Vibrational Fingerprints Research Articles

A graphene-metal hybrid biosensor for SEIRA spectroscopy applications

Detecting the building blocks of all living organisms plays a vital role in medical diagnosis and biological research. Infrared (IR) spectroscopy is one of the techniques for detecting biomolecules, such as DNA, RNA, and lipids, through their vibrational fingerprints. IR spectroscopy provides biosensing by directly measuring changes in absorption spectra; however, nanometric-size molecules reveal a weak signal-to-noise ratio with IR light, which is a disadvantage for sensitive bio-detection. Surface-Enhanced Infrared Spectroscopy (SEIRA) based on different structures and materials has been widely used to overcome this problem. In this study, a SEIRA platform based on a hybrid graphene-metal nanoantenna array is designed by combining the enhanced sensitivity of graphene with its electrical tunability and strong-field enhancement with metallic structures. The plasmonic resonance of graphene nano-slit is dynamically tuned to detect fingerprints of protein monolayer at different frequencies. The same detection behavior has been statically demonstrated by metallic antennas. Our results indicate that the sensitivity of the SEIRA sensor platform is quite high due to the combination of graphene and metal hybrid structure compared to the metal resonator alone because of the strong light confinement in the graphene layer. The proposed biosensor can detect the Amid-I and Amid-II bonds, which create relatively strong vibrational fingerprints, as well as the Amide-III bond, which is a very weak bond of a monolayer protein-goat-mouse Immunoglobulin (IgG) protein. It can also be a very useful characterization tool for identifying the molecular fingerprints of unknown chemicals and molecules with its capability to span a large spectral range either dynamically or statically. The strong light absorption via metallic structures compensates for the large areal coverage of graphene sheets, which is quite a challenge for dynamic tuning in real applications.

Exploring the Steps of Infrared (IR) Spectral Analysis: Pre-Processing, (Classical) Data Modelling, and Deep Learning.

Infrared (IR) spectroscopy has greatly improved the ability to study biomedical samples because IR spectroscopy measures how molecules interact with infrared light, providing a measurement of the vibrational states of the molecules. Therefore, the resulting IR spectrum provides a unique vibrational fingerprint of the sample. This characteristic makes IR spectroscopy an invaluable and versatile technology for detecting a wide variety of chemicals and is widely used in biological, chemical, and medical scenarios. These include, but are not limited to, micro-organism identification, clinical diagnosis, and explosive detection. However, IR spectroscopy is susceptible to various interfering factors such as scattering, reflection, and interference, which manifest themselves as baseline, band distortion, and intensity changes in the measured IR spectra. Combined with the absorption information of the molecules of interest, these interferences prevent direct data interpretation based on the Beer-Lambert law. Instead, more advanced data analysis approaches, particularly artificial intelligence (AI)-based algorithms, are required to remove the interfering contributions and, more importantly, to translate the spectral signals into high-level biological/chemical information. This leads to the tasks of spectral pre-processing and data modeling, the main topics of this review. In particular, we will discuss recent developments in both tasks from the perspectives of classical machine learning and deep learning.

A Smart Intracellular Self-Assembling Bioorthogonal Raman Active Nanoprobe for Targeted Tumor Imaging.

Inspired by the principle of in situ self-assembly, the development of enzyme-activated molecular nanoprobes can have a profound impact on targeted tumor detection. However, despite their intrinsic promise, obtaining an optical readout of enzyme activity with high specificity in native milieu has proven to be challenging. Here, a fundamentally new class of Raman-active self-assembling bioorthogonal enzyme recognition (nanoSABER) probes for targeted tumor imaging is reported. This class of Raman probes presents narrow spectral bands reflecting their vibrational fingerprints and offers an attractive solution for optical imaging at different bio-organization levels. The optical beacon harnesses an enzyme-responsive peptide sequence, unique tumor-penetrating properties, and vibrational tags with stretching frequencies in the cell-silent Raman window. The design of nanoSABER is tailored and engineered to transform into a supramolecular structure exhibiting distinct vibrational signatures in presence of target enzyme, creating a direct causality between enzyme activity and Raman signal. Through the integration of substrate-specific for tumor-associated enzyme legumain, unique capabilities of nanoSABER for imaging enzyme activity at molecular, cellular, and tissue levels in combination with machine learning models are shown. These results demonstrate that the nanoSABER probe may serve as a versatile platform for Raman-based recognition of tumor aggressiveness, drug accumulation, and therapeutic response.

Photoion Mass-Selected Threshold Photoelectron Spectroscopy to Detect Reactive Intermediates in Catalysis: From Instrumentation and Examples to Peculiarities and a Database.

Photoion mass-selected threshold photoelectron spectroscopy (ms-TPES) is a synchrotron-based, universal, sensitive, and multiplexed detection tool applied in the areas of catalysis, combustion, and gas-phase reactions. Isomer-selective vibrational fingerprints in the ms-TPES of stable and reactive intermediates allow for unequivocal assignment of spectral carriers. Case studies are presented on heterogeneous catalysis, revealing the role of ketenes in the methanol-to-olefins process, the catalytic pyrolysis mechanism of lignin model compounds, and the radical chemistry upon C-H activation in oxyhalogenation. These studies demonstrate the potential of ms-TPES as an analytical technique for elucidating complex reaction mechanisms. We examine the robustness of ms-TPES assignments and address sampling effects, especially the temperature dependence of ms-TPES due to rovibrational broadening. Data acquisition approaches and the Stark shift from the extraction field are also considered to arrive at general recommendations. Finally, the PhotoElectron PhotoIon Spectral Compendium (https://pepisco.psi.ch), a spectral database hosted at Paul Scherrer Institute to support assignment, is introduced.

Intrinsic SERS Fingerprints of Aptamer-Peptide Conjugates for Direct High-Specific Profiling Abnormal Protein Levels in Cancer Patients.

Surface-enhanced Raman spectroscopy (SERS) with ultrasensitive vibrational fingerprints enables quick identification and trace detection of various kinds of molecules. But proteins usually have low Raman cross sections and are difficult to generate recognizable signals in direct SERS detection. Recently, nucleic acid-peptide conjugates are emerging with great potential in structuring, assembling, catalyzing, sensing, etc., and the coupling of aptamers further enables superior biological recognition and programmability. Here, we develop the aptamer-peptide conjugates as a new kind of SERS probe for direct high-specific profiling abnormal protein levels in cancer patients. The aptamer conjugated with glutathione (GSH) functions as both the recognition element and the SERS reporters that can simultaneously generate SERS fingerprints of both peptides and nucleic acids. This kind of biocompatible probe appears to have excellent performance in high-salt environments and realizes rapid, simple, and multisignal detection of thrombin (TB). Data-driven soft independent modeling of class analogy (DD-SIMCA) is used to distinguish SERS profiles of actual blood samples and realize the identification and classification of cancer patients. Furthermore, the effect of low-temperature storage time on blood samples is analyzed by tracking the changes of SERS profiles; the results hint that plasma samples stored under 4 °C for more than 2 days could generate false negative results due to TB hydrolysis, which has important implications for clinical sample analysis. This kind of nucleic acid-peptide conjugate provides new ideas for SERS sensing strategy in the future.

Identifying the Structure of Supported Metal Catalysts Using Vibrational Fingerprints from Ab Initio Nanoscale Models (Small 34/2023)

Identifying the Structure of Supported Metal Catalysts Using Vibrational Fingerprints from Ab Initio Nanoscale Models (Small 34/2023)

A Review on Non-Noble Metal Substrates for Surface-Enhanced Raman Scattering Detection

Surface-enhanced Raman scattering (SERS), a powerful spectroscopic technique owing to its abundant vibrational fingerprints, has been widely employed for the assay of analytes. It is generally considered that one of the critical factors determining the SERS performance is the property of the substrate materials. Apart from noble metal substrates, non-noble metal nanostructured materials, as emerging new substrates, have been extensively studied for SERS research by virtue of their superior biocompatibility, good chemical stability, outstanding selectivity, and unique physicochemical properties such as adjustable band structure and carrier concentration. Herein, in this review, we summarized the research on the analytical application of non-noble metal SERS substrates from three aspects. Firstly, we started with an introduction to the possible enhancement mechanism of non-noble metal substrates. Then, as a guideline for substrates design, several main types of materials, including carbon nanomaterials, transition metal dichalcogenides (TMDs), metal oxides, metal-organic frameworks (MOFs), transition metal carbides and nitrides (MXenes), and conjugated polymers were discussed. Finally, we especially emphasized their analytical application, such as the detection of pollutants and biomarkers. Moreover, the challenges and attractive research prospects of non-noble metal SERS substrates in practical application were proposed. This work may arouse more awareness of the practical application of the non-noble metal material-based SERS substrates, especially for bioanalysis.

Evaluation of Multivariate Filters on Vibrational Spectroscopic Fingerprints for the PLS-DA and SIMCA Classification of Argan Oils from Four Moroccan Regions.

This study aimed to develop an analytical method to determine the geographical origin of Moroccan Argan oil through near-infrared (NIR) or mid-infrared (MIR) spectroscopic fingerprints. However, the classification may be problematic due to the spectral similarity of the components in the samples. Therefore, unsupervised and supervised classification methods-including principal component analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Soft Independent Modeling of Class Analogy (SIMCA)-were evaluated to distinguish between Argan oils from four regions. The spectra of 93 samples were acquired and preprocessed using both standard preprocessing methods and multivariate filters, such as External Parameter Orthogonalization, Generalized Least Squares Weighting and Orthogonal Signal Correction, to improve the models. Their accuracy, precision, sensitivity, and selectivity were used to evaluate the performance of the models. SIMCA and PLS-DA models generated after standard preprocessing failed to correctly classify all samples. However, successful models were produced after using multivariate filters. The NIR and MIR classification models show an equivalent accuracy. The PLS-DA models outperformed the SIMCA with 100% accuracy, specificity, sensitivity and precision. In conclusion, the studied multivariate filters are applicable on the spectroscopic fingerprints to geographically identify the Argan oils in routine monitoring, significantly reducing analysis costs and time.

Atomic-Scale Insights into the Interlayer Characteristics and Oxygen Reactivity of Bilayer Borophene.

Bilayer (BL) two-dimensional boron (i.e., borophene) has recently been synthesized and computationally predicted to have promising physical properties for a variety of electronic and energy technologies. However, the fundamental chemical properties of BL borophene that form the foundation of practical applications remain unexplored. Here, we present atomic-level chemical characterization of BL borophene using ultrahigh vacuum tip-enhanced Raman spectroscopy (UHV-TERS). UHV-TERS identifies the vibrational fingerprint of BL borophene with angstrom-scale spatial resolution. The observed Raman spectra are directly correlated with the vibrations of interlayer boron-boron bonds, validating the three-dimensional lattice geometry of BL borophene. By virtue of the single-bond sensitivity of UHV-TERS to oxygen adatoms, we demonstrate the enhanced chemical stability of BL borophene compared to its monolayer counterpart by exposure to controlled oxidizing atmospheres in UHV. In addition to providing fundamental chemical insight into BL borophene, this work establishes UHV-TERS as a powerful tool to probe interlayer bonding and surface reactivity of low-dimensional materials at the atomic scale.

Atomic‐Scale Insights into the Interlayer Characteristics and Oxygen Reactivity of Bilayer Borophene

AbstractBilayer (BL) two‐dimensional boron (i.e., borophene) has recently been synthesized and computationally predicted to have promising physical properties for a variety of electronic and energy technologies. However, the fundamental chemical properties of BL borophene that form the foundation of practical applications remain unexplored. Here, we present atomic‐level chemical characterization of BL borophene using ultrahigh vacuum tip‐enhanced Raman spectroscopy (UHV‐TERS). UHV‐TERS identifies the vibrational fingerprint of BL borophene with angstrom‐scale spatial resolution. The observed Raman spectra are directly correlated with the vibrations of interlayer boron–boron bonds, validating the three‐dimensional lattice geometry of BL borophene. By virtue of the single‐bond sensitivity of UHV‐TERS to oxygen adatoms, we demonstrate the enhanced chemical stability of BL borophene compared to its monolayer counterpart by exposure to controlled oxidizing atmospheres in UHV. In addition to providing fundamental chemical insight into BL borophene, this work establishes UHV‐TERS as a powerful tool to probe interlayer bonding and surface reactivity of low‐dimensional materials at the atomic scale.

Infrared action spectroscopy as tool for probing gas-phase dynamics: protonated dimethyl ether, (CH3)2OH+, formed by the reaction of CH3OH2 + with CH3OH

Methanol is one of the most abundant interstellar Complex Organic Molecules (iCOMs) and represents a major building block for the synthesis of increasingly complex oxygen-containing molecules. The reaction between protonated methanol and its neutral counterpart, giving protonated dimethyl ether, ( CH 3 ) 2 OH + , along with the ejection of a water molecule, has been proposed as a key reaction in the synthesis of dimethyl ether in space. Here, gas phase vibrational spectra of the ( CH 3 ) 2 OH + reaction product and the [ C 2 H 9 O 2 ] + intermediate complex(es), formed under different pressure and temperature conditions, are presented. The widely tunable free electron laser for infrared experiments, FELIX, was employed to record these vibrational fingerprint spectra using different types of infrared action spectroscopy in the 600-1700 cm − 1 frequency range, complemented with measurements using an OPO/OPA system to cover the O − H stretching region 3400 − 3700 c m − 1 . The formation of protonated dimethyl ether as a product of the reaction is spectroscopically confirmed, providing the first gas-phase vibrational spectrum of this potentially relevant astrochemical ion.

FTIR spectroscopy-based lipochemical fingerprints involved in pomegranate response to water stress

Pomegranate trees are known for their ability to withstand drought conditions, but there is still much to learn about how water stress affects the lipobiochemical behavior of their seeds. This study aimed to investigate how sustained deficit irrigation (SDI-50), equivalent to 50% of crop evapotranspiration, influences pomegranate seed oil attributes such as phenols, flavonoids, and tannins content, and the seeds’ lipochemical fingerprints compared to fully irrigated trees. At the full ripening stage, pomegranate seeds were analyzed for their oil content, biochemical traits, and vibrational fingerprints using infrared radiation. The results indicated that there was a significant genotypic effect coupled with applied water stress on all the investigated traits. Interestingly, an increasing trend in seed oil yield was observed under water stress conditions compared to the control, with the highest oil yield increase observed in the ‘Zheri Precoce’ fruit seeds. Only two cultivars did not show the same pattern, with the oil yield increase ranging from 8% to 100%. Furthermore, SDI-50 induced a substantial increase in total phenolic content, coupled with a significant genotypic effect, and resulted in an average increase of 7.5%. This increase in total phenolics also correlated with an increase in antioxidant activity across all investigated cultivars. ATR-FTIR fingerprinting revealed eleven spectral fingerprints corresponding to functional groups present in pomegranate seeds oil, with a particular pattern of significant effects of both genotypic and SDI-50 factors. These results suggest that exploiting water scarcity conditions could be a viable approach to improve the quantitative and qualitative attributes of pomegranate seed oil. While there are still several aspects to be investigated further, this study provides a basis for pomegranate processing under water shortage conditions.

Identifying the Structure of Supported Metal Catalysts Using Vibrational Fingerprints from Ab Initio Nanoscale Models.

Identifying active sites of supported noble metal nanocatalysts remains challenging, since their size and shape undergo changes depending on the support, temperature, and gas mixture composition. Herein, the anharmonic infrared spectrum of adsorbed CO is simulated using density functional theory (DFT) to gain insight into the nature of Pd nanoparticles (NPs) supported on ceria. The authors systematically determine how the simulated infrared spectra are affected by CO coverage, NP size (0.5-1.5nm), NP morphology (octahedral, icosahedral), and metal-support contact angle, by exploring a diversity of realistic models inspired by ab initio molecular dynamics. The simulated spectra are then used as a spectroscopic fingerprint to characterize nanoparticles in a real catalyst, by comparison with in-situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) experiments. Truncated octahedral NPs with an acute Pd-ceria angle reproduce most of the measurements. In particular, the authors isolate features characteristic of CO adsorbed at the metal-support interface appearing at low frequencies, both seen in simulation and experiment. This work illustrates the strong need for realistic models to provide a robust description of the active sites, especially at the interface of supported metal nanocatalysts, which can be highly dynamic and evolve considerably during reaction.

Stretchable and Flexible Micro-Nano Substrates for SERS Detection of Organic Dyes.

Surface-enhanced Raman spectroscopy (SERS) is a precise and noninvasive analytical technique to identify vibrational fingerprints of trace analytes with sensitivity down to the single-molecule level. However, substrates can influence this capability, and current SERS techniques lack uniform, reproducible, and stable substrates to control plasma hot spots over a wide spectral range. Herein, we demonstrate a flexible SERS substrate via longitudinal stretching of a polydimethylsiloxane (PDMS) film. This substrate, after stretching and shrinking, exhibits an irregular wrinkled structure with abundant gaps and grooves that function as hot spots, thereby improving the hydrophobic properties of the material. To investigate the enhancement effect of Raman signals, silver nanoparticles (AgNPs) were mixed with Rhodamine 6G (R6G) solution, and the obtained blend was dropped onto the PDMS film to form a coffee ring pattern. According to the results, the hydrophobicity of the substrate increases with the degree of PDMS stretching, achieving the optimal level at 150% stretching. Moreover, the increase in hydrophobicity makes the measured molecules more aggregated, which enhances the Raman signal. The stretching and shrinkage of the PDMS film lead to a much higher density of nanogaps among nanoparticles and nanogrooves, which serve as multiple hot spots. Being highly localized regions of intense local fields, these hot spots make a significant contribution to SERS performance, improving the sensitivity and reproducibility of the method. In particular, the relative standard deviation (RSD) was found to be 2.5544%, and the detection limit was 1 × 10-7 M. Therefore, SERS using stretchable and flexible micro-nano substrates is a promising way for detecting dyes in wastewater.

Macrocyclic Compounds: Metal Oxide Particles Nanocomposite Thin Films Deposited by MAPLE.

Nanocomposite films based on macrocyclic compounds (zinc phthalocyanine (ZnPc) and 5,10,15,20-tetra(4-pyridyl) 21H,23H-porphyrin (TPyP)) and metal oxide nanoparticles (ZnO or CuO) were deposited by matrix-assisted pulsed laser evaporation (MAPLE). 1,4-dioxane was used as a solvent in the preparation of MAPLE targets that favor the deposition of films with a low roughness, which is a key feature for their integration in structures for optoelectronic applications. The influence of the addition of ZnO nanoparticles (~20 nm in size) or CuO nanoparticles (~5 nm in size) in the ZnPc:TPyP mixture and the impact of the added metal oxide amount on the properties of the obtained composite films were evaluated in comparison to a reference layer based only on an organic blend. Thus, in the case of nanocomposite films, the vibrational fingerprints of both organic compounds were identified in the infrared spectra, their specific strong absorption bands were observed in the UV-Vis spectra, and a quenching of the TPyP emission band was visible in the photoluminescence spectra. The morphological analysis evidenced agglomerated particles on the composite film surface, but their presence has no significant impact on the roughness of the MAPLE deposited layers. The current density-voltage (J-V) characteristics of the structures based on the nanocomposite films deposited by MAPLE revealed the critical role played by the layer composition and component ratio, an improvement in the electrical parameters values being achieved only for the films with a certain type and optimum amount of metal oxide nanoparticles.

Recent State and Challenges in Spectroelectrochemistry with Its Applications in Microfluidics.

This review paper presents the recent developments in spectroelectrochemical (SEC) technologies. The coupling of spectroscopy and electrochemistry enables SEC to do a detailed and comprehensive study of the electron transfer kinetics and vibrational spectroscopic fingerprint of analytes during electrochemical reactions. Though SEC is a promising technique, the usage of SEC techniques is still limited. Therefore, enough publicity for SEC is required, considering the promising potential in the analysis fields. Unlike previously published review papers primarily focused on the relatively frequently used SEC techniques (ultraviolet-visible SEC and surface-enhanced Raman spectroscopy SEC), the two not-frequently used but promising techniques (nuclear magnetic resonance SEC and dark-field microscopy SEC) have also been studied in detail. This review paper not only focuses on the applications of each SEC method but also details their primary working mechanism. In short, this paper summarizes each SEC technique's working principles, current applications, challenges encountered, and future development directions. In addition, each SEC technique's applicative research directions are detailed and compared in this review work. Furthermore, integrating SEC techniques into microfluidics is becoming a trend in minimized analysis devices. Therefore, the usage of SEC techniques in microfluidics is discussed.

Hypervirulent R20291 Clostridioides difficile spores show disinfection resilience to sodium hypochlorite despite structural changes

BackgroundClostridioides difficile is a spore forming bacterial species and the major causative agent of nosocomial gastrointestinal infections. C. difficile spores are highly resilient to disinfection methods and to prevent infection, common cleaning protocols use sodium hypochlorite solutions to decontaminate hospital surfaces and equipment. However, there is a balance between minimising the use of harmful chemicals to the environment and patients as well as the need to eliminate spores, which can have varying resistance properties between strains. In this work, we employ TEM imaging and Raman spectroscopy to analyse changes in spore physiology in response to sodium hypochlorite. We characterize different C. difficile clinical isolates and assess the chemical’s impact on spores’ biochemical composition. Changes in the biochemical composition can, in turn, change spores’ vibrational spectroscopic fingerprints, which can impact the possibility of detecting spores in a hospital using Raman based methods.ResultsWe found that the isolates show significantly different susceptibility to hypochlorite, with the R20291 strain, in particular, showing less than 1 log reduction in viability for a 0.5% hypochlorite treatment, far below typically reported values for C. difficile. While TEM and Raman spectra analysis of hypochlorite-treated spores revealed that some hypochlorite-exposed spores remained intact and not distinguishable from controls, most spores showed structural changes. These changes were prominent in B. thuringiensis spores than C. difficile spores.ConclusionThis study highlights the ability of certain C. difficile spores to survive practical disinfection exposure and the related changes in spore Raman spectra that can be seen after exposure. These findings are important to consider when designing practical disinfection protocols and vibrational-based detection methods to avoid a false-positive response when screening decontaminated areas.Graphical

Mid‐infrared dual‐comb polarimetry of anisotropic samples

AbstractThe mid‐infrared (mid‐IR) anisotropic optical response of a material probes vibrational fingerprints and absorption bands sensitive to order, structure, and direction‐dependent stimuli. Such anisotropic properties play a fundamental role in catalysis, optoelectronic, photonic, polymer and biomedical research and applications. Infrared dual‐comb polarimetry (IR‐DCP) is introduced as a powerful new spectroscopic method for the analysis of complex dielectric functions and anisotropic samples in the mid‐IR range. IR‐DCP enables novel hyperspectral and time‐resolved applications far beyond the technical possibilities of classical Fourier‐transform IR approaches. The method unravels structure–spectra relations at high spectral bandwidth up to 90 cm−1 and short integration times of 65 μs, with previously unattainable time resolutions for spectral IR polarimetric measurements for potential studies of noncyclic and irreversible processes. The polarimetric capabilities of IR‐DCP are demonstrated by investigating an anisotropic inhomogeneous freestanding nanofiber scaffold for neural tissue applications. Polarization sensitive multi‐angle dual‐comb transmission amplitude and absolute phase measurements (separately for ss‐, pp‐, ps‐, and sp‐polarized light) allow the in‐depth probing of the samples’ orientation‐dependent vibrational absorption properties. Mid‐IR anisotropies can quickly be identified by cross‐polarized IR‐DCP polarimetry.Key points A novel dual‐comb laser‐based technique is established for polarization‐dependent mid‐infrared spectroscopy. Independent measurements of spectral s‐ and p‐polarized transmission amplitudes and phases in the μs range. Visualization of the anisotropy of nanofiber scaffolds as used for neural tissue applications.

Label-free SERS ultrasensitive and universal detection of low back pain fingerprint based on SERS substrate.

Low back pain (LBP) seriously endangers human health and quality of life, and the detection of thoracolumbar fasciitis (TLF) is vital for the prevention and treatment of LBP. Surface-enhanced Raman scattering (SERS) is considered as a powerful technique for fingerprint detection due to the inherent richness of the spectral data. In this work, a novel SERS strategy based on a three-dimensional substrate was developed for fingerprint analysis for early diagnosis of TLF. A rat TLF model was established and the model was evaluated from the immunological and behavioral perspectives. Vibrational fingerprints were obtained by SERS testing of isolated fascial tissue and were used to explore the material changes during fasciitis. SERS spectra were analyzed using principal component analysis (PCA) that allowed unambiguous distinction and monitoring of component changes during TLF. Furthermore, in order to further clarify the occurrence and development of TLF, we combined clinical samples for analysis, and investigated the inflammatory factor expression levels of CRP and SAA in TLF. Our results demonstrated that tryptophan, phenylalanine and glycogen could unambiguously distinguish TLF as confirmed by SERS analysis, a method that is capable of noninvasive characterization of and diagnosis of TLF during LBP. We have provided a new tool that may promote in-depth study of the mechanism and treatment of fasciitis.

Fingerprinting fragments of fragile interstellar molecules: dissociation chemistry of pyridine and benzonitrile revealed by infrared spectroscopy and theory.

The cationic fragmentation products in the dissociative ionization of pyridine and benzonitrile have been studied by infrared action spectroscopy in a cryogenic ion trap instrument at the Free-Electron Lasers for Infrared eXperiments (FELIX) Laboratory. A comparison of the experimental vibrational fingerprints of the dominant cationic fragments with those from quantum chemical calculations revealed a diversity of molecular fragment structures. The loss of HCN/HNC is shown to be the major fragmentation channel for both pyridine and benzonitrile. Using the determined structures of the cationic fragments, potential energy surfaces have been calculated to elucidate the nature of the neutral fragment partner. In the fragmentation chemistry of pyridine, multiple non-cyclic structures are formed, whereas the fragmentation of benzonitrile dominantly leads to the formation of cyclic structures. Among the fragments are linear cyano-(di)acetylene˙+, methylene-cyclopropene˙+ and o- and m-benzyne˙+ structures, the latter possible building blocks in interstellar polycyclic aromatic hydrocarbon (PAH) formation chemistry. Molecular dynamics simulations using density functional based tight binding (MD/DFTB) were performed and used to benchmark and elucidate the different fragmentation pathways based on the experimentally determined structures. The implications of the difference in fragments observed for pyridine and benzonitrile are discussed in an astrochemical context.