Non-destructive Analysis Research Articles

Nondestructive volumetric optical analysis of corroded copper oxidation using 1700nm swept-source optical coherence microscopy.

This study presents a novel nondestructive analysis method for precise characterization of corroded copper oxidation using optical coherence microscopy (OCM). By exploiting the partial light transmission through metallic oxide layers, we employed a specialized OCM system with a wavelength of 1700nm and enhanced the analysis accuracy compared to conventional optical coherence tomography (OCT). The developed OCM system featured a numerical aperture (NA) of 0.15, providing improved surface profiling and higher lateral resolution than OCT. we developed a peak-finding algorithm to accurately determine the thickness of the copper oxide layer from the acquired interference data with zero padding. Our method was validated by comparing the measured thickness profiles with those obtained from scanning electron microscope (SEM) images of corroded metals. The copper oxidation specimens were prepared after heat treatment for 1, 2, 4, and 8 h in an alumina tube furnace at a temperature of 900 °C to find the correlation between the OCM thickness measurement. Additionally, the acquired enface 3D images enabled the identification of local corrosion distribution within a 4 mm × 4 mm area. The en-face mapping images are utilized to analyze the uniformity of the metal oxidation process across the imaging area of the copper oxidation specimens. With an increase in heat treatment time, the median value of the thickness histogram for the copper oxide within the area consistently remained around 10 µm. However, the thickness variation ranged from -2 µm to 5 µm. This indicates that as the heat treatment time progresses, the thickness of the copper oxide becomes more non-uniform. Our technique holds great potential for nondestructive and noncontact detection of metal corrosion and assessment of corrosion rates in various industrial applications. Future research efforts could focus on expanding the application of OCM to different metals and exploring its commercialization prospects for practical implementation in diverse industries.

How to Achieve Excellent Luminescence Properties of Cr Ion‐Doped Near‐Infrared Phosphors

AbstractTransition metal chromium (Cr) ion‐doped inorganic materials exhibit distinct tunable broadband near‐infrared luminescence, and they have promising applications including nondestructive composition analysis, night vision, biomedicine, plant illumination, and afterglow anticounterfeiting. Currently, the most critical issue is to optimize their full width at half maxima, thermal stability, and internal/external quantum efficiency. This review systematically summarizes strategies to effectively improve the photoluminescence performance of near‐infrared‐emitting materials with transition metal chromium ions. Key examples of the design and preparation of Cr ion‐doped luminescence with different transition modes, a detailed discussion of strategies to effectively improve the photoluminescence properties of near‐infrared luminescent materials, and a summary of generic strategies to help explore novel and efficient Cr‐doped phosphor materials are provided. Next, the latest developments and trends in these Cr ion‐doped phosphor materials are presented for a variety of application scenarios. Finally, future research directions and new challenges faced are also discussed.

Dynamic Changes and Correlation Analysis of Polysaccharide Content and Color Parameters in Glycyrrhiza Stems and Leaves during Fermentation

Fermentation can increase the concentration of active ingredients and improve the effectiveness of Chinese herbal medicine. The purpose of this study was to investigate the effect of solid-state fermentation (SSF) on the polysaccharide content and color of Glycyrrhiza stems and leaves, as well as to explore the potential of computer vision-based analytical chemistry for the rapid, non-destructive, and accurate quality identification of fermented herbs. The effects of different inoculation rates on the polysaccharide content and color of fermented Glycyrrhiza stems and leaves were evaluated. Subsequently, dynamic changes in the viable counts of the probiotic strains, pH values, polysaccharide content, and color of Glycyrrhiza stems and leaves were explored during the entire fermentation process. The correlations of color variables that were extracted from the images with key quality indicators of the Glycyrrhiza stem and leaf samples were verified. The results showed that with an increase in inoculation amount, the polysaccharide content demonstrated a trend of first increasing and then decreasing, which was consistent with the color parameter behavior, and the optimal inoculation amount was 0.2%. During fermentation, R, G, B, S, V, L, a*, and B* were significantly correlated with the polysaccharide content (p < 0.01), while the correlation of H was weak. Principal component analysis (PCA) based on color variables can effectively distinguish between different stages of fermentation. This study provides a reference for the rapid and nondestructive analysis of fermented Glycyrrhiza stems and leaves, offering a new approach to process monitoring and quality control of fermented herbs.

Study of bremsstrahlung radiation coming from a transmission type x-ray generator and its application on EDXRF technique

We have demonstrated the use of the bremsstrahlung radiation from a small, portable, transmission type x-ray generator that can be used in energy dispersive x-ray fluorescence technique as a tool to perform non-destructive elemental analysis of solid samples employed in inter-disciplinary science research. As our knowledge goes, till date, this is the first attempt to generate the bremsstrahlung spectrum theoretically from a portable transmission type x-ray generator and compared it with the actual observation. Theoretically generated bremsstrahlung spectra are also found to be in good agreement with the experimentally observed spectra obtained with various operating anode voltages of the x-ray generator. A computer program has been developed utilizing a few atomic parameters to obtain the elemental concentrations in the sample by a single run using the whole bremsstrahlung. The knowledge of incoming x-ray flux, geometry of experimental arrangements are not required in this technique. To validate the technique, we have taken two samples: an Indian one rupee coin of the year 2000 and a NIST made brass sample, whose compositions are well known. We have used these samples to expose to the bremsstrahlung radiation, produced by the operating anode voltages 20, 25, and 30 KV. The relative concentrations of different elements are determined, which is in good agreement with the earlier results.

Recognition of mineralogical and technological varieties of iron ore on the basis of ultrasound backscatter spectrograms

The research is aimed to the analysis and modeling of the process of propagation of ultrasonic waves in iron ore samples to assess its mineralogical varieties. The paper analyzes domestic and foreign experience in modeling of ultrasonic waves propagation; methods of mathematical and computer modeling were used, as well as methods of mathematical statistics and probability theory for analysis of the results. Scientific novelty consists in developing and substantiating a method for recognizing the mineralogical and technological varieties of iron ore of a developed deposit based on spectrograms of a backscattered ultrasonic probing signal. Practical valueconsists in developing a methodology for non-contact non-destructive mineralogical analysis of iron ore to improve the efficiency and quality of its further processing and preparation for metallurgical processing. results. As measurable characteristic estimates of textural and structural features of iron ore varieties the results of spectral analysis of the reversed radiant ultrasonic signal were used. To implement the measurement results classification procedure, Adaptive Neuro-Fuzzy Inference System is used. At the vector of parameters of membership functions of terms of input variables and the vector of coefficients of linear functions in the conclusions of the rules was formed based on the characteristics of the processed ore and the spectrograms of the backscattered ultrasonic signal. The average accuracy of recognition of magnetite, chlorite-carbonate-magnetite, hematite-magnetite, magnetite-cummngtonite-chlorite-siderite mineral varieties of iron ore of the studied deposit was 93%.

Shannon entropy on near-infrared spectroscopy for nondestructively determining water content in oil palm

<span lang="EN-US">Indonesia is the world’s largest producer of palm oil. To preserve its competitive advantages, the Indonesian oil palm sector must expand high-quality palm oil output. In oil palm quality control, the water content is a crucial parameter as it can be used as a reference to determine the right harvest time. Thus, this study proposed a near-infrared (NIR) spectroscopy as a fast and non-destructive analysis to assess oil palm water content. NIR spectra were processed using Shannon entropy to describe the characteristics at each wavelength. In this study, oil palm fruit samples at various maturity levels were collected with eight different maturity fractions. Based on the analysis, the Shannon entropy value is closely related to any changes in the water content of palm oil. The entropy value has a decreasing trend as the water content increases. The proposed technique can predict the water content of an oil palm with satisfactory performance with values of 0.9746 of coefficient of determination (R<sup>2</sup>) and 2,487 of root mean square error (RMSE). Application of this model will lead to a fast and accurate prediction system related to oil palm water content.</span>

Non-Destructive Discrimination of Blue Inks on Suspected Documents through the Combination of Raman Spectroscopy and Chemometric Analysis

Increasingly sophisticated techniques for falsifying and forging legal documents demand non-destructive and accurate analysis methods. Researchers have extensively investigated ink discrimination through an interdisciplinary analysis involving Raman spectroscopy and chemometrics, which is now regarded as a leading forensic document analysis approach. In this study, a groundbreaking method was developed to identify the specific origin of blue-ink pens used in written documents. By employing Raman spectroscopy in conjunction with principal component analysis (PCA), we successfully differentiated between 45 different blue-ink pens used on various documents. The Raman spectroscopy analysis provided a visual examination of each blue ink’s unique Raman signature, and PCA was then applied to the processed spectral data. Moreover, we successfully distinguished highly similar ink types in documents through the combined use of Raman spectroscopy, Pearson’s correlation analysis, and a statistical approach (PCA).

Hyperspectral imaging to assess wine grape quality

AbstractBackgroundGrape composition is of high interest for producing quality wines. For that, grape analyses are necessary, and require sample preparation, whether with classical analyses or with NIR analyses. The aim of the study was to test the ability of hyperspectral imaging (HSI), a nondestructive analysis to assess their composition. For that, seven grape varieties were analyzed for two vintages. Partial least squares (PLS) and discriminate (PLS‐DA) and PLS‐R were realized respectively in order to classify the berries, to validate the data sets, and to provide models to assess grape composition after a 1st derivative data pretreatment.ResultsHSI allowed a 100% good classification of the grape varieties. It showed good results to assess technological ripening parameters (sugar and acid contents) as well as phenolic content (TPI, Total Phenolics, Total Anthocyanins, Total Flavonoids, and their extractable equivalents) (globally R2 > 0.81). However, it was not possible to reach the color intensity of grapes.ConclusionHSI led to generate good models to assess wine grape composition. The quality of the generated models was dependent on the color of grapes and the parameter considered.

A novel paper-based electrochemiluminescence biosensor for non-destructive detection of pathogenic bacteria in real samples

The demand for sensitive, portable, and non-destructive analysis of pathogenic bacteria is of significance in point-of-care diagnosis. Herein, we constructed a smart electrochemiluminescence (ECL) biosensor by integrating a flexible paper-based sensing device and a disposable three-electrode detecting system. Staphylococcus aureus (S. aureus)-responsive cellulose paper was prepared by employing aptamer as recognition element and a probe DNA (probe DNA-GOD) tagged with glucose oxidase (GOD) as a signal amplification unit. The formation of aptamer-S. aureus complex mediated the quantitative release of probe DNA-GOD. The remaining probe DNA-GOD on the paper-based aptasensor was then activated by glucose, which resulted in a significant decrease in ECL signal. To further improve the ECL performance of biosensor, a large number of Ru(bpy)32+ molecules were embedded into porous zinc-based metal-organic frameworks (MOFs) to form Ru(bpy)32+ functionalized MOF nanoflowers (Ru-MOF-5 NFs). Such biosensor enabled accurate, non-destructive, and real-time monitoring of S. aureus-contaminated food samples, opening a new avenue for sensitive recognition of pathogenic bacteria.

A Study on the Preservation Treatment of Gold-Leafed Clothing Artefacts Excavated from a Tomb of the Cheongsong Shim Clan - Focusing on Bugeum Wonsam and Jikgeum Chima (Skirt) -

The purpose of this study is to perform a non-destructive material analysis and conservation treatments on two gold-leafed clothing artefacts (Bugeum Wonsam and Jikgeum Chima (Skirt)) excavated from a tomb of the Cheongsong Shim Clan held by the Chungbuk National University Museum. The artefacts, which were excavated in April 2003, had been stored in storage and were found to be wrinkled, contaminated, hardened and dried. The preservation treatment of the artefacts was performed by means of material analysis and repair. The analysis of the material using scanning electron microscopy SEM, FT-IR, colorimetric and XRF analyses showed that the material is silk fiber, and the analysis of the gold leaf layer using XRF showed that the gold leaf is gold (Au). The preservation treatment was performed by investigating the condition of the artefacts and conducting preliminary experiments on the reinforcing agents. For the reinforcement treatment, a 10% reinforcing agent of cow glue was applied to protect the gold leaf layer to prevent flaking of the gold leaf layer during wet cleaning, and a 2% reinforcing agent was applied after repair . For wet cleaning, a natural cleaning liquid mixed with cypress extract was used at a concentration of 1.0%. For wet cleaning, a natural cleaning solution mixed with Oriental arborvitae extract was used at a concentration of 1.0%. After cleaning, the artefacts were reinforced and repaired to restore their original shapes, completing the preservation treatment including packaging and storage.

Numerical Simulation, Preparation, and Evaluation of Cu(In, Ga)Se2 (CIGS) Thin-Film Solar Cells

This study presents the numerical simulation, optimization, preparation, and characterization of Cu(In, Ga)Se2 (CIGS) thin-film solar cells (TFSCs). Different cell parameters were investigated, including Ga/(Ga+In) (GGI) ratios, the thicknesses of CIGS absorption layers, the fill factor (FF), the open-circuit voltage (Voc), and the short-circuit current (Isc). The effects of the simulated parameters on the power conversion efficiency (η) of each prototype CIGS cells were investigated. The optimal GGI ratio was approximately 0.6. Using COMSOL Multiphysics software, a CIGS layer thickness of 2 μm and an η of 17% was calculated, assuming constant operating temperatures. Moreover, prototype CIGS solar cells with various compositions were prepared via a simple and cost-effective method based on sol–gel, sonication, and spin-coating techniques. The microstructures and electrical and optical properties of the CIGS-based solar cells were evaluated using current–voltage (I-V) characteristics, scanning electron microscopy (SEM), X-ray diffraction, atomic force microscopy (AFM), and UV-vis spectroscopy. The elemental compositions of the solar cell layers were evaluated via energy-dispersive X-ray fluorescence (EDXRF). The obtained results were compared with the experimental results. For example, in a prototype cell with a CIGS absorption layer thickness of 2 μm and a GGI ratio of 0.6, the experimental value of η was about 15%. Our results revealed that the agreement between the simulation results and the experimental findings for most of the simulated parameters is quite good. These findings indicate that a non-destructive analysis based on EDXRF is a versatile tool for evaluating CIGS solar cells in a very short time with excellent repeatability for both layer composition and thickness.

Effects of wet granulation process variables on the quantitative assay model of transmission Raman spectroscopy for pharmaceutical tablets

Transmission Raman spectroscopy (TRS) is a process analytical technology tool for nondestructive analysis of drug content in tablets. Although wet granulation is the most used tablet manufacturing method, most TRS studies have focused on tablets manufactured via direct compression. The effects of upstream process parameter variations, such as granulation, on the prediction performance of TRS quantitative models are unknown. We evaluated the effects of process parameter variations during granulation on the prediction performance of the TRS quantitative model. Tablets with a drug concentration of 1%w/w were used. We developed PLS calibration models for the drug concentration range of 70–130% label claims. Subsequently, we predicted the drug content of the tablets with different granulation parameters. The results of our study demonstrate that the variation in the predicted recovery due to the variation in granulation parameters was practically acceptable. The calibration model showed a good prediction performance for tablets manufactured at different granulation scales and thicknesses. Therefore, we conclude that TRS quantitative models are robust to variations in upstream processes, such as granulation and downstream variations in tableting parameters. These results suggest that TRS is a versatile non-destructive quantitative analysis method that can be applied in tablet manufacturing.

Quality and physiological evaluation of tomato subjected to different supplemental lighting systems

Light is a crucial mediator in plants of growth and development, secondary metabolism, and signaling of potentially beneficial phytochemicals. The present study investigated three indoor supplemental light treatments, HPS, LED, and LED+IR, applied during tomato cultivation, in which non-destructive and destructive analyses were performed at two time points to record the physiological responses and effects of these artificial lights on the growth and quality of the produce. An infrared thermometer and thermal cameras were used throughout the experiment to record temperature changes under each growing condition. LED+IR supplemented light showed a decrease in photosynthetic pigments, such as chlorophyll a, b, and carotenoids but induced an increased number of flowers, heavier tomato fruits, enhanced anthocyanins, phenolic index, lipid peroxidation, titratable acidity, and reduced nitrate accumulation. Moreover, higher generated temperatures under LED+IR helped tomato plants to reduce white fly infestation, but suppressed plant height. HPS light performed better than both LED and LED+IR in terms of total sugar accumulation, total carotenoids, water content, plant height, and leaf lipid peroxidation at harvest. Lycopene, ß-carotene, brix index were remarkable under HPS lighting but under the same conditions the number of whiteflies, however, was the highest in HPS among all the tested light treatments. In terms of fruit color analysis, maximum redness (a*), reduced hue angle, and chroma were observed under LED+IR while LED lighting in brightness (L*), and HPS in yellowness (b*) were prominent. However, LED in particular was insufficiently effective in acquiring any possible physiological and qualitative characteristics of tomato plants and fruits for the observed time span of the experiment. Hence, LED+IR has been shown to boost the accumulation of bioactive chemicals, improve fruit quality, promote more rapid and early flowering in tomato plants, and can serve as an efficient replacement for traditional indoor illumination.

Rapid detection of maize seed germination rate based on Gaussian process regression with selection kernel function

Near-infrared spectroscopy (NIR) detection technology enables nondestructive analysis of samples. To achieve fast detection of maize seed germination rates using NIR spectroscopy, 245 samples of maize seeds from three different varieties were purchased from the market and subjected to artificial aging to obtain maize seeds with varying levels of vigor. NIR spectroscopy was collected for each sample, and germination experiments were performed. The Monte Carlo cross-validation method was employed to eliminate 12 outliers, and the baseline correction method along with multiplicative scatter correction (MSC) was applied to the NIR. Partial least squares (PLS), support vector machine (SVM) models, and Gaussian process regression (GPR) models based on different kernel functions were established for detecting maize germination rates. Through comparison of the results of different models, it was found that the GPR model based on the Matern32 kernel function performed best. The R² values for the training and testing sets of this model were 0.9727 and 0.9599, respectively. Experimental results showed that the Matern32-GPR model exhibited greater stability and superior capability in detecting maize seed germination rates. This method can provide a reference for other applications based on NIR detection.

An integrated, non-destructive method for evaluating core quality from R/V Legend’s giant piston coring system (LGD-GPC)

Despite technological advances, some core disturbances due to piston coring process still occur and can be extremely difficult to identify characteristics of sedimentary structures during qualitative visual core description and core lithologies. Few quantitative methods have offered plausible ways to define the exact magnitude of the distorted sedimentary structures in imperfect sedimentary records in the context of overly limited sedimentary records. In this study, an investigation was conducted on the Kaoping slope offshore southwestern Taiwan, a region known for its high sedimentation rate (> 0.9 g/cm2/year), using both the LGD-GPC (giant piston corer) and giant gravity corer techniques. To examine how GPC procedures have shaped the retrieval of sedimentary sequences and affected core quality, we apply well-developed, non-destructive analyses, including physical property measurements, visible color reflectance and digital core images with quantitative curvature index (CI), to recovered sediments. Cores at 22° 23′N, 120° 13′E were as the basis for non-destructive measurement comparison. Evidence from digital core imaging and the CI calculation further supports the mechanism of piston suction. We suggest that shear deformation of sediment against the core barrel would be the prominent factor that govern the observed core disturbances in LGD-GPC cores. Meanwhile, excessive pulling forcing from a modified TORI piston and a slowly lift speed during LGD-GPC coring process may further aggravate core disturbances at the revisited site. The sedimentary length of core LGD-T43-B-PC is overestimated by more than 200%. We further demonstrate that an integration of the CI and color reflectance is an effective way to evaluate the transformation and distorted sedimentary sequences.

Variational Mode Decomposition for Raman Spectral Denoising.

As a fast and non-destructive spectroscopic analysis technique, Raman spectroscopy has been widely applied in chemistry. However, noise is usually unavoidable in Raman spectra. Hence, denoising is an important step before Raman spectral analysis. A novel spectral denoising method based on variational mode decomposition (VMD) was introduced to solve the above problem. The spectrum is decomposed into a series of modes (uk) by VMD. Then, the high-frequency noise modes are removed and the remaining modes are reconstructed to obtain the denoised spectrum. The proposed method was verified by two artificial noised signals and two Raman spectra of inorganic materials, i.e., MnCo ISAs/CN and Fe-NCNT. For comparison, empirical mode decomposition (EMD), Savitzky-Golay (SG) smoothing, and discrete wavelet transformation (DWT) are also investigated. At the same time, signal-to-noise ratio (SNR) was introduced as evaluation indicators to verify the performance of the proposed method. The results show that compared with EMD, VMD can significantly improve mode mixing and the endpoint effect. Moreover, the Raman spectrum by VMD denoising is more excellent than that of EMD, SG smoothing and DWT in terms of visualization and SNR. For the small sharp peaks, some information is lost after denoising by EMD, SG smoothing, DWT and VMD while VMD loses fewest information. Therefore, VMD may be an alternative method for Raman spectral denoising.

Experimental comparison between dynamic and static parameters for volcanic rocks in Sulcis basin (Italy)

This work compares the results of expensive and time-consuming destructive tests and cheap non-destructive ultrasonic analyses for the assessment of rock parameters (i.e. uniaxial compressive strength, Young's modulus, Poisson's ratio, etc.), with the aim to geologically characterize the site and to find correlations between the mechanical and acoustic properties of rocks for applications in the field of the monitoring of CO2 leakage. The assessment considers 60 samples, 10 per each of the six formations of the Sulcis Miocene volcanic sequence. Samples have been initially subjected to non-destructive tests for the measurement of density and compressional and shear wave velocity and then mechanically tested to determine the uniaxial strength. As it happens for other kinds of rock, a linear direct correlation has been found between uniaxial compressive strength and compressional wave velocity, as well as between dynamic and static Young's moduli and for the dynamic and static Poisson's ratios, with a correlation coefficient R2 significantly affected by the nature of the pyroclastic formation. Helpful information on the pyroclastic rocks have been obtained, collecting parameters currently not available in the literature for this kind of geological formations.

Tea authentication and determination of chemical constituents using digital image-based fingerprint signatures and chemometrics.

Tea (Camellia sinensis) fraud has been frequently identified and involves tampering with the labelling of inferior products or without geographical origin certification and even mixing them with superior quality teas to mask an adulteration. Consequently, economic losses and health damage to consumers are observed. Thus, a Chemometrics-assisted Color Histogram-based Analytical System (CACHAS) was employed a simple, cost-effective, reliable, and green analytical tool to screen the quality of teas. Data-Driven Soft Independent Modeling of Class Analogy was used to authenticate their geographical origin and category simultaneously, recognizing correctly all Argentinean and Sri Lankan black teas and Argentinean green teas. For the determination of moisture, total polyphenols, and caffeine, Partial Least Squares obtained satisfactory predictive abilities, with values of root mean squared error of prediction (RMSEP) of 0.50, 0.788, and 0.25mgkg-1, rpred of 0.81, 0.902, and 0.81, and relative error of prediction (REP) of 6.38, 9.031, and 14.58%., respectively. CACHAS proved to be a good alternative tool for environmentally-friendly non-destructive chemical analysis.

A Modification of Magnetic Adaptive Testing: Progressive Method for Nondestructive Inspection of Microstructural Changes in Ferromagnetic Constructional Materials

Magnetic adaptive testing (MAT), thanks to its relative simplicity from the point of view of both hardware and software, appears to be very promising for non-destructive analysis of various ferromagnetic constructional materials used in many industrial applications. In order to make the inspection of tested objects faster, even more straightforward and the processing of data easier, we concentrated our effort both to improve the experimental procedure, based on specific way of the measurement of magnetization curves at piece-wise linear (triangular) exciting field with a constant field rate of change (i.e., slope) as well as to create a universal software tool for MAT data analysis. On contrary to the original implementation of MAT, the hysteresis loops are measured with decreasing maximum field values, starting at sample saturation region; therefore, time consuming sample demagnetization can be skipped completely. In addition, an advanced tool for the processing of experimentally obtained magnetization curves is presented. Using this application allows to find proper non-traditional magnetic parameters (e.g., the differential permeability) being the most sensitive to various types of industrial load (e.g., thermal, mechanical and/or neutron irradiation) and, at the same time, sufficiently correlated with other, traditional magnetic as well as non-magnetic parameters used routinely for the assessment of possible structural changes associated with applied, often long-term, load even on a microscopic scale, prior to any damage manifests on a macroscopic, visible level. The software capabilities were demonstrated on the data representing the material, whose response to acting thermal load is being difficult to analyze, since the dependence of observed parameters (differential permeability) upon defined artificial ageing was rather complicated. Nevertheless, the sensitivity of differential permeability to such a load was found being more than 8 times larger than in case of traditional hysteretic parameter, namely the remanent flux density while the correlation between them was high.

The 2023 Emerging Leader in Molecular Spectroscopy Award

This year’s Emerging Leader in Molecular Spectroscopy Award recipient is Dmitry Kurouski, an assistant professor of chemistry at the Texas A&M University in College Station, Texas. From his early research days as a graduate student at State University of New York in Albany, Kurouski’s research has emphasized the development and application of innovative Raman spectroscopy methods for noninvasive, nondestructive analyses of biological materials.