Spectra-structure Correlations Research Articles

Surface-Enhanced Raman Spectroscopy: Current Understanding, Challenges, and Opportunities.

While surface-enhanced Raman spectroscopy (SERS) has experienced substantial advancements since its discovery in the 1970s, it is an opportunity to celebrate achievements, consider ongoing endeavors, and anticipate the future trajectory of SERS. In this perspective, we encapsulate the latest breakthroughs in comprehending the electromagnetic enhancement mechanisms of SERS, and revisit CT mechanisms of semiconductors. We then summarize the strategies to improve sensitivity, selectivity, and reliability. After addressing experimental advancements, we comprehensively survey the progress on spectrum-structure correlation of SERS showcasing their important role in promoting SERS development. Finally, we anticipate forthcoming directions and opportunities, especially in deepening our insights into chemical or biological processes and establishing a clear spectrum-structure correlation.

Deep Learning-Assisted Spectrum-Structure Correlation: State-of-the-Art and Perspectives.

Spectrum-structure correlation is playing an increasingly crucial role in spectral analysis and has undergone significant development in recent decades. With the advancement of spectrometers, the high-throughput detection triggers the explosive growth of spectral data, and the research extension from small molecules to biomolecules accompanies massive chemical space. Facing the evolving landscape of spectrum-structure correlation, conventional chemometrics becomes ill-equipped, and deep learning assisted chemometrics rapidly emerges as a flourishing approach with superior ability of extracting latent features and making precise predictions. In this review, the molecular and spectral representations and fundamental knowledge of deep learning are first introduced. We then summarize the development of how deep learning assist to establish the correlation between spectrum and molecular structure in the recent 5 years, by empowering spectral prediction (i.e., forward structure-spectrum correlation) and further enabling library matching and de novo molecular generation (i.e., inverse spectrum-structure correlation). Finally, we highlight the most important open issues persisted with corresponding potential solutions. With the fast development of deep learning, it is expected to see ultimate solution of establishing spectrum-structure correlation soon, which would trigger substantial development of various disciplines.

A machine learning protocol for geometric information retrieval from molecular spectra

Geometric information of molecules is closely related to their properties, and vibrational spectroscopy, as a common and powerful analytical tool for determining molecular structure, can assist in gaining precise geometric information. Traditional methods used to delineate spectrum-structure correlations are often expensive, time-consuming, and require extensive professional expertise. In this work, we used a machine learning protocol to construct a map from spectra to molecular geometric structures, and employed Grad-CAM, a convolutional network interpretation technology, to analyze which kinds of chemical information are important for determining our model’s results. The results obtained for six small molecules of differing structures demonstrate that the model is capable of (1) extracting the crucial spectral features that are vital to downstream tasks without necessitating any manual preprocessing, and (2) enabling retrieval of molecular structural information with high precision.

Quantitative Structural Description of Zeolites by Machine Learning Analysis of Infrared Spectra

Application of machine learning (ML) algorithms to spectroscopic data has a great potential for obtaining hidden correlations between structural information and spectral features. Here, we apply ML algorithms to theoretically simulated infrared (IR) spectra to establish the structure-spectrum correlations in zeolites. Two hundred thirty different types of zeolite frameworks were considered in the study whose theoretical IR spectra were used as the training ML set. A classification problem was solved to predict the presence or absence of possible tilings and secondary building units (SBUs). Several natural tilings and SBUs were also predicted with an accuracy above 89%. The set of continuous descriptors was also suggested, and the regression problem was also solved using the ExtraTrees algorithm. For the latter problem, additional IR spectra were computed for the structures with artificially modified cell parameters, expanding the database to 470 different spectra of zeolites. The resulting prediction quality above or close to 90% was obtained for the average Si-O distances, Si-O-Si angles, and volume of TO4 tetrahedra. The obtained results provide new possibilities for utilization of infrared spectra as a quantitative tool for characterization of zeolites.

Raman microspectroscopy based TNM staging and grading of breast cancer

The tumor-node-metastasis (TNM) system is the most common way that doctors determine the anatomical extent of cancer on the basis of clinical and pathological criteria. In this study, a spectral histopathological study has been carried out to bridge Raman micro spectroscopy with the breast cancer TNM system. A total of seventy breast tissue samples, including healthy tissue, early, middle, and advanced cancer, were investigated to provide detailed insights into compositional and structural variations that accompany breast malignant evolution. After evaluating the main spectral variations in all tissue types, the generalized discriminant analysis (GDA) pathological diagnostic model was established to discriminate the TNM staging and grading information. Moreover, micro-Raman images were reconstructed by K-means clustering analysis (KCA) for visualizing the lobular acinar in healthy tissue and ductal structures in all early, middle and advanced breast cancer tissue groups. While, univariate imaging techniques were adapted to describe the distribution differences of biochemical components such as tryptophan, β-carotene, proteins, and lipids in the scanned regions. The achieved spectral histopathological results not only established a spectra-structure correlations via tissue biochemical profiles but also provided important data and discriminative model references for in vivo Raman-based breast cancer diagnosis.

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.

A unique approach for in-situ monitoring of the THCA decarboxylation reaction in solid state

The decarboxylation of Δ9-tetrahydrocannabinolic acid (THCA) plays pivotal role in the potency of medical cannabis and its extracts. Our present work aims to draw attention to mid-infrared (MIR) spectroscopy to in-situ monitor and decipher the THCA decarboxylation reaction in the solid state. The initial TG/DTG curves of THCA, for a first time, outlined the solid–solid decarboxylation dynamics, defined the endpoint of the process and the temperature of the maximal conversion rate, which aided in the design of the further IR experiment. Temperature controlled IR spectroscopy experiments were performed on both THCA standard and cannabis flower by providing detailed band assignment and conducting spectra-structure correlations, based on the concept of functional groups vibrations. Moreover, a multivariate statistical analysis was employed to address the spectral regions of utmost importance for the THCA → THC interconversion process. The principal component analysis model was reduced to two PCs, where PC1 explained 94.76% and 98.21% of the total spectral variations in the THCA standard and in the plant sample, respectively. The PC1 plot score of the THCA standard, as a function of the temperature, neatly complemented to the TG/DTG curves and enabled determination of rate constants for the decarboxylation reaction undertaken on several selected temperatures. The predictive capability of MIR was further demonstrated with PLS (R2X = 0.99, R2Y = 0.994 and Q2 = 0.992) using thermally treated flower samples that covered broad range of THCA/THC content. Consequently, a progress in elucidation of kinetic models of THCA decarboxylation in terms of fitting the experimental data for both, solid state standard substance and a plant flower, was achieved. The results open the horizon to promote an appropriate process analytical technology (PAT) in the outgrowing medical cannabis industry.

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.

Infrared spectroscopic study of nickel complexes with salen-type ligands and their polymers

In this work, a series of the monomeric and polymeric complexes of nickel (II) with N2O2 Schiff base ligands were investigated by Fourier Transform Infrared (FTIR) spectroscopy. In these complexes, the molecular structure was modulated by peripheral substitution affecting the electronic and steric properties of the compounds. The complexes with donor and acceptor substituents in the phenolate moieties were examined. Also, the diimine backbone was varying by aliphatic and aromatic groups, the latter is in conjugation with the phenolate moieties. The empirical band assessment was supported by theoretical modeling of the infrared spectra at the DFT level of theory. Infrared spectra–structure correlations for metal complexes were found. A complete set of vibrational characteristics for all complexes was determined as well as vibrational properties for the diimine bridge and substituents in the phenolate moieties.

Decoding the 2D IR spectrum of the aqueous proton with high-level VSCF/VCI calculations

The aqueous proton is a common and long-studied species in chemistry, yet there is currently intense interest devoted to understanding its hydration structure and transport dynamics. Typically described in terms of two limiting structures observed in gas-phase clusters, the Zundel H5O2 + and Eigen H9O4 + ions, the aqueous structure is less clear due to the heterogeneity of hydrogen bonding environments and room-temperature structural fluctuations in water. The linear infrared (IR) spectrum, which reports on structural configurations, is challenging to interpret because it appears as a continuum of absorption, and the underlying vibrational modes are strongly anharmonically coupled to each other. Recent two-dimensional IR (2D IR) experiments presented strong evidence for asymmetric Zundel-like motifs in solution, but true structure-spectrum correlations are missing and complicated by the anharmonicity of the system. In this study, we employ high-level vibrational self-consistent field/virtual state configuration interaction calculations to demonstrate that the 2D IR spectrum reports on a broad distribution of geometric configurations of the aqueous proton. We find that the diagonal 2D IR spectrum around 1200 cm-1 is dominated by the proton stretch vibrations of Zundel-like and intermediate geometries, broadened by the heterogeneity of aqueous configurations. There is a wide distribution of multidimensional potential shapes for the proton stretching vibration with varying degrees of potential asymmetry and confinement. Finally, we find specific cross peak patterns due to aqueous Zundel-like species. These studies provide clarity on highly debated spectral assignments and stringent spectroscopic benchmarks for future simulations.

Cryogenic Infrared Spectroscopy Reveals Structural Modularity in the Vibrational Fingerprints of Heparan Sulfate Diastereomers.

Heparan sulfate and heparin are highly acidic polysaccharides with a linear sequence, consisting of alternating glucosamine and hexuronic acid building blocks. The identity of hexuronic acid units shows a variability along their sequence, as d-glucuronic acid and its C5 epimer, l-iduronic acid, can both occur. The resulting backbone diversity represents a major challenge for an unambiguous structural assignment by mass spectrometry-based techniques. Here, we employ cryogenic infrared spectroscopy on mass-selected ions to overcome this challenge and distinguish isomeric heparan sulfate tetrasaccharides that differ only in the configuration of their hexuronic acid building blocks. High-resolution infrared spectra of a systematic set of synthetic heparan sulfate stereoisomers were recorded in the fingerprint region from 1000 to 1800 cm-1. The experiments reveal a characteristic combination of spectral features for each of the four diastereomers studied and imply structural modularity in the vibrational fingerprints. Strong spectrum-structure correlations were found and rationalized by state-of-the-art quantum chemical calculations. The findings demonstrate the potential of cryogenic infrared spectroscopy to extend the mass spectrometry-based toolkit for the sequencing of heparan sulfate and structurally related biomolecules.

Two-Dimensional Correlation Spectroscopy: The Power of Power Spectra.

Power spectra are a powerful tool provided by two-dimensional correlation analysis. However, this tool is seldom used in practice. This work shows selected examples of using of the power spectra for the study of various kinds of samples with the aim to promote more common use of this tool. By examination of the power spectrum of specific sample, one can estimate the sensitivity of different molecular fragments on a given perturbation. Determination of the power spectra for smaller data subsets provides information on the dynamics of perturbation-induced spectral changes. If the experimental spectra of different samples in the same perturbation window are recorded, the comparison of the power spectra yields information on differences in the sensitivity of various samples on common perturbation. This possibility is particularly useful for studies of the spectra-structure correlations, interactions, and molecular dynamics. A comparison of the power spectra obtained by using different reference spectra provides information on the nature of spectral changes at different wavenumbers.

Brilliant mid-infrared ellipsometry and polarimetry of thin films: Toward laboratory applications with laser based techniques

Tunable quantum cascade lasers (QCLs) have recently been introduced as mid-infrared (mid-IR) sources for spectroscopic ellipsometric and polarimetric setups. QCLs, with their unique properties with respect to coherence and brilliance in either pulsed or continuous-wave operation, are opening up numerous new possibilities for laboratory and industrial applications. In this review, the authors will focus on thin-film characterization techniques like ellipsometric and nanopolarimetric methods and summarize related state-of-the-art techniques in this rapidly developing field. These methods are highly relevant for optical, electronical, and biomedical applications and allow detailed structural analyses regarding band properties, spectra–structure correlations, and material anisotropy. Compared to classical Fourier-transform-IR spectroscopy, thin-film sensitivity can be achieved at high spectral and spatial resolution (<0.5 cm−1, <150 μm). Measurement times are reducible by several orders of magnitude into the millisecond and microsecond range with laser-based polarimetric setups involving modulation or single-shot concepts. Thus, mid-IR ellipsometric and polarimetric hyperspectral imaging can be performed on the time scale of minutes. For mid-IR ellipsometric imaging, thickness and structure information become simultaneously accessible at spatial resolutions of a few 100 μm and possibly even at the micrometer scale by the integration of microscopic concepts. With the atomic force microscopy-infrared spectroscopy based nanopolarimetric approach, anisotropy in the absorption properties can be investigated with lateral resolutions beyond the diffraction limit, reaching a few 10 nm.

Spectra-Structure Correlations in Isotopomers of Ethanol (CX3CX2OX; X = H, D): Combined Near-Infrared and Anharmonic Computational Study.

The effect of isotopic substitution on near-infrared (NIR) spectra has not been studied in detail. With an exception of few major bands, it is difficult to follow the spectral changes due to complexity of NIR spectra. Recent progress in anharmonic quantum mechanical calculations allows for accurate reconstruction of NIR spectra. Taking this opportunity, we carried out a systematic study of NIR spectra of six isotopomers of ethanol (CX3CX2OX; X = H, D). Besides, we calculated the theoretical spectra of two other isotopomers (CH3CD2OD and CD3CH2OD) for which the experimental spectra are not available. The anharmonic calculations were based on generalized vibrational second-order perturbation theory (GVPT2) at DFT and MP2 levels with several basis sets. We compared the accuracy and efficiency of various computational methods. It appears that the best results were obtained with B2PLYP-GD3BJ/def2-TZVP//CPCM approach. Our simulations included the first and second overtones, as well as binary and ternary combinations bands. This way, we reliably reproduced even minor bands in the spectra of diluted samples (0.1 M in CCl4). On this basis, the effect of isotopic substitution on NIR spectra of ethanol was accurately reproduced and comprehensively explained.

Study on the pathological and biomedical characteristics of spinal cord injury by confocal Raman microspectral imaging.

Confocal Raman microspectral imaging (CRMI) in combination with multivariate analysis was used to study pathological progression after spinal cord injury (SCI). By establishing moderate contusion in rat models, ex vivo longitudinal spinal cord tissue sections were prepared for microspectroscopic analysis. Comparative studies were then performed to determine the pathological distinctions among before injury (BI), one day post-injury (1 DPI), seven days post-injury (7 DPI), and 14 days post-injury (14 DPI) groups. Multivariate analysis algorithms, including K-mean cluster analysis (KCA) and principal component analysis (PCA), were conducted to highlight biochemical and structural variations after tissue damage. It is confirmed that typical spectral features and profiles can illustrate some fundamental and significant pathological processes post-injury, such as neuron apoptosis, hemorrhage, demyelination, and chondroitin sulfate proteoglycans (CSPGs) upregulation. Further, by establishing spectra-structure correlations, the reconstructed spectral images revealed some minute and important morphological characteristics following tissue injury, such as glial scar formation surrounding the cavity structure. The observed spectral phenomena also provide a detailed view on relevant pathobiological factors, which are involved in the spread of secondary damage after traumatic spinal cord injury. Our findings not only provide a spectral perspective to the well-known cellular mechanisms underlying SCI, but further provide a sound basis for developing real-time Raman methodologies to evaluate the prognostic factors and therapeutic results of SCI.

Unraveling the Structure-Raman Spectra Relationships in V2O5 Polymorphs via a Comprehensive Experimental and DFT Study.

Vanadium pentoxide polymorphs (α-, β-, γ'-, and ε'-V2O5) have been studied using the Raman spectroscopy and quantum-chemical calculations based on density functional theory. All crystal structures have been optimized by minimizing the total energy with respect to the lattice parameters and the positions of atoms in the unit cell. The structural optimization has been followed by the analysis of the phonon states in the Γ-point of the Brillouin zone, and the analysis has been completed by the computation of the Raman scattering intensities of the vibrational modes of the structures. The optimized structural characteristics compare well with the experimental data, and the calculated Raman spectra match the experimental ones remarkably well. With the good agreement between the spectra, a reliable assignment of the observed Raman peaks to the vibrations of specific structurals units in the V2O5 lattices is proposed. The obtained results support the viewpoint on the layered structure of vanadium pentoxide polymorphs as an ensemble of V2O5 chains held together by weaker interchain and interlayer interactions. Similarities and distinctions in the Raman spectra of the polymorphs have been highlighted, and the analysis of the experimental and computational data allows us, for the first time, to put forward spectrum-structure correlations for the four V2O5 structures. These findings are of the utmost importance for an efficient use of Raman spectroscopy to probe the changes at the atomic scale in the V2O5-based materials under electrochemical operation.

Characterization of the Action of Antibiotics and Essential Oils against Bacteria by Surface-Enhanced Raman Spectroscopy and Scanning Electron Microscopy

ABSTRACTThe description of the main structural alterations generated by the interaction between pathogenic microorganisms and antibiotic agents, either standard antibiotics or volatile plant derived oils, is an essential topic in understanding drug action mechanisms at the molecular level. To investigate this effect, an original approach based on ultrasensitive vibrational surface-enhanced Raman spectroscopy (SERS) and scanning electron microscopy (SEM) was used. Single-bacteria SERS spectra, recorded in the 600–1800 cm−1 wavenumber interval are reported for two bacterial strains: Enterococcus durans and Aeromonas media. Spectra-structure correlations for all types of localized vibrations, including bands assigned to proteins, saturated lipids, glycosidic linkages, and nitrogenous bases, are also discussed. SEM images revealed that the mechanism of action of antibiotic agents against the pathogenic microorganisms involves a complete denaturation of the bacterial membrane, which induces bacterial cells apoptosis.

Spectra-structure correlations in NIR region: Spectroscopic and anharmonic DFT study of n-hexanol, cyclohexanol and phenol

We investigated near-infrared (7500–4000 cm−1) spectra of n-hexanol, cyclohexanol and phenol in CCl4 (0.2 M) by using anharmonic quantum calculations. These molecules represent three major kinds of alcohols; linear and cyclic aliphatic, and aromatic ones. Vibrational second-order perturbation theory (VPT2) was employed to calculate the first overtones and binary combination modes and to reproduce the experimental NIR spectra. The level of conformational flexibility of these three alcohols varies from one stable conformer of phenol through four conformers of cyclohexanol to few hundreds conformers in the case of n-hexanol. To take into account the most relevant conformational population of n-hexanol, a systematic conformational search was performed. Accurate reproduction of the experimental NIR spectra was achieved and detailed spectra-structure correlations were obtained for these three alcohols. VPT2 approach provides less reliable description of highly anharmonic modes, i.e. OH stretching. In the present work this limitation was manifested in erroneous results yielded by VPT2 for 2νOH mode of cyclohexanol. To study the anharmonicity of this mode we solved the corresponding time-independent Schrödinger equation based on a dense-grid probing of the relevant vibrational potential. These results allowed for significant improvement of the agreement between the calculated and experimental 2νOH band of cyclohexanol. Various important biomolecules include similar structural units to the systems investigated here. A detailed knowledge on spectral properties of these three types of alcohols is therefore essential for advancing our understanding of NIR spectroscopy of biomolecules.

Revisiting empirical rules for the determination of the absolute configuration of cascarosides and other (ox‐)anthrones

The introduction of the C10 -stereocenter of (ox-)anthrones by plant organisms is not stereospecific. Consequently, often, both (10S)- and (10R)-diastereomers can be found in the same plant. Motivated by the importance of a correct assignment of the configuration at C10 , this study revisits the nuclear magnetic resonance and electronic circular dichroism-based empirical rules for the determination of the absolute configuration by molecular dynamic simulations and electronic circular dichroism spectrum calculations. Furthermore, a vibrational circular dichroism spectroscopic characterization of these large and conformationally very flexible molecules reveals spectral signatures, which can be used to specifically distinguish the C10 stereochemistry. A detailed analysis of the underlying vibrational modes suggests that the observed spectral pattern of the investigated cascarosides may be generally characteristic for the C10 -stereocenter of (ox-)anthrones and that they can be used for empirical spectra-structure correlations.

The Effect of Chain Length on Mid-Infrared and Near-Infrared Spectra of Aliphatic 1-Alcohols.

Effect of the chain length on mid-infrared (MIR) and near-infrared (NIR) spectra of aliphatic 1-alcohols from methanol to 1-decanol was examined in detail. Of particular interest were the spectra-structure correlations in the NIR region and the correlation between MIR and NIR spectra of 1-alcohols. An application of two-dimensional correlation analysis (2D-COS) and chemometric methods provided comprehensive information on spectral changes in the data set. Principal component analysis (PCA) and cluster analysis evidenced that the spectra of methanol, ethanol, and 1-propanol are noticeably different from the spectra of higher 1-alcohols. The similarity between the spectra increases with an increase in the chain length. Hence, the most similar are the spectra of 1-nonanol and 1-decanol. Two-dimensional hetero-correlation analysis is very helpful for identification of the origin of bands and may guide selection of the best spectral ranges for the chemometric analysis. As shown, normalization of the spectra pronounces the intensity changes in various spectral regions and provides information not accessible from the raw data. The spectra of alcohols cannot be represented as a sum of the CH3, CH2, and OH group spectra since the OH group is involved in the hydrogen bonding. As a result, the spectral changes of this group are nonlinear and its spectral profile cannot be properly resolved. Finally, this work provides a lot of evidence that the degree of self-association of 1-alcohols decreases with the increase in chain length because of the growing meaning of the hydrophobic interactions. For butyl alcohol and higher 1-alcohols the hydrophobic interactions are more important than the OH OH interactions. Therefore, methanol, ethanol, and 1-propanol have unlimited miscibility with water, whereas 1-butanol and higher 1-alcohols have limited miscibility with water.