Complementary vibrational spectroscopy

Symmetric Non-Monochromatic Light as Reference in Fourier Transform Spectrometers

Fourier transform spectrometers typically use a presumed monochromatic reference source to track and correct errors in optical path difference changes. This paper will conduct a theoretical analysis to show that non-monochromatic light sources with symmetric spectral profiles can also be used as reference sources without adding errors. An experiment was carried out using a symmetric broadband superluminescent diode (SLED) as reference light to measure the spectrum of some other SLED light sources to experimentally demonstrate this finding.

Hyper-Raman spectroscopy of non-proteinogenic amino acids

We report 532-nm and 1064-nm excited hyper-Raman (HR) spectra of representative non-proteinogenic amino acids, including α-, β-, and γ-amino acids. Different from the common 20 proteinogenic amino acids, natural non-proteinogenic amino acids cannot be incorporated into proteins during translation, while they are indispensable as intermediates in many processes like biosynthesis and neurotransmitters. In 532-nm excited HR spectra, the COO─ symmetric stretching bands are commonly intense, and the NH3+ bands are clearly observable. In addition, based on the reported IR and Raman study, we found that some HR bands are IR-active but Raman-inactive. In contrast, HR signals with the 1064-nm excitation are much weaker than the 532-nm excitation. Nevertheless, we observed the COO─ scissoring band unexpectedly, much stronger than other bands with the 1064-nm excitation. Our results suggest that the electronic resonance effect plays a role in enabling us to detect HR signals in the UV region readily. We expect that this study provides a supplementary reference for HR spectroscopy of natural amino acids.

INSPIRE: Single-beam probed complementary vibrational bioimaging

Molecular spectroscopy provides intrinsic contrast for in situ chemical imaging, linking the physiochemical properties of biomolecules to the functions of living systems. While stimulated Raman imaging has found successes in deciphering biological machinery, many vibrational modes are Raman inactive or weak, limiting the broader impact of the technique. It can potentially be mitigated by the spectral complementarity from infrared (IR) spectroscopy. However, the vastly different optical windows make it challenging to develop such a platform. Here, we introduce in situ pump-probe IR and Raman excitation (INSPIRE) microscopy, a nascent cross-modality spectroscopic imaging approach by encoding the ultrafast Raman and the IR photothermal relaxation into a single probe beam for simultaneous detection. INSPIRE inherits the merits of complementary modalities and demonstrates high-content molecular imaging of chemicals, cells, tissues, and organisms. Furthermore, INSPIRE applies to label-free and molecular tag imaging, offering possibilities for optical sensing and imaging in biomedicine and materials science.

Fourier Transform Coherent Anti-Stokes Raman Scattering Spectroscopy: A Comprehensive Review

Fourier transform coherent anti-Stokes Raman scattering (FT-CARS) spectroscopy is a powerful spectroscopic method that combines the principles of Fourier transform spectroscopy with coherent anti-Stokes Raman scattering (CARS). This method stands out in spectroscopy for its ability to rapidly acquire coherent Raman spectra, achieving an impressive rate of over 10 000 spectra per second. The method involves scanning the optical delay between two femtosecond pulses; the initial pulse induces a vibrational coherence in the sample, while the subsequent pulse probes this coherence over increasing delays. The anti-Stokes scattering intensity generated is modulated by the vibrational dynamics of the sample, enabling the retrieval of Raman spectra through Fourier transformation. Over the past two decades, FT-CARS spectroscopy has undergone substantial evolution, paving the way for its application in a wide array of fields, including material analysis and flow cytometry. In this comprehensive Review, we explore the fundamental principles and diverse applications of FT-CARS spectroscopy and delve into the potential future advances and challenges associated with this emerging method.

A tutorial on optical photothermal infrared (O-PTIR) microscopy

This tutorial reviews the rapidly growing field of optical photothermal infrared (O-PTIR) spectroscopy and chemical imaging. O-PTIR is an infrared super-resolution measurement technique where a shorter wavelength visible probe is used to measure and map infrared (IR) absorption with spatial resolution up to 30× better than conventional techniques such as Fourier transform infrared and direct IR laser imaging systems. This article reviews key limitations of conventional IR instruments, the O-PTIR technology breakthroughs, and their origins that have overcome the prior limitations. This article also discusses recent developments in expanding multi-modal O-PTIR approaches that enable complementary Raman spectroscopy and fluorescence microscopy imaging, including wide-field O-PTIR imaging with fluorescence-based detection of IR absorption. Various practical subjects are covered, including sample preparation techniques, optimal measurement configurations, use of IR tags/labels and techniques for data analysis, and visualization. Key O-PTIR applications are reviewed in many areas, including biological and biomedical sciences, environmental and microplastics research, (bio)pharmaceuticals, materials science, cultural heritage, forensics, photonics, and failure analysis.

Vacancy-Driven High-Performance Metabolic Assay for Diagnosis and Therapeutic Evaluation of Depression

Depression is one of the most common mental illnesses and is a well-known risk factor for suicide, characterized by low overall efficacy (<50%) and high relapse rate (40%). A rapid and objective approach for screening and prognosis of depression is highly desirable but still awaits further development. Herein, a high-performance metabolite-based assay to aid the diagnosis and therapeutic evaluation of depression by developing a vacancy-engineered cobalt oxide (Vo-Co3O4) assisted laser desorption/ionization mass spectrometer platform is presented. The easy-prepared nanoparticles with optimal vacancy achieve a considerable signal enhancement, characterized by favorable charge transfer and increased photothermal conversion. The optimized Vo-Co3O4 allows for a direct and robust record of plasma metabolic fingerprints (PMFs). Through machine learning of PMFs, high-performance depression diagnosis is achieved, with the areas under the curve (AUC) of 0.941-0.980 and an accuracy of over 92%. Furthermore, a simplified diagnostic panel for depression is established, with a desirable AUC value of 0.933. Finally, proline levels are quantified in a follow-up cohort of depressive patients, highlighting the potential of metabolite quantification in the therapeutic evaluation of depression. This work promotes the progression of advanced matrixes and brings insights into the management of depression.

Fluorescence in depth: integration of spectroscopy and imaging with Raman, IR, and CD for advanced research

Fluorescence spectroscopy serves as a vital technique for studying the interaction between light and fluorescent molecules. It encompasses a range of methods, each presenting unique advantages and applications. This technique finds utility in various chemical studies. This review discusses Fluorescence spectroscopy, its branches such as Time-Resolved Fluorescence Spectroscopy (TRFS) and Fluorescence Lifetime Imaging Microscopy (FLIM), and their integration with other spectroscopic methods, including Raman, Infrared (IR), and Circular Dichroism (CD) spectroscopies. By delving into these methods, we aim to provide a comprehensive understanding of the capabilities and significance of fluorescence spectroscopy in scientific research, highlighting its diverse applications and the enhanced understanding it brings when combined with other spectroscopic methods. This review looks at each technique's unique features and applications. It discusses the prospects of their combined use in advancing scientific understanding and applications across various domains.

Molecular Design Using Selected Concentration Effects in Optically Activated Fluorescent Matrices

Molecular physics plays a pivotal role in various fields, including medicine, pharmaceuticals, and broader industrial applications. This study aims to enhance the methods for producing specific optically active materials with distinct spectroscopic properties at the molecular level, which are crucial for these sectors, while prioritizing human safety in both production and application. Forensic science, a significant socio-economic field, often employs hazardous substances in analyzing friction ridges on porous surfaces, posing safety concerns. In response, we formulated novel, non-toxic procedures for examining paper evidence, particularly thermal papers. Our laboratory model utilizes a polyvinyl alcohol polymer as a rigid matrix to emulate the thermal paper's environment, enabling precise control over the spectroscopic characteristics of 1,8-diazafluoro-9-one (DFO). We identified and analyzed the cyclodimer 1,8-diazafluoren-9-one (DAK DFO), which is a non-toxic and biocompatible alternative for revealing forensic marks. The reagents used to preserve fingerprints were optimized for their effectiveness and stability. Using stationary absorption and emission spectroscopy, along with time-resolved emission studies, we verified the spectroscopic attributes of the new structures under deliberate aggregation conditions. Raman spectroscopy and quantum mechanical computations substantiated the cyclodimer's configuration. The investigation provides robust scientific endorsement for the novel compound and its structural diversity, influenced by the solvatochromic sensitivity of the DFO precursor. Our approach to monitoring aggregation processes signifies a substantial shift in synthetic research paradigms, leveraging simple chemistry to yield an innovative contribution to forensic science methodologies.

Multimodal fiber probe for simultaneous mid-infrared and Raman spectroscopy

A fiber probe has been developed that enables simultaneous acquisition of mid-infrared (MIR) and Raman spectra in the region of 3100-2600 cm-1. Multimodal measurement is based on a proposed ZrO2 crystal design at the tip of an attenuated total reflection (ATR) probe. Mid-infrared ATR spectra are obtained through a pair of chalcogenide infrared (CIR) fibers mounted at the base of the crystal. The probe enables both excitation and acquisition of a weak Raman signal from a portion of the sample in front of the crystal using an additional pair of silica fibers located in a plane perpendicular to the CIR fibers. The advantages of combining MIR and Raman spectra in a single probe have been discussed.

Wide-field mid-infrared hyperspectral imaging beyond video rate

Mid-infrared hyperspectral imaging has become an indispensable tool to spatially resolve chemical information in a wide variety of samples. However, acquiring three-dimensional data cubes is typically time-consuming due to the limited speed of raster scanning or wavelength tuning, which impedes real-time visualization with high spatial definition across broad spectral bands. Here, we devise and implement a high-speed, wide-field mid-infrared hyperspectral imaging system relying on broadband parametric upconversion of high-brightness supercontinuum illumination at the Fourier plane. The upconverted replica is spectrally decomposed by a rapid acousto-optic tunable filter, which records high-definition monochromatic images at a frame rate of 10 kHz based on a megapixel silicon camera. Consequently, the hyperspectral imager allows us to acquire 100 spectral bands over 2600-4085 cm-1 in 10 ms, corresponding to a refreshing rate of 100 Hz. Moreover, the angular dependence of phase matching in the image upconversion is leveraged to realize snapshot operation with spatial multiplexing for multiple spectral channels, which may further boost the spectral imaging rate. The high acquisition rate, wide-field operation, and broadband spectral coverage could open new possibilities for high-throughput characterization of transient processes in material and life sciences.

Infrared to terahertz identification of chemical substances used for the production of IEDs

In our modern times, improvised explosive devices (IEDs) have become more sophisticated than ever, capable of causing destruction and loss of life. The creative use of homemade substances for IEDs manufactures has led to efforts in developing sensitive detection methods that can anticipate, identify and protect against improvised attacks. Laser-based spectroscopic techniques provide rapid and accurate detection of chemicals in improvised explosives, but no single method can detect all components of all explosives. In this study, two spectroscopic methods are used for the sensitive identification of 8 explosive chemical substances in the form of powders and vapors. Absorption spectra of benzene, toluene, acetone and ethylene glycol were examined with CO2 laser photoacoustic spectroscopy. The photoacoustic signals of the samples were recorded in the CO2 laser emission range from 9.2 to 10.8 µm and a different spectral behavior was observed for each analyzed substance. Time-domain spectroscopy with THz radiation was used to analyze ammonium nitrate, potassium chlorate, dinitrobenzene, hexamethylenetetramine transmission spectra in the 0.1-3 THz range, and it was observed that they have characteristic THz fingerprint spectra. CO2 laser photoacoustic spectroscopy and THz time domain spectroscopy have met the criterion of proven effectiveness in identifying explosive components. The combination of these spectroscopic methods is innovative, giving a promising new approach for detection of a large number of IED components.

Nondestructive and Rapid Screening of Aflatoxin-Contaminated Single Peanut Kernels Using Field-Portable Spectroscopy Instruments (FT-IR and Raman)

A nondestructive and rapid classification approach was developed for identifying aflatoxin-contaminated single peanut kernels using field-portable vibrational spectroscopy instruments (FT-IR and Raman). Single peanut kernels were either spiked with an aflatoxin solution (30 ppb-400 ppb) or hexane (control), and their spectra were collected via Raman and FT-IR. An uHPLC-MS/MS approach was used to verify the spiking accuracy via determining actual aflatoxin content on the surface of randomly selected peanut samples. Supervised classification using soft independent modeling of class analogies (SIMCA) showed better discrimination between aflatoxin-contaminated (30 ppb-400 ppb) and control peanuts with FT-IR compared with Raman, predicting the external validation samples with 100% accuracy. The accuracy, sensitivity, and specificity of SIMCA models generated with the portable FT-IR device outperformed the methods in other destructive studies reported in the literature, using a variety of vibrational spectroscopy benchtop systems. The discriminating power analysis showed that the bands corresponded to the C=C stretching vibrations of the ring structures of aflatoxins were most significant in explaining the variance in the model, which were also reported for Aspergillus-infected brown rice samples. Field-deployable vibrational spectroscopy devices can enable in situ identification of aflatoxin-contaminated peanuts to assure regulatory compliance as well as cost savings in the production of peanut products.

Towards a point-of-care multimodal spectroscopy instrument for the evaluation of human cardiac tissue

To demonstrate that point-of-care multimodal spectroscopy using Near-Infrared (NIR) and Raman Spectroscopy (RS) can be used to diagnose human heart tissue. We generated 105 spectroscopic scans, which comprised 4 NIR and 3 RS scans per sample to generate a "multimodal spectroscopic scan" (MSS) for each heart, done across 15 patients, 5 each from the dilated cardiomyopathy (DCM), Ischaemic Heart Disease (IHD) and Normal pathologies. Each of the MSS scans was undertaken in 3 s. Data were entered into machine learning (ML) algorithms to assess accuracy of MSS in diagnosing tissue type. The median age was 50 years (IQR 49-52) for IHD, 47 (IQR 45-50) for DCM and 36 (IQR 33-52) for healthy patients (p = 0.35), 60% of which were male. MSS identified key differences in IHD, DCM and normal heart samples in regions typically associated with fibrosis and collagen (NIR wavenumbers: 1433, 1509, 1581, 1689 and 1725 nm; RS wavelengths: 1658, 1450 and 1330 cm-1). In principal component (PC) analyses, these differences explained 99.2% of the variation in 4 PCs for NIR, 81.6% in 10 PCs for Raman, and 99.0% in 26 PCs for multimodal spectroscopic signatures. Using a stack machine learning algorithm with combined NIR and Raman data, our model had a precision of 96.9%, recall of 96.6%, specificity of 98.2% and Area Under Curve (AUC) of 0.989 (Table 1). NIR and Raman modalities alone had similar levels of precision at 94.4% and 89.8% respectively (Table 1). MSS combined with ML showed accuracy of 90% for detecting dilated cardiomyopathy, 100% for ischaemic heart disease and 100% for diagnosing healthy tissue. Multimodal spectroscopic signatures, based on NIR and Raman spectroscopy, could provide cardiac tissue scans in 3-s to aid accurate diagnoses of fibrosis in IHD, DCM and normal hearts. Table 1 Machine learning performance metrics for validation data sets of (a) Near-Infrared (NIR), (b) Raman and (c and d) multimodal data using logistic regression (LR), stochastic gradient descent (SGD) and support vector machines (SVM), with combined "stack" (LR + SGD + SVM) AUC Precision Recall Specificity (a) NIR model  Logistic regression 0.980 0.944 0.933 0.967  SGD 0.550 0.281 0.400 0.700  SVM 0.840 0.806 0.800 0.900  Stack 0.933 0.794 0.800 0.900 (b) Raman model  Logistic regression 0.985 0.940 0.929 0.960  SGD 0.892 0.869 0.857 0.932  SVM 0.992 0.940 0.929 0.960  Stack 0.954 0.869 0.857 0.932 (c) MSS: multimodal (NIR + Raman) to detect DCM vs. IHD vs. normal patients  Logistic regression 0.975 0.841 0.828 0.917  SGD 0.847 0.803 0.793 0.899  SVM 0.971 0.853 0.828 0.917  Stack 0.961 0.853 0.828 0.917 (d) MSS: multimodal (NIR + Raman) to detect pathological vs. normal patients  Logistic regression 0.961 0.969 0.966 0.984  SGD 0.944 0.967 0.966 0.923  SVM 1.000 1.000 1.000 1.000  Stack 1.000 0.944 0.931 0.969 Bold values indicate values obtained from the stack algorithm and used for analyses.

Adaptogenic activity of withaferin A on human cervical carcinoma cells using high-definition vibrational spectroscopic imaging

Despite invaluable advances in cervical cancer therapy, treatment regimens for recurrent or persistent cancers and low-toxicity alternative treatment options are scarce. In recent years, substances classified as adaptogens have been identified as promising drug sources for preventing and treating cancer-based diseases on their ability to attack multiple molecular targets. This paper establishes the effectiveness of inhibition of the neoplastic process by a withaferin A (WFA), an adaptogenic substance, based on an in vitro model of cervical cancer. This study explores for the first time the potential of high-definition vibrational spectroscopy methods, i.e. Fourier-transform infrared (FT-IR) and Raman spectroscopic (RS) imaging at the single-cell level to evaluate the efficacy of the adaptogenic drug. HeLa cervical cancer cells were incubated with various concentrations of WFA at different incubation times. The multimodal spectroscopic approach combined with partial least squares (PLS) regression allowed the identification of molecular changes (e.g., lipids, protein secondary structures, or nucleic acids) induced by WFA at the cellular level. The results clearly illustrate the enormous potential of WFA in inhibiting the proliferation of cervical cancer cells. WFA inhibited the growth of the studied cancer cell line in a dose-dependent manner. Such studies provide comprehensive information on the sensitivity of cells to adaptogenic drugs. This is a fundamental step towards determining the rate and nature of adaptogen-induced changes in cancer cells.

Overview of cocaine identification by vibrational spectroscopy and chemometrics

The use of non-destructive forensic methods for cocaine identification is of outstanding importance, given the amount of samples seized. Techniques such as ATR-FTIR, Raman, and NIR spectroscopy have become alternatives to circumvent this problem, as they allow fast, cheap analysis, and enable the reanalysis of samples. When combined with chemometrics, these spectroscopic methods can be used to determine and quantify cocaine samples, meaning that the limitations of existing techniques can be overcome. This review article covers spectroscopic techniques for identifying cocaine in different forms and matrices, such as food and textiles, which are materials used for smuggling. The chemometric identification of cocaine in oral fluid and water is also discussed. In addition, vibrational spectroscopy techniques using portable equipment are described. This work seeks to evaluate the main chemometric applications of spectroscopic data and to find new perspectives on the identification of cocaine using chemometrics.

Review of the Application of Raman Spectroscopy in Qualitative and Quantitative Analysis of Drug Polymorphism

Drug polymorphism is an important factor affecting the drugs quality and clinical efficacy. Therefore, great attention should be paid to the crystal analysis of drugs with their researching and evaluating part. With the booming development of Raman spectroscopy in recent years, more and more crystal analysis investigations were based on vibrational spectroscopy. This review mainly discussed the qualitative and quantitative analysis of active pharmaceutical ingredients (API) and pharmaceutical preparation with Raman spectroscopy. On basis of the determination of the vibration mode of drug molecules and the analysis of their chemical structure, this method had the advantages of universal, non-destructive, fast determination, low samples and cost, etc. This review provides theoretical and technical support for crystal structure, which are worth popularizing. It is expected that it will be helpful to relevant government management institutions, pharmaceutical scientific research institutions and pharmaceutical manufacturers.

Rapid discrimination of hepatic echinococcosis patients' serum using vibrational spectroscopy combined with support vector machines

Echinococcosis is a severe zoonotic parasitic disease, and it is continuing to be a significant public health issue. The course of the disease is usually slow, and patients often remain asymptomatic for years. There is no standardized and widely accepted treatment, so early and accurate diagnosis is essential. Herein, this study utilized vibrational spectroscopic techniques, namely Raman and Fourier Transform Infrared (FTIR) spectroscopy, to quickly and accurately distinguish hepatic echinococcosis (HE) patients' serum from the healthy group. Serum samples were collected from HE patients as well as healthy control subjects, and then the Raman and FTIR spectra of the two groups were recorded. After a series of pre-processing, support vector machines (SVMs) were then used to establish the classification models for the two spectral data sets. The performance of each diagnostic model was evaluated using leave-one-out cross-validation (LOOCV) and hold-out validation methods, respectively. For the distinction between HE and healthy groups, these two spectroscopic techniques had achieved satisfactory classification results, and the diagnostic capabilities of the Raman technique were comparable to that of the FTIR method. The results demonstrate that vibrational spectroscopy has great potential in the rapid and accurate detection of HE and is expected to make up for the shortcomings of the existing clinical diagnosis methods.

Trace Analysis of Gases and Liquids with Spontaneous Raman Scattering Based on the Integrating Sphere Principle

Spontaneous Raman scattering is an attractive optical technique for the analysis of gases and liquids; however, their low densities and notoriously weak scattering cross sections demand an enhancement of the spontaneous Raman scattering signal for detection. Here, we have developed a simple but highly effective and fast technique to enhance the signal of spontaneous Raman scattering from gases and liquids. The technique is developed based on the principle of an integrating sphere, which realizes the multiple pass actions of low-energy pump light and the collection of all Raman scattered light for a sample volume of 2 mL. By measuring the ambient air sample with an exposure time of 180 s, we found the experimental detection limit of our spontaneous Raman scattering setup can reach 3 ppm. CH₄ (<2 ppm) in air can be also examined by increasing the exposure time to 300 s. The performance of our setup used for the analysis of trace gases is further illustrated by characterizing ethane, propane, butane, and pentane in methane as well as isotopes of carbon dioxide. The results reveal that the detection limit of our setup for liquids can be improved by nearly 4 orders of magnitude compared to that of confocal Raman scattering spectroscopy with the same experimental conditions.

Protein secondary structure in spider silk nanofibrils

Nanofibrils play a pivotal role in spider silk and are responsible for many of the impressive properties of this unique natural material. However, little is known about the internal structure of these protein fibrils. We carry out polarized Raman and polarized Fourier-transform infrared spectroscopies on native spider silk nanofibrils and determine the concentrations of six distinct protein secondary structures, including β-sheets, and two types of helical structures, for which we also determine orientation distributions. Our advancements in peak assignments are in full agreement with the published silk vibrational spectroscopy literature. We further corroborate our findings with X-ray diffraction and magic-angle spinning nuclear magnetic resonance experiments. Based on the latter and on polypeptide Raman spectra, we assess the role of key amino acids in different secondary structures. For the recluse spider we develop a highly detailed structural model, featuring seven levels of structural hierarchy. The approaches we develop are directly applicable to other proteinaceous materials.

Secondary fibril structure is a key component of the mechanical properties of protein materials like silk, yet, limited information is known about the internal structure of these protein fibrils. Here, the authors report on the use of polarised Raman and FTIR spectroscopy to study silk materials and identify six distinct secondary structures.

A comparative study of meat quality and vibrational spectroscopic properties of different chicken breeds

Chicken breed is one of the key factors that influence meat quality. The quality attributes of breast meat from commercial broiler (CB), Thai native chicken (NC, Leung Hang Khao), and the crossbred Korat chicken (KC) were investigated via synchrotron radiation-based Fourier transform infrared (SR-FTIR) microspectroscopy, Fourier transform Raman (FT-Raman) spectroscopy, and physicochemical analysis. The protein and carbonyl contents of KC and NC meats were higher than that of CB meat, but the lipid content was lower (P < 0.05). CB meat was characterized by high moisture, lightness (L*), and presence of taste-active nucleotides, namely, inosine 5′-monophosphate (IMP) and guanosine 5′-monophosphate (GMP). Moreover, NC meat had the highest insoluble collagen and inosine contents (P < 0.05). The predominant protein secondary structures of KC and NC meats were β-turns and random coils, whereas α-helices were mainly found in CB meat. Based on principal component analysis, the meat quality and spectra were clearly separated by breeds. The high moisture and lipid content of meat corresponded to O–H stretching (3,203 cm⁻¹) and C–H stretching (2,854 cm⁻¹) in the FT-Raman spectra, whereas PO₂⁻ stretching (1,240 cm⁻¹), measured via SR-FTIR, was well correlated with the IMP content. In addition, the FT-Raman wavenumber of 934 cm⁻¹, indicating C–C stretching, was correlated with high water-holding capacity (WHC) in KC meat. The quality of meat from slow- and fast-growing chickens significantly varies. Vibrational spectroscopy is a powerful technique that provides insightful molecular information correlated with various meat attributes.

Simultaneous Raman and Infrared Spectroscopy of Stable Isotope Labelled Escherichia coli

We report the use of a novel technology based on optical photothermal infrared (O-PTIR) spectroscopy for obtaining simultaneous infrared and Raman spectra from the same location of the sample allowing us to study bacterial metabolism by monitoring the incorporation of 13C- and 15N-labeled compounds. Infrared data obtained from bulk populations and single cells via O-PTIR spectroscopy were compared to conventional Fourier transform infrared (FTIR) spectroscopy in order to evaluate the reproducibility of the results achieved by all three approaches. Raman spectra acquired were concomitant with infrared data from bulk populations as well as infrared spectra collected from single cells, and were subjected to principal component analysis in order to evaluate any specific separation resulting from the isotopic incorporation. Similar clustering patterns were observed in infrared data acquired from single cells via O-PTIR spectroscopy as well as from bulk populations via FTIR and O-PTIR spectroscopies, indicating full incorporation of heavy isotopes by the bacteria. Satisfactory discrimination between unlabeled (viz. 12C14N), 13C14N- and 13C15N-labeled bacteria was also obtained using Raman spectra from bulk populations. In this report, we also discuss the limitations of O-PTIR technology to acquire Raman data from single bacterial cells (with typical dimensions of 1 × 2 µm) as well as spectral artifacts induced by thermal damage when analyzing very small amounts of biomass (a bacterium tipically weighs ~ 1 pg).

Label-free discrimination of tumorigenesis stages using in vitro prostate cancer bone metastasis model by Raman imaging

Metastatic prostate cancer colonizes the bone to pave the way for bone metastasis, leading to skeletal complications associated with poor prognosis and morbidity. This study demonstrates the feasibility of Raman imaging to differentiate between cancer cells at different stages of tumorigenesis using a nanoclay-based three-dimensional (3D) bone mimetic in vitro model that mimics prostate cancer bone metastasis. A comprehensive study comparing the classification of as received prostate cancer cells in a two-dimensional (2D) model and cancer cells in a 3D bone mimetic environment was performed over various time intervals using principal component analysis (PCA). Our results showed distinctive spectral differences in Raman imaging between prostate cancer cells and the cells cultured in 3D bone mimetic scaffolds, particularly at 1002, 1261, 1444, and 1654 cm-1, which primarily contain proteins and lipids signals. Raman maps capture sub-cellular responses with the progression of tumor cells into metastasis. Raman feature extraction via cluster analysis allows for the identification of specific cellular constituents in the images. For the first time, this work demonstrates a promising potential of Raman imaging, PCA, and cluster analysis to discriminate between cancer cells at different stages of metastatic tumorigenesis.

Vibrational Spectroscopy Combined with Chemometrics in Authentication of Functional Foods

Many foods have both edible and medical importance and are appreciated as functional foods, preventing diseases. However, due to unscrupulous vendors and imperfect market supervision mechanisms, curative foods are prone to adulteration or some other events that harm the interests of consumers. However, traditional analytical methods are unsuitable and expensive for a broad and complex application. Therefore, people urgently need a fast, efficient, and accurate detection method to protect self-interests. Recently, the study of target samples by vibration spectrum shows strong qualitative and quantitative ability. The model established by platform technology combined with the stoichiometric analysis method can obtain better parameters, which it has good robustness and can detect functional food efficiently, quickly and nondestructive. The review compared and prospect five different vibrational spectroscopic techniques (near-infrared, Fourier transform infrared, Raman, hyperspectral imaging spectroscopy and Terahertz spectroscopy). In order to better solve some of the actual situations faced by certification, we explore and through relevant research and investigation to appropriately highlight the applicability and importance of technology combined with chemometrics in functional food authentication. There are four categories of authentication discussed: functional food authenticated in source, processing method, fraud and ingredient ratio. This paper provides an innovative process for the authentication of functional food, which has a meaningful reference value for future review or scientific research of relevant departments.

Leaf microscopy applications in photosynthesis research: identifying the gaps

Leaf imaging via microscopy has provided critical insights into research on photosynthesis at multiple junctures, from the early understanding of the role of stomata, through elucidating C4 photosynthesis via Kranz anatomy and chloroplast arrangement in single cells, to detailed explorations of diffusion pathways and light utilization gradients within leaves. In recent decades, the original two-dimensional (2D) explorations have begun to be visualized in three-dimensional (3D) space, revising our understanding of structure-function relationships between internal leaf anatomy and photosynthesis. In particular, advancing new technologies and analyses are providing fresh insight into the relationship between leaf cellular components and improving the ability to model net carbon fixation, water use efficiency, and metabolite turnover rate in leaves. While ground-breaking developments in imaging tools and techniques have expanded our knowledge of leaf 3D structure via high-resolution 3D and time-series images, there is a growing need for more in vivo imaging as well as metabolite imaging. However, these advances necessitate further improvement in microscopy sciences to overcome the unique challenges a green leaf poses. In this review, we discuss the available tools, techniques, challenges, and gaps for efficient in vivo leaf 3D imaging, as well as innovations to overcome these difficulties.

Identification and characterisation of individual nanoplastics by scanning transmission X-ray microscopy (STXM)

Nanoplastics (NP) are of environmental and human health concern. We tested a novel NP extraction method and scanning transmission X-ray spectro-microscopy (STXM) in combination with near-edge X-ray absorption fine-structure spectroscopy (NEXAFS) to image and identify individual NP in environmental and food matrices. We (1) discussed the potential of STXM compared to other methods potentially suitable for NP analysis, (2) applied the method on NP suspensions of eight of the most common polymers, (3) analyzed environmental water and soil samples spiked with NP and (4) characterized NP in tea water infused in plastic teabags and unspiked soil samples. Here we show that STXM has methodological advantages and that polymers give characteristic spectra, which allows NP identification in environmental and food matrices. For soils we deliver a visual and spectroscopic characterization of NP, proving their presence and highlighting their diversity. Thus, STXM, can be used for the detection and characterisation of NP in different types of matrices.

Relative Populations and IR Spectra of Cu38 Cluster at Finite Temperature Based on DFT and Statistical Thermodynamics Calculations

The relative populations of Cu38 isomers depend to a great extent on the temperature. Density functional theory and nanothermodynamics can be combined to compute the geometrical optimization of isomers and their spectroscopic properties in an approximate manner. In this article, we investigate entropy-driven isomer distributions of Cu38 clusters and the effect of temperature on their IR spectra. An extensive, systematic global search is performed on the potential and free energy surfaces of Cu38 using a two-stage strategy to identify the lowest-energy structure and its low-energy neighbors. The effects of temperature on the populations and IR spectra are considered via Boltzmann factors. The computed IR spectrum of each isomer is multiplied by its corresponding Boltzmann weight at finite temperature. Then, they are summed together to produce a final temperature-dependent, Boltzmann-weighted spectrum. Our results show that the disordered structure dominates at high temperatures and the overall Boltzmann-weighted spectrum is composed of a mixture of spectra from several individual isomers.

Simultaneous Raman and infrared spectroscopy: a novel combination for studying bacterial infections at the single cell level

Sepsis is a life-threatening clinical condition responsible for approximately 11 million deaths worldwide. Rapid and accurate identification of pathogenic bacteria and its antimicrobial susceptibility play a critical role in reducing the morbidity and mortality rates related to sepsis. Raman and infrared spectroscopies have great potential to be used as diagnostic tools for rapid and culture-free detection of bacterial infections. Despite numerous reports using both methods to analyse bacterial samples, there is to date no study collecting both Raman and infrared signatures from clinical samples simultaneously due to instrument incompatibilities. Here, we report for the first time the use of an emerging technology that provides infrared signatures via optical photothermal infrared (O-PTIR) spectroscopy and Raman spectra simultaneously. We use this approach to analyse 12 bacterial clinical isolates including six isolates of Gram-negative and six Gram-positive bacteria commonly associated with bloodstream infection in humans. To benchmark the single cell spectra obtained by O-PTIR spectroscopy, infrared signatures were also collected from bulk samples via both FTIR and O-PTIR spectroscopies. Our findings showed significant similarity and high reproducibility in the infrared signatures obtained by all three approaches, including similar discrimination patterns when subjected to clustering algorithms. Principal component analysis (PCA) showed that O-PTIR and Raman data acquired simultaneously from bulk bacterial isolates displayed different clustering patterns due to the ability of both methods to probe metabolites produced by bacteria. By contrast, signatures of microbial pigments were identified in Raman spectra, providing complementary and orthogonal information compared to infrared, which may be advantageous as it has been demonstrated that certain pigments play an important role in bacterial virulence. We found that infrared spectroscopy showed higher sensitivity than Raman for the analysis of individual cells. Despite the different patterns obtained by using Raman and infrared spectral data as input for clustering algorithms, our findings showed high data reproducibility in both approaches as the biological replicates from each bacterial strain clustered together. Overall, we show that Raman and infrared spectroscopy offer both advantages and disadvantages and, therefore, having both techniques combined in one single technology is a powerful tool with promising applications in clinical microbiology.

O-PTIR was used for simultaneous collection of infrared and Raman spectra from clinical pathogens associated with bloodstream infections.

Spectral Properties of Foams and Emulsions

The optical and spectral properties of foams and emulsions provide information about their micro-/nanostructures, chemical and time stability and molecular data of their components. Foams and emulsions are collections of different kinds of bubbles or drops with particular properties. A summary of various surfactant and emulsifier types is performed here, as well as an overview of methods for producing foams and emulsions. Absorption, reflectance, and vibrational spectroscopy (Fourier Transform Infrared spectroscopy-FTIR, Raman spectroscopy) studies are detailed in connection with the spectral characterization techniques of colloidal systems. Diffusing Wave Spectroscopy (DWS) data for foams and emulsions are likewise introduced. The utility of spectroscopic approaches has grown as processing power and analysis capabilities have improved. In addition, lasers offer advantages due to the specific properties of the emitted beams which allow focusing on very small volumes and enable accurate, fast, and high spatial resolution sample characterization. Emulsions and foams provide exceptional sensitive bases for measuring low concentrations of molecules down to the level of traces using spectroscopy techniques, thus opening new horizons in microfluidics.

Versatile Tools for Understanding Electrosynthetic Mechanisms

Electrosynthesis is a popular, green alternative to traditional organic methods. Understanding the mechanisms is not trivial yet is necessary to optimize reaction processes. To this end, a multitude of analytical tools is available to identify and quantitate reaction products and intermediates. The first portion of this review serves as a guide that underscores electrosynthesis fundamentals, including instrumentation, electrode selection, impacts of electrolyte and solvent, cell configuration, and methods of electrosynthesis. Next, the broad base of analytical techniques that aid in mechanism elucidation are covered in detail. These methods are divided into electrochemical, spectroscopic, chromatographic, microscopic, and computational. Technique selection is dependent on predicted reaction pathways and electrogenerated intermediates. Often, a combination of techniques must be utilized to ensure accuracy of the proposed model. To conclude, future prospects that aim to enhance the field are discussed.

The online coupling of liquid chromatography to Fourier transform infrared spectroscopy using a solute-deposition interface: A proof of concept

Hyphenated techniques combining chromatographic and spectroscopic methods are the gold standard to effectively handle the emerging challenges in the analysis of unknown chemical components in mixtures, and in this regard the coupling of liquid chromatography to Fourier transform infrared spectroscopy (LC-FTIR) is no exception. While earlier attempts to couple LC to IR spectroscopy relied almost entirely on offline techniques, clear motivations for implementing online LC-FTIR instrumentation emerged from the need for shorter analysis time, a higher degree of automation and sample throughput, better reproducibility, and reduced contamination. Most recent designs of LC-FTIR concepts have aimed to combine the advantages of both approaches by means of a solvent-elimination interface. The hyphenated instrumentation and method presented in this research are based on a pneumatically assisted LC-FTIR interface, relying on a small-scale self-regulating spray dryer to attain desolvation of the LC eluent stream while retaining the spatial and temporal resolution of the dissolved substrates. Focused deposition of the dried analytes occurs onto a ZnSe disc for continuous transmission mid-IR analysis at a resolution of 4 cm^-1. The optimization of the LC-FTIR technique is discussed in terms of interface parameters, limits of detection, and limits of quantification for a pair of furanocoumarin isomers differing in the position (linear or angular type) of the furan ring fused to coumarin. Finally, confident discrimination between the two closely related molecules was attained by matching the experimental FTIR spectra in a dedicated library. The quality match factors obtained were higher than 99% for both molecules. The limit of identification (LOI) was determined experimentally as the minimum amount of substance yielding a library-searchable IR spectrum (affording a quality match factor higher than 90%). Specifically, LOI of 0.6 μg and 1.25 μg was determined for psoralen and angelicin, respectively.

Broadband complementary vibrational spectroscopy with cascaded intra-pulse difference frequency generation

One of the essential goals of molecular spectroscopy is to measure all fundamental molecular vibrations simultaneously. To this end, one needs to measure broadband infrared (IR) absorption and Raman scattering spectra, which provide complementary vibrational information. A recently demonstrated technique called complementary vibrational spectroscopy (CVS) enables simultaneous measurements of IR and Raman spectra with a single device based on a single laser source. However, the spectral coverage was limited to ∼1000cm^-1, which partially covers the spectral regions of the fundamental vibrations. In this work, we demonstrate a simple method to expand the spectral bandwidth of the CVS with a cascaded intra-pulse difference-frequency generation (IDFG). Using the system, we measure broadband CVS spectra of organic liquids spanning over 2000cm^-1, more than double the previous study.

Monitoring the ripening attributes of Turkish white cheese using miniaturized vibrational spectrometers

Monitoring the ripening process by prevalent analytic methods is laborious, expensive, and time consuming. Our objective was to develop a rapid and simple method based on vibrational spectroscopic techniques to understand the biochemical changes occurring during the ripening process of Turkish white cheese and to generate predictive algorithms for the determination of the content of key cheese quality and ripening indicator compounds. Turkish white cheese samples were produced in a pilot plant scale and ripened for 100 d, and samples were analyzed at 20 d intervals during storage. The collected spectra (Fourier-transform infrared, Raman, and near-infrared) correlated with major composition characteristics (fat, protein, and moisture) and primary products of the ripening process and analyzed by pattern recognition to generate prediction (partial least squares regression) and classification (soft independent analysis of class analogy) models. The soft independent analysis of class analogy models classified cheese samples based on the unique biochemical changes taking place during the ripening process. partial least squares regression models showed good correlation (R_Pre = 0.87 to 0.98) between the predicted values by vibrational spectroscopy and the reference values, giving low standard errors of prediction (0.01 to 0.57). Portable and handheld vibrational spectroscopy units can be used as a rapid, simple, and in situ technique for monitoring the quality of cheese during aging and provide real-time tools for addressing deviations in manufacturing.

Imaging of α-Synuclein Aggregates in a Rat Model of Parkinson's Disease Using Raman Microspectroscopy

A hallmark of Parkinson’s disease (PD) is the formation of Lewy bodies in the brain. Lewy bodies are rich in the aggregated form of misfolded α-Synuclein (α-Syn). The brain from PD patients can only be analyzed after postmortem, therefore, limiting the diagnosis of PD to the manifestation of motor symptoms. In PD patients and animal models, phosphorylated α-Syn was detected in the peripheral tissues including the gut, thus, raising the hypothesis that early-stage PD could be diagnosed based on colon tissue biopsies. Non-invasive marker-free technologies represent ideal methods to potentially detect aggregated α-Syn in vivo. Raman microspectroscopy has been established for the detection of molecular changes such as alterations of protein structures. Using Raman imaging and microspectroscopy, we analyzed the olfactory bulb in the brain and the muscularis mucosae of colon tissue sections of a human BAC-SNCA transgenic (TG) rat model. Raman images from TG and WT rats were investigated using principal component analysis (PCA) and true component analysis (TCA). Spectral components indicated protein aggregates (spheroidal oligomers) in the TG rat brain and in the colon tissues even at a young age but not in WT. In summary, we have demonstrated that Raman imaging is capable of detecting α-Syn aggregates in colon tissues of a PD rat model and making it a promising tool for future use in PD pathology.

Current and potential applications of simultaneous DSC-FTIR microspectroscopy for pharmaceutical analysis

Quality control (QC) is the most important key issue in the pharmaceutical industry to ensure the quality of drug products. Many analytical instruments and techniques in pharmaceutical analysis are applied to assess the quality and quantity of the drugs. In the current and future trends, a combination of digitization, automation and hyphenation with high throughput on-line performance will be the topics for the future of pharmaceutical QC. The hyphenated analytical techniques have recently received great attention as unique means to solve complex analytical problems in a short period of time. This review article is an update on the recent potential applications of hyphenated technique developed from the coupling of a rapid separation or induction technique (differential scanning calorimetry; DSC) and an on-line spectroscopic (Fourier transform infrared; FTIR) detection technology to carry out an one-step solid-state analysis in pharmaceutical formulation developments, including (1) intramolecular condensation of pharmaceutical polymers, (2) intramolecular cyclization of drugs and sweetener, (3) polymorphic transformation of drugs and excipients, (4) drug-polymer (excipient) interaction, (5) fast cocrystal screening and formation. This simultaneous DSC-FTIR microspectroscopy can also provide an easy and direct method for one-step screening and qualitative detection of drug stability in real time.

Bond-selective imaging by optically sensing the mid-infrared photothermal effect

Mid-infrared (IR) spectroscopic imaging using inherent vibrational contrast has been broadly used as a powerful analytical tool for sample identification and characterization. However, the low spatial resolution and large water absorption associated with the long IR wavelengths hinder its applications to study subcellular features in living systems. Recently developed mid-infrared photothermal (MIP) microscopy overcomes these limitations by probing the IR absorption-induced photothermal effect using a visible light. MIP microscopy yields submicrometer spatial resolution with high spectral fidelity and reduced water background. In this review, we categorize different photothermal contrast mechanisms and discuss instrumentations for scanning and widefield MIP microscope configurations. We highlight a broad range of applications from life science to materials. We further provide future perspective and potential venues in MIP microscopy field.

Attenuated Total Reflectance-Fourier transform infrared spectroscopy coupled with chemometrics for the rapid detection of coconut water adulteration

Attenuated Total Reflectance-Fourier Transform Infrared spectroscopy (ATR-FTIR), in combination with chemometrics, was explored as a rapid method of detecting sugar adulteration in coconut water. In a simulated experiment, coconut water was substituted with binary sugars, mixed sugars, and high fructose corn syrup and discriminated using the fingerprint infrared band region between 1200 and 950 cm^-1. Principal component analysis (PCA) performed on data pre-processed by the Savitzky-Golay smoothing and gap-segment derivative, revealed data clusters discernible by the type and level of substituted sugars, enabling visual diagnosis of the similarity and anomalous features in the dataset. Statistical performance metrics following a cross-validated partial least square (PLS) regression indicated the prediction of adulterant sugars at single-digit percent substitutions. A parallel exploratory analysis of 31 different commercial coconut water samples showed a distinct PCA clustering for samples bearing the label "added sugar", suggesting the potential use of the methods to screening samples for undeclared sugar additions.

Comparison of Raman and Near-Infrared Chemical Mapping for the Analysis of Pharmaceutical Tablets

Raman and near-infrared (NIR) chemical mapping are widely used methods in the pharmaceutical industry to understand the distribution of components within a drug product. Recent advancements in instrumentation have enabled the rapid acquisition of high-resolution images. The comparison of these techniques for the analysis of pharmaceutical tablets has not recently been explored and thus the relative performance of each technique is not currently well defined. Here, the differences in the chemical images obtained by each method are assessed and compared with scanning electron microscopy with energy dispersive X-ray microanalysis (SEM-EDX), as an alternative surface imaging technique to understand the ability of each technique to acquire a chemical image representative of the sample surface. It was found that the Raman data showed the best agreement with the spatial distribution of components observed in the SEM-EDX images. Quantitative and qualitative comparison of the Raman and NIR images revealed a very different spatial distribution of components with regards to domain size and shape. The Raman image exhibited sharper and better discriminated domains of each component, whereas the NIR image was heavily dominated by large pixelated domains. This study demonstrated the superiority of using Raman chemical mapping compared with NIR chemical mapping to produce a chemical image representative of the sample surface using routinely available instrumentation to obtain a better approximation of domain size and shape. This is fundamental for understanding knowledge gaps in current manufacturing processes; particularly relating the relationship between components in the formulation, processing condition, and final characteristics. By providing a means to more accurately visualize the components within a tablet matrix, these areas can all be further understood.

Machine learning for recognizing minerals from multispectral data

Machine Learning (ML) has found several applications in spectroscopy, including recognizing minerals and estimating elemental composition. ML algorithms have been widely used on datasets from individual spectroscopy methods such as vibrational Raman scattering, reflective Visible-Near Infrared (VNIR), and Laser-Induced Breakdown Spectroscopy (LIBS). We firstly reviewed and tested several ML approaches to mineral classification from the existing literature, and identified a novel approach for using Deep Learning algorithms for mineral classification from Raman spectra, that outperform previous state-of-the-art methods. We then developed and evaluated a novel method for automatic mineral identification from combining measurements with two complementary spectroscopic methods using Convolutional Neural Networks (CNN) for Raman and VNIR, and cosine similarity for LIBS. Specifically, we evaluated fusing Raman + VNIR, Raman + LIBS or VNIR + LIBS spectra in order to classify minerals. ML methods applied to combined spectral methods presented here are shown to outperform the use of a single data source by a significant margin. Our approach was tested on both open access experimental Raman (RRUFF) and VNIR (USGS, RELAB, ECOSTRESS) libraries, as well as on synthetic LIBS (NIST) spectral libraries. Our cross-validation tests show that multi-method spectroscopy paired with ML paves the way towards rapid and accurate characterization of rocks and minerals. Future solutions combining Deep Learning Algorithms, together with data fusion from multi-method spectroscopy, could drastically increase the accuracy of automatic mineral recognition compared to existing approaches.

Photoinduced Dynamics with Constrained Vibrational Motion: FrozeNM Algorithm

Ab initio molecular dynamics (AIMD) simulation, analyzed in terms of vibrational normal modes, is a widely used technique that facilitates understanding of complex structural motions and coupling between electronic and nuclear degrees of freedom. Usually, only a subset of vibrations is directly involved in the process of interest. The impact of these vibrations can be evaluated by performing AIMD simulations by selectively freezing certain motions. Herein, we present frozen normal mode (FrozeNM), a new algorithm to apply normal-mode constraints in AIMD simulations, as implemented in the nonadiabatic excited state molecular dynamics code. We further illustrate its capacity by analyzing the impact of normal-mode constraints on the photoinduced energy transfer between polyphenylene ethynylene dendrimer building blocks. Our results show that the electronic relaxation can be significantly slowed down by freezing a well-selected small subset of active normal modes characterized by their contributions in the direction of energy transfer. The application of these constraints reduces the nonadiabatic coupling between electronic excited states during the entire dynamical simulations. Furthermore, we validate reduced dimensionality models by freezing all the vibrations, except a few active modes. Altogether, we consider FrozeNM as a useful tool that can be broadly used to underpin the role of vibrational motion in a studied process and to formulate reduced models that describe essential physical phenomena.

Intrinsic molecular vibration and rigorous vibrational assignment of benzene by first-principles molecular dynamics

Vibrational assignment, which establishes the correspondence between vibrational modes and spectral frequencies, is a key step in any spectroscopic study. Due to the lack of experimental technique to directly observe the thermal vibration of atoms, the assignment is usually done by empirical trial-and-error method with considerable uncertainty. Here we demonstrate a successful study of intrinsic molecular vibration property based on first-principles molecular dynamics trajectory. A unified approach for calculating and assigning vibrational frequencies is developed and applied to solve some historical issues of benzene vibration. As a major achievement, the experimental frequencies of benzene a_2g and b_2u vibrations are reassigned, which breaks a deadlock in contemporary spectroscopic science and removes a cloud over the application of density-functional theory in organic chemistry. This work paves the way for the comprehensive realization of the first-principles spectroscopic research, and provides crucial clues to solve the century-old problems of Kekule resonance, π-deformation, and aromaticity.

Vibrational Spectroscopy for Identification of Metabolites in Biologic Samples

Vibrational spectroscopy (mid-infrared (IR) and Raman) and its fingerprinting capabilities offer rapid, high-throughput, and non-destructive analysis of a wide range of sample types producing a characteristic chemical "fingerprint" with a unique signature profile. Nuclear magnetic resonance (NMR) spectroscopy and an array of mass spectrometry (MS) techniques provide selectivity and specificity for screening metabolites, but demand costly instrumentation, complex sample pretreatment, are labor-intensive, require well-trained technicians to operate the instrumentation, and are less amenable for implementation in clinics. The potential for vibration spectroscopy techniques to be brought to the bedside gives hope for huge cost savings and potential revolutionary advances in diagnostics in the clinic. We discuss the utilization of current vibrational spectroscopy methodologies on biologic samples as an avenue towards rapid cost saving diagnostics.

Tolerance to Stretching in Thiol-Terminated Single-Molecule Junctions Characterized by Surface-Enhanced Raman Scattering

We investigated the change in the metal-molecule interaction in a 1,4-benzenedithiol (BDT) single-molecule junction using a combination of surface-enhanced Raman scattering spectra and current-voltage curves. During the stretching process, the conductance of the junction systematically decreased, accompanied by an increase in the vibrational energy of the CC stretching mode. By analyzing the current-voltage curves and Raman spectra, we found that the interaction between the π orbital of BDT and the electronic states of Au was diminished by the orientation change of BDT during the stretching process. A comparison with a 4,4'-bipyridine single-molecule junction revealed that the reduction of coupling of the Au-S contacts was smaller than that of Au-pyridine contacts. Therefore, the electronic states originating from the contact geometry are responsible for the tolerance to the stretching of thiol-terminated molecular junctions.

Microcavity Enhanced Raman Spectroscopy of Fullerene C60 Bucky Balls

Raman spectroscopy is a widely used characterization technique in material science. It is a non-destructive tool with relatively simple instrumentation, and provides intrinsic qualitative information of analytes by probing their vibrational modes. In many cases, Raman enhancement is essential for detecting low-intensity signals in high-noise environments, spectrally unresolved features, and hidden modes. Here we present optical and Raman spectroscopic characterization of fullerene C 60 in a gold microcavity. The fabrication of single-layered gold mirrors is facile, low cost and direct but was proven to give considerably significant enhancement. The findings of this work demonstrate the cavity resonance as a powerful tool in obtaining tunability over individual peak for selective enhancement in the tuned spectral range. The PL of the material within the cavity has demonstrated a red shift assumed to be caused by the low-energy transitions. These transitions are induced by virtual low-energy states generated by the cavity. We further observe that adopting this principle enables resolution of active Raman modes that until now were unobserved. Finally, we assigned the new experimentally observed modes to the corresponding motions calculated by DFT.