfully fitted to the observed NIR spectra of SBS/PE and PP/PE samples and estimated blend ratios were achieved with exceptionally high accuracy thus demonstrating that NIR spectroscopy can be a powerful tool for use in the pre-sorting process.

Kitt, Jay P.; Harris, Joel M.

doi: 10.1177/00037028261442539pmid: 42080837

Pore-forming peptides are a pharmacologically relevant class of membrane-active molecules capable of self-assembling in phospholipid bilayers to form transmembrane ion channels that induce uncontrolled ion flux, disrupting cellular homeostasis. Developing mechanistic insight into how these molecules perturb lipid–bilayer structure is critical for understanding their biological activity and for rational design of next-generation antimicrobials. In this work, optical-trapping confocal Raman microscopy was employed to investigate the structural impact of gramicidin A (gA) incorporation into individual 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) phospholipid vesicle bilayers as a function of peptide concentration in the vesicle membrane. Raman spectra acquired from individual, optically trapped vesicles confirmed gA incorporation through observation of peptide-specific tryptophan vibrational markers. Concentration-dependent spectra collected from 0 to 20 mol% gA vesicles revealed systematic disordering of DMPC acyl chains, observed through changes in the C–C stretching, C–H twisting, and C–H bending regions, consistent with bilayer deformation driven by hydrophobic mismatch between the gA channel and surrounding lipid chains. Self-modeling curve resolution analysis of the concentration-dependent spectra identified two spectral components: an ordered bilayer of unperturbed DMPC chains, and a gA-perturbed disordered bilayer. The amplitude of the two components vary linearly with gA concentration but with opposite sign. This result is consistent with each additional gA channel generating a localized region of disordered boundary lipids whose population grows in proportion with peptide concentration. Lipids not within the local region perturbed by the presence of gA remain ordered and decrease in proportion to their diminishing population until they disappear when the gA concentration reaches ∼20 mol%, indicating that 7–8 lipids surrounding each gA channel are impacted by hydrophobic mismatch. These results establish optical-trapping confocal Raman microscopy as an effective method for quantitative, single-vesicle investigation of peptide-membrane interactions, and highlight the power of model-free spectral analysis for unconstrained resolution of the peptide impact on membrane structure.

Jones, Christopher

doi: 10.1177/00037028261437102pmid: 42033403

Spectral similarity supports comparison of circular dichroism (CD) spectra by using all datapoints to improve alignment of wavelength, intensity and offset. CD is increasingly used to confirm the higher order structure and stability of biopharmaceutical proteins, which requires method validation and assessment of robustness in quality regulated analytical systems. Camphor-10-sulphonic acid (CSA), or its ammonium salt, is widely used to calibrate spectropolarimeters, with its use specified in the European Pharmacopoeia (EP), and, more broadly, as a system suitability standard. Spectral similarity comparison of 75 CSA reference spectra in the Protein Circular Dichroism Data Bank (PCDDB) showed the potential value of this approach to monitor instrument performance and support compliance within a quality system.

Kanayama, Naoki; Hidaka, Kohei; Shimamura, Mamiko; Miura, Takamasa; Takahara, Noriko; Hagihara, Hideaki; Shinzawa, Hideyuki

doi: 10.1177/00037028261444737pmid: 42132375

This study demonstrates the use of Fourier transform infrared photoacoustic spectroscopy (FT-IR-PAS) to investigate surface structural changes in biodegradable poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBH) films during marine microbial degradation. FT-IR-PAS, a non-contact and surface-sensitive technique, enables the analysis of brittle or rough surfaces without pretreatment and offers clear advantages over conventional attenuated total reflection infrared (ATR-IR) for degraded films. To enhance spectral interpretation, FT-IR-PAS was combined with two-trace two-dimensional (2T2D) correlation analysis, which allowed the detection of subtle spectral variations associated with microbial degradation. This approach revealed changes in the carbonyl stretching bands (1675–1775 cm–1) linked to the molecular order of the PHBH chains, enabling the detection of changes in the proportion of crystalline and amorphous regions on the surface. Asynchronous 2T2D correlation spectra for PHBH residues revealed specific cross-peaks at (1726 cm–1, 1743 cm–1), indicating preferential degradation of amorphous regions. Furthermore, the asynchronous correlation intensities at these positions showed a positive relationship with the PHBH film weight loss resulting from microbial degradation. These findings highlight FT-IR-PAS coupled with 2T2D analysis as a powerful, non-destructive approach for elucidating the surface degradation mechanisms of biodegradable polymers under marine conditions.

Oka, Takayuki; Shioya, Nobutaka; Hasegawa, Takeshi

doi: 10.1177/00037028261450651pmid: 42153792

Although atomic force microscopy–infrared (AFM–IR) spectroscopy enables nanoscale infrared characterization, the dielectric origin of its spectral contrast, particularly the role of collective vibrational modes, remains incompletely understood. Here, we investigate the correlation between nanoscale infrared spectra and surface morphology using thin films of perfluorotetracosane (C24F50). By comparing low-temperature vapor-deposited films and their aged counterparts, we track aging-induced morphological evolution from lying-oriented sub-micrometer aggregates to standing-oriented crystalline grains. For discussing fine features in the nano-scale spectrum, infrared p-polarized multiple-angle incidence resolution spectroscopy (pMAIRS) is also employed as a macroscopic reference in advance. The pMAIRS analysis reveals pronounced longitudinal–transverse optical (LO–TO) splitting, which increases upon aging due to an enhanced Berreman-type longitudinal field contribution associated with surface flattening and improved crystallinity. Nanoscale AFM–IR measurements in a resonance-enhanced-mode with top-down illumination configuration demonstrate that the local spectral response is predominantly governed by the transverse optical (TO) dielectric function, while surface phonon–polariton (SPP) modes are strongly enhanced, reflecting localized electromagnetic field confinement at crystalline grains. Through rigorous cross-scale comparisons of macroscopic and nanoscale spectroscopy, this study has experimentally established the dominant TO-controlled contrast mechanism in top-down AFM–IR and revealed the characteristics of SPP-driven nanoscale spectra. These results demonstrate that AFM–IR is a powerful probe for investigating both the chemical identity of surface-active organic materials and nanoscale surface morphology.

Jakubek, Ryan S.; Bhartia, Rohit; Fries, Marc D.

doi: 10.1177/00037028261446995pmid: 42165618

Quantification of band parameters in spectral data typically requires iteratively fitting the spectroscopic feature to Gaussian, Lorentzian, or pseudo-Voigt functions for the extraction of band height, width, position, and area values. However, there are currently no adequate methods of measuring their errors. Previously, Lenz and Ayres [“Errors Associated with Fitting Gaussian Profiles to Noisy Emission-Line Spectra”. Publications of the Astronomical Society of the Pacific. 1992. 104: 1104. DOI: 10.1086/133096] addressed this problem for Gaussian fits by empirically fitting a set of model data to derive equations for the calculation of Gaussian band parameter errors. However, the treatment of only Gaussian fitting functions greatly limits utility. In this study, we extend their error calculation methods to include Lorentzian and pseudo-Voigt fits for error analysis in a wide range analytical techniques that utilize spectral fitting. We do this empirically by fitting a model dataset of noisy spectral signals to Gaussian, Lorentzian, and pseudo-Voigt functions to calculate the accuracy and precision of the fits. We derive a set of equations for the simple calculation of band fitting errors. In addition, the simple calculation of band height and area errors allows for easy calculation of multi-pixel signal-to-noise ratios that were previously shown to significantly improve instrument limit-of-detection [Jakubek et al. “Improving Spectroscopic Detection Limits with Multi-Pixel Signal-to-Noise Ratio Calculations: Application to the SHERLOC Instrument Aboard the Perseverance Rover”. Analytica Chimica Acta. 2025. 1357: 344072. DOI: 10.1016/j.aca.2025.344072]. The results of this work are broadly applicable to most analytical techniques that produce spectral data.

Schulze, H. Georg; Haldavekar, Rupa; Rangan, Shreyas; Colombini, Smilla; Blades, Michael W.; Turner, Robin F. B.; Piret, James M.

doi: 10.1177/00037028261439686pmid: 41879274

Partial least squares discriminant analysis (PLS-DA) is often used for data sets that consist of a large number of potential predictors but relatively few observations such that chance correlations between predictors and response can occur that lead to false conclusions. Hence, there is a need for data adequacy testing before model building but currently no such method exists. In this work we propose one where we used random permutations to destroy the correlation structure between predictor and response data. This produced normal distributions of chance correlation coefficients that were used to find correlation coefficients in the non-permuted data that differed significantly from chance occurrences. Based on these distributions, we defined two novel null hypotheses to control for when a true null hypothesis is incorrectly rejected and the other for when a false null hypothesis is not rejected. To counter false positive errors, the standard significance levels were adjusted with predictor-based Bonferroni corrections. To counter false negative errors, we compared the true and permuted correlation coefficients in distribution tails. The outcomes of the hypothesis tests then indicated whether or not PLS-DA models could be successfully built from these data sets. We also investigated how to determine the number of samples needed for a data set with a given number of predictors. Simulations showed that our method produced significantly fewer false positives than PLS-DA (P = 0.0018, our method error rate 12 × less than PLS-DA error rate) but significantly more false negatives (P = 0.0003, our method error rate 4.5 × more than PLS-DA error rate). Data from Raman spectroscopy showed that the method transferred to real data. By pre-screening such data, our method can aid in assessing whether to proceed with model building and, when there is a need to increase the sample size, we show by how much.

Lessard, Myriam; Pellerin, Christian

doi: 10.1177/00037028261436431pmid: 41972915

Electrospun fibers generally exhibit improved properties with a reduction in diameter, a phenomenon often correlated with a higher orientation of the polymer chains. Over the years, confocal Raman microscopy has proven to be a valuable technique for studying the molecular orientation of individual fibers and understanding how electrospinning conditions govern their structure–properties relationships. However, the current methods for the quantification of orientation, via the order parameter ⟨P2⟩, require the acquisition of four Raman spectra in different polarization configurations, which makes them prone to drifts. Band ratio calibration curves are a useful alternative, but they may not be as reliable because they only rely on two bands. In this work, we develop a calibration method based on partial least squares regression (PLSR) to quantify the order parameter ⟨P2⟩ values from a single polarized Raman spectrum. As proof of concept, we demonstrate PLS models for three polymers exhibiting contrasting orientation and spectral properties, namely poly (ethylene terephthalate) or PET, poly (ethylene oxide) or PEO, and polyoxymethylene (POM). The three PLS models provide good calibration quality and prediction performance, where the errors of the predicted values are similar to those of the calibration data. We also demonstrate the applicability of our PLS models by reproducing the evolution of orientation with fiber diameter for the three systems investigated.

Park, Yeonju; Jing, Young Mee; Noda, Isao

doi: 10.1177/00037028261440561pmid: 41879270

The growing interest in high-purity bioplastics for emerging specialized applications motivated us to investigate the crystallization of poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBHx) from a chloroform solution using advanced spectroscopic techniques. Previous study of the carbonyl stretching region of time-dependent attenuated total reflection infrared (ATR-IR) spectra had revealed that solution crystallization process of PHBHx involving distinct intermediate species was markedly different from the more traditional melt crystallization. IR study of PHBHx solution crystallization is now extended to more complex C–H stretching and fingerprint regions. Characteristic IR bands of the system showing the least correlated and most independent behaviors with each other were identified using a new technique based on a two-dimensional (2D) discrimination spectrum. Correlation filters based on the characteristic bands were used to selectively attenuate interfering spectral contributions in conjunction with the hetero-mode two-dimensional correlation spectroscopy (2D-COS) analysis. Traditional classification of decreasing and increasing IR bands, respectively, during the crystallization process of PHBHx copolymers simply to the amorphous and crystalline components probably needs to be reconsidered. Dynamics of bands in the C–H stretching and fingerprint regions are not fully synchronized with the behavior of amorphous or crystalline species characterized by the carbonyl stretching region. The result strongly suggests the presence of some intermediate species appearing after the consumption of amorphous components and prior to the formation of crystals.