Spatially Offset Raman Spectroscopy Combined with Attention-Based LSTM for Freshness Evaluation of Shrimp.

Optical detection of the freshness of intact in-shell shrimps is a well-known difficult task due to shell occlusion and its signal interference. The spatially offset Raman spectroscopy (SORS) is a workable technical solution for identifying and extracting subsurface shrimp meat information by collecting Raman scattering images at different distances from the offset laser incidence point. However, the SORS technology still suffers from physical information loss, difficulties in determining the optimum offset distance, and human operational errors. Thus, this paper presents a shrimp freshness detection method using spatially offset Raman spectroscopy combined with a targeted attention-based long short-term memory network (attention-based LSTM). The proposed attention-based LSTM model uses the LSTM module to extract physical and chemical composition information of tissue, weight the output of each module by an attention mechanism, and come together as a fully connected (FC) module for feature fusion and storage dates prediction. Modeling predictions by collecting Raman scattering images of 100 shrimps within 7 days. The R2, RMSE, and RPD of the attention-based LSTM model achieved 0.93, 0.48, and 4.06, respectively, which is superior to the conventional machine learning algorithm with manual selection of the optimal spatially offset distance. This method of automatically extracting information from SORS data by Attention-based LSTM eliminates human error and enables fast and non-destructive quality inspection of in-shell shrimp.

Evaluating Spatially Offset Low-Frequency Anti-Stokes Raman Spectroscopy (SOLFARS) for Detecting Subsurface Composition below an Emissive Layer: A Proof of Principle Study Using a Model Bilayer System.

This work explores the potential use of spatially offset low-frequency anti-Stokes Raman spectroscopy (SOLFARS) to detect subsurface composition below an emissive surface. A range of bilayer tablets were used to evaluate this approach. Bilayer tablets differed in both the underlying layer composition (active pharmaceutical ingredient to excipient ratio, celecoxib: α-lactose monohydrate) and the upper layer thickness of the fluorescent coating (polyvinylpyrrolidone mixture with sunset yellow FCF dye). Two low- (<300 cm-1) plus mid- (300 to 1800 cm-1) frequency Raman instrumental setups, with lateral displacements for spatial analysis of solid dosage forms, using different excitation wavelengths were explored. The 532 nm system was used to illustrate how the low-frequency anti-Stokes Raman approach works with samples exhibiting extreme fluorescence/background emission interference, and the 785 nm system was used to demonstrate the performance when less extreme fluorescence/emission is present. Qualitative and quantitative chemometric analyses were performed to evaluate the performance of individual spectral domains and their combinations for the determination of the composition of the subsurface layer as well as the coating layer thickness. Overall, the commonly used midfrequency region (300-1800 cm-1) proved superior when using 785 nm incident laser for quantifying the coating thickness (amorphous materials), whereas a combined Stokes and anti-Stokes low-frequency region was found to be superior for quantifying underlying crystalline materials. When exploring individual spectral regions for subsurface composition using spatially offset measurements, the anti-Stokes LFR spectral window performed best. The anti-Stokes low-frequency range also demonstrated an advantage for models composed of data exhibiting high levels of fluorescence (e.g., data collected using 532 nm incident laser), as the Stokes scattering was masked by fluorescence. Transmission measurements were also explored for comparison and showed the best applicability for both upper and lower layer analysis, attributed to the inherently larger bulk sampling volume of this setup. From a practical perspective, these results highlight the potential adjustments that can be made to already existing (in-line) Raman setups to facilitate similar analysis in pharmaceutical industry-based settings.

Spatial Heterodyne Offset Raman Spectroscopy Enabling Rapid, High Sensitivity Characterization of Materials' Interfaces.

Spatially offset Raman spectroscopy is integrated with a fiber-coupled spatial heterodyne spectrometer to collect Raman spectra from deep within opaque or scattering materials. The method, named spatial heterodyne offset Raman spectroscopy generates a wavenumber-dependent spatial phase shift of the optical signal as a "spectral" image on a charge-coupled device detector. The image can be readily processed from the spatial domain using a single, simple, and "on-the-fly" Fourier transform to generate Raman spectra, in the frequency domain. By collecting all of the spatially offset Raman scattered photons that pass through the microscope's collection objective lens, the methodology gives an improvement in the Raman sensitivity by an order of magnitude. The instrumentation is both mechanically robust and "movement-free," which when coupled with the associated advantages of highly efficient signal collection and ease of data processing, enables rapid interfacial analysis of complex constructs based on established biomaterials models.

Non-invasive monitoring of red blood cells during cold storage using handheld Raman spectroscopy.

BACKGROUND: The current best practices allow for the red blood cells (RBCs) to be stored for prolonged periods in blood banks worldwide. However, due to the individual-related variability in donated blood and RBCs continual degradation within transfusion bags, the quality of stored blood varies considerably. There is currently no method for assessing the blood product quality without compromising the sterility of the unit. This study demonstrates the feasibility of monitoring storage lesion of RBCs in situ while maintaining sterility using an optical approach. STUDY DESIGN AND METHODS: A handheld spatially offset Raman spectroscopy (RS) device was employed to non-invasively monitor hemolysis and metabolic changes in 12 red cell concentrate (RCC) units within standard sealed transfusion bags over 7 weeks of cold storage. The donated blood was analyzed in parallel by biochemical (chemical analysis, spectrophotometry, hematology analysis) and RS measurements, which were then correlated through multisource correlation analysis. RESULTS: Raman bands of lactate (857 cm-1 ), glucose (787 cm-1 ), and hemolysis (1003 cm-1 ) were found to correlate strongly with bioanalytical data over the length of storage, with correlation values 0.98 (95% confidence interval [CI]: 0.86-1.00; p = .0001), 0.95 (95% CI: 0.71-0.99; p = .0008) and 0.97 (95% CI: 0.79-1.00; p = .0004) respectively. DISCUSSION: This study demonstrates the potential of collecting information on the clinical quality of blood units without breaching the sterility using Raman technology. This could significantly benefit quality control of RCC units, patient safety and inventory management in blood banks and hospitals.

Current and Future Advancements of Raman Spectroscopy Techniques in Cancer Nanomedicine.

Raman scattering is one of the most used spectroscopy and imaging techniques in cancer nanomedicine due to its high spatial resolution, high chemical specificity, and multiplexity modalities. The flexibility of Raman techniques has led, in the past few years, to the rapid development of Raman spectroscopy and imaging for nanodiagnostics, nanotherapy, and nanotheranostics. This review focuses on the applications of spontaneous Raman spectroscopy and bioimaging to cancer nanotheranostics and their coupling to a variety of diagnostic/therapy methods to create nanoparticle-free theranostic systems for cancer diagnostics and therapy. Recent implementations of confocal Raman spectroscopy that led to the development of platforms for monitoring the therapeutic effects of anticancer drugs in vitro and in vivo are also reviewed. Another Raman technique that is largely employed in cancer nanomedicine, due to its ability to enhance the Raman signal, is surface-enhanced Raman spectroscopy (SERS). This review also explores the applications of the different types of SERS, such as SERRS and SORS, to cancer diagnosis through SERS nanoprobes and the detection of small-size biomarkers, such as exosomes. SERS cancer immunotherapy and immuno-SERS (iSERS) microscopy are reviewed.

A Spatially Offset Raman Spectroscopy Method for Non-Destructive Detection of Gelatin-Encapsulated Powders.

Non-destructive subsurface detection of encapsulated, coated, or seal-packaged foods and pharmaceuticals can help prevent distribution and consumption of counterfeit or hazardous products. This study used a Spatially Offset Raman Spectroscopy (SORS) method to detect and identify urea, ibuprofen, and acetaminophen powders contained within one or more (up to eight) layers of gelatin capsules to demonstrate subsurface chemical detection and identification. A 785-nm point-scan Raman spectroscopy system was used to acquire spatially offset Raman spectra for an offset range of 0 to 10 mm from the surfaces of 24 encapsulated samples, using a step size of 0.1 mm to obtain 101 spectral measurements per sample. As the offset distance was increased, the spectral contribution from the subsurface powder gradually outweighed that of the surface capsule layers, allowing for detection of the encapsulated powders. Containing mixed contributions from the powder and capsule, the SORS spectra for each sample were resolved into pure component spectra using self-modeling mixture analysis (SMA) and the corresponding components were identified using spectral information divergence values. As demonstrated here for detecting chemicals contained inside thick capsule layers, this SORS measurement technique coupled with SMA has the potential to be a reliable non-destructive method for subsurface inspection and authentication of foods, health supplements, and pharmaceutical products that are prepared or packaged with semi-transparent materials.

Theoretical and Practical Considerations of Spatially Offset Raman Spectroscopy (SORS) and Micro-SORS.

Spatially offset Raman spectroscopy (SORS) is typically used to non-invasively investigate stratified samples that possess features on a millimeter scale, whereas micro-SORS usually deals with micrometer-thick layered samples. However, there are many instances where these boundaries are intertwined, sometimes indicating the possibility of using both techniques as well as circumstances that present mutual exclusion to their applicability. The aim of this study is to establish an application protocol that provides better insight into their suitability for deployment in various scenarios. The differences and similarities between the two approaches are investigated highlighting their strengths and limitations considering both theoretical and practical aspects. Diverse available parameters entail prospects and restrictions of both techniques and give rise to specific instrumental effects, namely, the overlap between the collection and excitation areas, the percentage of collected area for a given spatial offset, and the accuracy in the definition of the spatial offset (spread effect). These aspects are studied and exemplified on mockup samples relevant to the field of cultural heritage. The samples are characterized by high compositional complexity comprising features ranging from micrometer to millimeter scales. The conclusions reached are also relevant to other scientific areas such as biomedical, forensic, or energy harvest.

Determining ideal offsets of spatially offset Raman spectroscopy for transcutaneous measurements-A Monte Carlo study.

Spatially offset Raman spectroscopy (SORS) is valuable for noninvasive bone assessment but requires a clearer understanding of how offset distances influence detection depth. To address this, our study devised a forward-adjoint Monte Carlo multi-layer (MCML) model to simulate photon paths in SORS, aiming to determine optimal offsets for various tissue types. We examined photon migration at offsets between 0 and 15 mm against layered phantoms of differing thicknesses and compositions to optimize the signal-to-noise ratio for bone layers. The findings highlight that optimal offsets are contingent on tissue characteristics: a metacarpal beneath 2.5 mm of tissue had an ideal offset of 6.7 mm, while a tibia with 5 mm of soft tissue required 10-11 mm. This precise calibration of SORS via MCML modeling promises substantial improvements in bone health diagnostics and potential for expansive medical applications.

Active Surface-Enhanced Raman Spectroscopy (SERS): A Novel Concept for Enhancing Signal Contrast in Complex Matrices Using External Perturbation.

Noninvasive detection of surface-enhanced Raman spectroscopy (SERS) signals from deep within tissue represents a common challenge in many biological and clinical applications including disease diagnosis and therapy monitoring. Such signals are typically weak and not readily discernible from often much larger Raman and fluorescence background signals (e.g., from surrounding tissue). Consequently, suboptimal sensitivity in the detection of SERS signals is often achieved in these situations. Similar issues can arise in SERS measurements in other diffusely scattering samples and complex matrices. Here, we propose a novel concept, active SERS, for the efficient retrieval of SERS signals from deep within complex matrices such as biological tissues that mitigates these issues. It relies on applying an external perturbation to the sample to alter the SERS signal from nanoparticles (NPs) deep inside the matrix. A measurement with and without, or before and after, such perturbation then can provide powerful contrasting data enabling an effective elimination of the matrix signals to reveal more clearly the desired SERS signal without the interfering background and associated artifacts. The concept is demonstrated using ultrasound (US) as an external source of perturbation and SERS NPs inserted deep within a heterogeneous tissue phantom mimicking a cluster of NPs accumulated within a small target lesion. The overall SERS signal intensity induced by the applied US perturbation decreased by ∼21% and the SERS signal contrast was considerably improved by eliminating subtraction artifacts present in a conventional measurement performed at a neighboring spatial location in a heterogeneous tissue sample. Although the technique was demonstrated with SERS gold NPs with a standard Raman label, it is envisaged that active SERS NPs (both the nanoscale metal geometry and Raman label) could be specifically designed to deliver an augmented response to the external stimulus to further enhance the achievable SERS signal contrast and yield even greater improvement in detection sensitivity. The method was demonstrated using transmission Raman spectroscopy; however, it is also applicable to other Raman implementations including spatially offset Raman spectroscopy and conventional Raman spectroscopy performed both at depth and at surfaces of complex matrices.

Surface-Enhanced Spatially Offset Raman Spectroscopy in Tissue.

One aim of personalized medicine is to use continuous or on-demand monitoring of metabolites to adjust prescription dosages in real time. Surface-enhanced spatially offset Raman spectroscopy (SESORS) is an optical technique capable of detecting surface-enhanced Raman spectroscopy (SERS)-active targets under a barrier, which may enable frequent metabolite monitoring. Here we investigate how the intensity of the signal from SERS-active material varies spatially through tissue, both experimentally and in a computational model. Implant-sized, SERS-active hydrogel was placed under different thicknesses of contiguous tissue. Emission spectra were collected at the air-tissue boundary over a range of offsets from the excitation site. New features were added to the Monte Carlo light-tissue interaction model to modify the optical properties after inelastic scattering and to calculate the distribution of photons as they exit the model. The Raman signals were detectable through all barrier thicknesses, with strongest emission for the case of 0 mm offset between the excitation and detector. A steep decline in the signal intensities occurred for offsets greater than 2 mm. These results did not match published SORS work (where targets were much larger than an implant). However, the model and experimental results agree in showing the greatest intensities at 0 mm offset and a steep gradient in the intensities with increasing offset. Also, the model showed an increase in the number of photons when the new, longer wavelengths were used following the Stokes shift for scattering and the graphical display of the exiting photons was helpful in the determination and confirmation of the optimal offset.

Innovative method for rapid detection of falsified COVID-19 vaccines through unopened vials using handheld Spatially Offset Raman Spectroscopy (SORS).

Preventing, detecting, and responding to substandard and falsified vaccines is of critical importance for ensuring the safety, efficacy, and public trust in vaccines. This is of heightened importance in context of public health crisis, such as the COVID-19 pandemic, in which extreme world-wide shortages of vaccines provided a fertile ground for exploitation by falsifiers. Here, a proof-of-concept study explored the feasibility of using a handheld Spatially Offset Raman Spectroscopy (SORS) device to authenticate COVID-19 vaccines through rapid analysis of unopened vaccine vials. The results show that SORS can verify the chemical identity of dominant excipients non-invasively through vaccine vial walls. The ability of SORS to identify potentially falsified COVID-19 vaccines was demonstrated by measurement of surrogates for falsified vaccines contained in vaccine vials. In all cases studied, the SORS technique was able to differentiate between surrogate samples from the genuine COVISHIELD™ vaccine. The genuine vaccines tested included samples from six batches across two manufacturing sites to account for any potential variations between batches or manufacturing sites. Batch and manufacturing site variations were insignificant. In conjunction with existing security features, for example on labels and packaging, SORS provided an intrinsic molecular fingerprint of the dominant excipients of the vaccines. The technique could be extended to other COVID-19 and non-COVID-19 vaccines, as well as other liquid medicines. As handheld and portable SORS devices are commercially available and widely used for other purposes, such as airport security, they are rapidly deployable non-invasive screening tools for vaccine authentication.

Locating Three-Dimensional Position of Deep-Seated SERS Phantom Lesions in Thick Tissues Using Tomographic Transmission Raman Spectroscopy.

Locating distinct objects within a thick scattering medium remains a long-standing challenge in the fields of materials science, health, and engineering. Transmission Raman spectroscopy (TRS) with the use of surface-enhanced Raman scattering (SERS) nanoparticles has proven to be an effective approach to detect deep-seated lesions inside thick biological tissues. However, it has not yet been proven to spatially locate deep lesions in three dimensions using optical modalities. Herein, we present the concept of tomographic TRS and report its successful use for accurately locating SERS nanoparticles in elongated rod-like thick tissues. Our work starts with theoretical simulations of Raman photon propagation in tissues. We discovered a linear relationship between the Raman spectral peak ratio and propagation distance of Raman photons in tissues, allowing us to predict the location of lesions tagged by SERS NPs. Based on this, we propose a two-step tomographic TRS strategy, which includes axial scanning and ring scanning. We demonstrate the robustness of our approach using ex vivo thick tissue (4.5 cm in thickness) and locate an embedded SERS phantom lesion, with a ring scanning step of 10-30°. We successfully locate multiple SERS phantom lesions in the ex vivo porcine muscle stack with high accuracy (absolute error of <2 mm). Our method is rapid, efficient, and of low cost compared to current tomographic medical imaging techniques. This work advances Raman techniques for three-dimensional positioning and offers new insights toward practical diagnosis applications.

Non-Invasive Detection, Precise Localization, and Perioperative Navigation of In Vivo Deep Lesions Using Transmission Raman Spectroscopy.

Non-invasive detection and precise localization of deep lesions have attracted significant attention for both fundamental and clinical studies. Optical modality techniques are promising with high sensitivity and molecular specificity, but are limited by shallow tissue penetration and the failure to accurately determine lesion depth. Here the authors report in vivo ratiometric surface-enhanced transmission Raman spectroscopy (SETRS) for non-invasive localization and perioperative surgery navigation of deep sentinel lymph nodes in live rats. The SETRS system uses ultrabright surface-enhanced Raman spectroscopy (SERS) nanoparticles with a low detection limit of 10 pM and a home-built photosafe transmission Raman spectroscopy setup. The ratiometric SETRS strategy is proposed based on the ratio of multiple Raman spectral peaks for obtaining lesion depth. Via this strategy, the depth of the phantom lesions in ex vivo rat tissues is precisely determined with a mean-absolute-percentage-error of 11.8%, and the accurate localization of a 6-mm-deep rat popliteal lymph node is achieved. The feasibility of ratiometric SETRS allows the successful perioperative navigation of in vivo lymph node biopsy surgery in live rats under clinically safe laser irradiance. This study represents a significant step toward the clinical translation of TRS techniques, providing new insights for the design and implementation of in vivo SERS applications.

Model-Based Optimization of Laser Excitation and Detection Improves Spectral Contrast in Noninvasive Diffuse Raman Spectroscopy.

Spatially offset Raman spectroscopy (SORS) is a powerful technique for subsurface molecular analysis of optically turbid samples. Numerical modeling of light propagation has been used to investigate opportunities for improving spectral contrast and signal to noise ratio when imaging regions of interest located 0-4.5 mm below the surface in polymer bulk material. Two- and three-dimensional modeling results demonstrate that when analyzing a certain region of interest (ROI) of finite lateral dimensions below the sample surface, offsetting both the laser source and detector in opposite directions from the central point of the ROI can increase the spectral contrast as compared to conventional SORS approach where the detector or the laser source is maintained at the central point (centered SORS). The outlined modeling results have been validated experimentally using a bulk polymer sample with a trans-stilbene ROI (cylinder) below the sample surface. The results show that modeling of the spatial configurations of laser excitation and detection points can be used to optimize the instrument configuration to achieve significant improvements (up to 2.25-fold) in performance over the conventional centered SORS. Such optimal solutions can then be implemented, for example, using robust fiber optic probes, moveable optics, or flexible spatial light modulator instruments for specific applications.

Assessing the quality of stored red blood cells using handheld Spatially Offset Raman spectroscopy with multisource correlation analysis.

In this work we employ Spatially Offset Raman Spectroscopy (SORS) to non-invasively identify storage-related changes in red blood cell concentrate (RCC) in-situ within standard plastic transfusion bags. To validate the measurements, we set up a parallel study comparing both bioanalytical data (obtained by blood-gas analysis, hematology analysis and spectrophotometric assays), and Raman spectrometry data from the same blood samples. We then employ Multisource Correlation Analysis (MuSCA) to correlate the different types of data in RCC. Our analysis confirmed a strong correlation of glucose, methemoglobin and oxyhemoglobin with their respective bioassay values in RCC units. Finally, by combining MuSCA with k-means clustering, we assessed changes in all Raman wavenumbers during cold storage in both RCC Raman data from the current study and parallel RCC supernatant Raman data previously acquired from the same units. Direct RCC quality monitoring during storage, would help to establish a basis for improved inventory management of blood products in blood banks and hospitals based on analytical data.

Sub-Surface Molecular Analysis and Imaging in Turbid Media Using Time-Gated Raman Spectral Multiplexing.

Obtaining molecular information deeper within optically turbid samples is valuable in many applications. However, in many cases this is challenging, in particular when the sample elicits strong laser-induced fluorescence emission. Here, we investigated the use of time-gated and micro-spatially offset Raman spectroscopy (micro-SORS) based on spectral multiplexing detection to obtain sub-surface molecular analysis and imaging for both fluorescing and non-fluorescing samples. The multiplexed spectral detection achieved with a digital micromirror device (DMD) allowed fast acquisition of the time-gated signals to enable three-dimensional Raman mapping (raster scanning in the lateral x,y plane and using time-of-flight calibration for the axial z-direction). Sub-millimeter resolution molecular depth mapping was achieved with dwell times on the order of seconds per pixel. To suppress fluorescence backgrounds and enhance Raman bands, time-gated Raman spectroscopy was combined with micro-SORS to recover Raman signals of red pigments placed behind a layer of optically turbid material. Using a defocusing micro-SORS approach, both fluorescence and Raman signals from the surface layers were further suppressed, which enhanced the Raman signals from the deeper sublayers containing the pigment. These results demonstrate that time-gated Raman spectroscopy based on spectral multiplexed detection, and in combination with micro-SORS, is a powerful technique for sub-surface molecular analysis and imaging, which may find practical applications in medical imaging, cultural heritage, forensics, and industry.

A Semi-quantitative method for the detection of fentanyl using surface-enhanced Raman scattering (SERS) with a handheld Raman instrument.

A handheld, spatially offset Raman spectroscopy (SORS) system was successfully used to obtain Surface-enhanced Raman Scattering (SERS) spectra of fentanyl under simulated field conditions. A series of aqueous fentanyl solutions were prepared with commercially available gold nanoparticle solution, at concentrations ranging from 0.003 to 1697 µM. These SERS spectra were then used to generate two concentration calibration models (via a plot of peak area (1026 cm-1 ) versus concentration, and quantitative spectral decomposition using partial least squares (PLS1)). For both models, the relationship followed Langmuir adsorption and became non-linear at concentrations above ~0.2 µM, with a limit of detection (LOD) of approximately 3 nM. The same technique was successfully used to measure fentanyl in the presence of two common "cutting agents," heroin and glucose, at 1% and 2% fentanyl proportions (w/w). Fentanyl detection was successfully achieved, but mixture interference from the cutting agents prevented a calibration model being generated. Four fentanyl analogues were also investigated-butyrylfentanyl, furanylfentanyl, acetylfentanyl, and ocfentanyl. A concentration calibration model for each species was successfully generated, but differentiation from fentanyl proved more challenging, although several potential diagnostic peaks were identified. These results identified a pathway forward in using handheld equipment for the reliable detection of ultra-low concentrations of fentanyl and fentanyl analogues via SERS, even when mixed with diluents. However, quantitative detection is negatively impacted in the presence of heroin and glucose. This also provides a starting point for a SERS-based spectral library of fentanyl analogues, in combination with a range of different diluents.

The Role of Raman Spectroscopy Within Quantitative Metabolomics.

Ninety-four years have passed since the discovery of the Raman effect, and there are currently more than 25 different types of Raman-based techniques. The past two decades have witnessed the blossoming of Raman spectroscopy as a powerful physicochemical technique with broad applications within the life sciences. In this review, we critique the use of Raman spectroscopy as a tool for quantitative metabolomics. We overview recent developments of Raman spectroscopy for identification and quantification of disease biomarkers in liquid biopsies, with a focus on the recent advances within surface-enhanced Raman scattering-based methods. Ultimately, we discuss the applications of imaging modalities based on Raman scattering as label-free methods to study the abundance and distribution of biomolecules in cells and tissues, including mammalian, algal, and bacterial cells.

Soft-tissue spectral subtraction improves transcutaneous Raman estimates of murine bone strength in vivo.

Transcutaneous determination of a bone's Raman spectrum is challenging because the type I collagen in the overlying soft tissue is spectroscopically identical to that in bone. In a previous transcutaneous study of murine tibiae, we developed a library-based model called SOLD to unmix spatially offset Raman measurements into three spectra: a bone estimate, a soft tissue estimate, and a residual. Here, we demonstrate the value of combining the bone estimate and the residual to produce a "top layer subtracted" (tls) spectrum. We report superior prediction of two standard bone metrics (volumetric bone mineralization density and maximum torque) using partial least squares regression models based upon tls spectra rather than SOLD bone estimates, implying that the spectral residuals contain useful information. Simulations reinforce experimental in vivo findings. This chemometric approach, which we denote as SOLD/TLS, could have broad applicability in situations where comprehensive spectral libraries are difficult to acquire.

Non-invasive characterisation of molecular diffusion of agent into turbid matrix using micro-SORS.

This study proposes a non-invasive analytical method to study the molecular diffusion of a chemical agent into a turbid matrix with an emerging analytical technique, micro-Spatially Offset Raman Spectroscopy (micro-SORS). Here, the micro-SORS concept has been extended from the analysis of chemically distinct stratified layers to the studies and monitoring of the absorption and diffusion processes, addressing a key analytical need in a number of areas including polymer, pharmaceutical, forensic and biomedical sciences. In Cultural Heritage the knowledge of the penetration depth of a polymer used to consolidate or to protect an object, or the absorption depth of solvents used during a cleaning procedure is crucial for the performance evaluation of restoration methods and their safety towards the work of art. To date the most common protocol for obtaining this type of information comprises the application of stratigraphical analysis on cross-sections prepared after taking a small amount of sample from the work of art. This approach is destructive and may lack of statistical meaning, since the analytical information is limited to the micro area of sampling. To overcome these drawbacks, in this study micro-SORS was successfully used, for the first time, to non-invasively characterise the penetration of a polymer and of a viscous solvent into a gypsum substrate, permitting the reconstruction of the diffusion trends of the products into the matrix and the evaluation of their performances.