Extraction of Chemical Information of Suspensions Using Radiative Transfer Theory To Remove Multiple Scattering Effects: Application to a Model Multicomponent System

Intensity correlation scan (IC-scan) technique to characterize the optical nonlinearities of scattering media

Light scattering, whether caused by desired or spurious elements, is considered one of the main phenomena that present great challenges for the nonlinear (NL) optical characterization of turbid media. The most relevant disturbing factor is the random deformation suffered by the spatial intensity distribution of the laser beam due to multiple scattering. In this work, we report the intensity correlation scan (IC-scan) technique as a new tool to characterize the NL optical response of scattering media, by taking advantage of light scattering to generate speckle patterns sensitive to wavefront changes induced by the self-focusing and self-defocusing effects. Peak-to-valley transmittance curves, with a higher signal-to-noise ratio, are obtained by analyzing the spatial intensity correlation functions of the different speckle patterns, even in very turbid media where conventional NL spectroscopy techniques fail. To demonstrate the potential of the IC-scan technique, the NL characterization of colloids that contain a high concentration of silica nanospheres as scatterers, as well as gold nanorods, which act as NL particles and light scatterers, was performed. The results show that the IC-scan technique is more accurate, precise and robust to measure NL refractive indices in turbid media, overcoming limitations imposed by well-established Z-scan and D4σ techniques.

Discriminating between Absorption and Scattering Effects in Complex Turbid Media by Coupling Polarized Light Spectroscopy with the Mueller Matrix Concept

The separation of the combined effects of absorption and scattering in complex media is a major issue for better characterization and prediction of media properties. In this study, an approach coupling polarized light spectroscopy and the Mueller matrix concept were evaluated to address this issue. A set of 50 turbid liquid optical phantoms with different levels of scattering and absorption properties were made and measured at various orientations of polarizers and analyzers to obtain the 16 elements of the complete Mueller matrix in the VIS-NIR region. Partial least square (PLS) was performed to build calibration models from diffuse reflectance spectra in order to evaluate the potential of polarization spectroscopy through the elements of the Mueller matrix to predict physical and chemical parameters and hence, to discriminate scattering and absorption effects, respectively. In particular, it was demonstrated that absorption and scattering effects can be distinguished in the Rayleigh regime with linear and circular polarization from the M₂₂ and M₄₄ elements of the Mueller matrix, correspondingly.

In-situ quantitative monitoring the organic contaminants uptake onto suspended microplastics in aquatic environments

Microplastics act as a source of organic contaminants in aquatic environments and thus affect their environmental fate and toxicity. Because of the weak and reversible interactions between microplastics and organic species, the organic coronas vary with their surrounding environments. Thus, in order to evaluate the possible environmental risks of microplastics, methods for evaluating the dynamic uptake of organic contaminants onto suspended microplastics in aquatic environments are greatly desired. In this work, a UV-vis spectroscopy-based approach was developed for in-situ monitoring organic contaminants uptake onto suspended microplastics after correcting the light scattering interference from microplastics suspensions and establishing the nonlinear relationship between concentration and light absorbance of organic species. The inverse adding-doubling method based on radiative transfer theory was adopted to correct the light scattering effect of suspensions. Then, the resulting mixed absorption spectra were decomposed to calculate the concentrations of the aqueous and adsorbed organic species simultaneously with a nonlinear calibration method. The uptake processes of bisphenol A and p-nitrophenol onto nylon 66 microparticles were monitored with this approach and confirmed by high-performance liquid chromatography analysis. The approach was validated by applying it to natural water samples, and the equilibrium adsorption capacity was found to be interfered mainly by the protein-like substances. This approach has high accuracy, good reproducibility, remarkable universality, and ease of handling, and also provides a potential tool for characterizing the corona formation process on suspended particles both in natural and artificial environments, such as eco-corona formation and engineering surface modification on nano/micro-particles.

Combining light polarization and speckle measurements with multivariate analysis to predict bulk optical properties of turbid media

This study aims to investigate the combination of speckle pattern analysis, polarization parameters, and chemometric tools to predict the optical absorption and scattering properties of materials. For this purpose, an optical setup based on light polarization and speckle measurements was developed, and turbid samples were measured at 405 and 660 nm. First, a backscattered polarized speckle acquisition was performed on a set of 41 samples with various scattering (${\mu}_s$μ_s) and absorbing (${{\mu}_a}$μ_a) coefficients. Then, several parameters were computed from the polarized speckle images, and prediction models were built using stepwise multiple linear regression. For scattering media, ${{\mu}_s}$μ_s was predicted with ${R^{2} = 0.9}$R²=0.9 using two parameters. In the case of scattering and absorbing media, prediction results using two parameters were ${R^{2} = 0.62}$R²=0.62 for ${{\mu}_s}$μ_s and ${R^{2} = 0.8}$R²=0.8 for ${{\mu}_a}$μ_a. The overall results obtained in this research showed that the combination of speckle pattern analysis, polarization parameters, and chemometric tools to predict the optical bulk properties of materials show interesting promise.

Estimation of Particle Size Distribution from Bulk Scattering Spectra: Validation on Monomodal Suspensions

A particle size distribution (PSD) estimation method based on light-scattering properties was validated on experimental visible/near-infrared scattering spectra of polystyrene suspensions, with a nominal particle size ranging from 0.1 to 12 μm in diameter. On the basis of μ_s and g spectra extracted from double integrating sphere measurements, good PSD estimates were obtained for particles ≥1 μm. The particle volume fraction estimates in the case of μ_s were close to the target concentrations, although influenced by small baseline fluctuations on the spectra. For submicrometer particles, on the other hand, the non-oscillating μ_s spectra lack discriminating power, resulting in erroneous PSD estimates. The reduced scattering coefficient spectra (μ_s') were found less useful for particle size estimation as they lack a characteristic shape, causing an over- or underestimation of the distribution width. In summary, the estimation routine proved to deliver PSD estimates in line with the reference measurements for micrometer-sized or larger particles based on their μ_s and g scattering spectra. Additional validation on more polydisperse samples forms the next step before going to bimodal PSD estimates.

Estimation of particle size distributions from bulk scattering spectra: sensitivity to distribution type and spectral noise

A shape dependent method for particle size distribution (PSD) estimation based on bulk scattering properties was elaborated. This method estimates the parameters of a particle size distribution with predefined shape from the bulk scattering spectra. The estimation routine was validated on simulated data of polystyrene in water suspensions. To investigate the effect of measurement errors on PSD estimates, a sensitivity analysis was performed. The influence of spectral resolution and range was rather limited. Good PSD estimations were obtained on noise-free spectra, spectra with limited random noise and for estimations on μs or μs' in case of a multiplicative baseline. However, the PSD estimation deteriorated if an incorrect value for the refractive index of the particle relative to the medium was used as input parameter. Deviations caused by an incorrect distribution type were smaller for more narrow PSDs than for broader ones. Overall, this study showed the potential to estimate PSDs from bulk scattering spectra and indicated the factors affecting the accuracy.

Spatially and angularly resolved spectroscopy for in-situ estimation of concentration and particle size in colloidal suspensions

Successful implementation of process analytical technology (PAT) hinges on the ability to make continuous or frequent measurements in-line or at-line of critical product attributes such as composition and particle size, the latter being an important parameter for particulate processes such as suspensions and emulsions. A novel probe-based spatially and angularly-resolved diffuse reflectance measurement (SAR-DRM) system is proposed. This instrument, along with appropriate calibration models, is designed for online monitoring of concentration of chemical species and particle size of the particulate species in process systems involving colloidal suspensions. This measurement system was investigated using polystyrene suspensions of various particle radius and concentration to evaluate its performance in terms of the information obtained from the novel configuration which allows the measurement of a combination of incident light at different angles and collection fibres at different distances from the source fibres. Different strategies of processing and combining the SAR-DRM measurements were considered in terms of the impact on partial least squares (PLS) model performance. The results were compared with those obtained using a bench-top instrument which was used as the reference (off-line) instrument for comparison purposes. The SAR-DRM system showed similar performance to the bench top reference instrument for estimation of particle radius, and outperforms the reference instrument in estimating particle concentration. The investigation shows that the improvement in PLS regression model performance using the SAR-DRM system is related to the extra information captured by the SAR-DRM configuration. The differences in SAR-DRM spectra collected by the different collection fibres from different angular source fibres are the dominant reason for the significant improvement in the model performance. The promising results from this study suggest the potential of the SAR-DRM system as an online monitoring tool for processes involving suspensions. Graphical abstract A probe designed to acquire diffuse reflectance measurements at different source-detector distances for three incidence angles 0°, 30° and 45° was used to estimate particle size and concentration of polystyrene beads in aqueous suspension using partial least squares calibration models.

A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance

Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant role in the calibration while wavelength selection plays a marginal role and the combination of certain pre-processing, wavelength selection, and nonlinear regression methods can achieve superior performance over traditional linear regression-based calibration.

Potential of vis-NIR spectroscopy to monitor the silica precipitation reaction

Controlling production online is an important issue for chemical companies. Visible and near-infrared (NIR) spectroscopy offers a number of important advantages for process monitoring, and has been used since the 1980s. For complex media such as silica precipitation samples, it is interesting to be able to study independently the scattering and absorption effects. From the scattering coefficient it is possible to extract information on the physical structure of the medium. In this work, the physical changes were monitored during a silica precipitation reaction by simple measurement of collimated transmittance NIR spectra. It is shown that it is possible to differentiate samples before and after the gel point, which is a key parameter for monitoring the process. From these NIR spectra the scattering coefficients were simply extracted, allowing a global vision of the physical changes in the medium. Then principal component analysis of the spectra allowed refinement of the understanding of the scattering effects, in combination with particle size monitoring.

Simulation Method Linking Dense Microalgal Culture Spectral Properties in the 400-750 nm Range to the Physiology of the Cells

This work describes a method to model the optical properties over the (400-750 nm) spectral range of a dense microalgal culture using the chemical and physical properties of the algal cells. The method was based on a specific program called AlgaSim coupled with the adding-doubling method: at the individual cell scale, AlgaSim simulates the spectral properties of one model, three-layer spherical algal cell from its size and chemical composition. As a second step, the adding-doubling method makes it possible to retrieve the total transmittance of the algal medium from the optical properties of the individual algal cells. The method was tested by comparing the simulated total transmittance spectra for dense marine microalgal cultures of Isochrysis galbana (small flagellates) and Phaeodactylum tricornutum (diatoms) to spectra measured using an experimental spectrophotometric setup. Our study revealed that the total transmittance spectra simulated for the quasi-spherical cells of Isochrysis galbana were in good agreement with the measured spectra over the whole spectral range. For Phaeodactylum tricornutum, large differences between simulated and measured spectra were observed over the blue part of the transmittance spectra, probably due to non-spherical shape of the algal cells. Prediction of the algal cell density, mean size and pigment composition from the total transmittance spectra measured on algal samples was also investigated using the reversal of the method. Mean cell size was successfully predicted for both species. The cell density was also successfully predicted for spherical Isochrysis galbana, with a relative error below 7%, but not for elongated Phaeodactylum tricornutum with a relative error up to 26%. The pigments total quantity and composition, the carotenoids:chlorophyll ratio in particular, were also successfully predicted for Isochrysis galbana with a relative error below 8%. However, the pigment predictions and measurements for Phaeodactylum tricornutum showed large discrepancies, with a relative error up to 88%. These results give strong support for the development of a promising tool providing rapid and accurate estimations of biomass and physiological status of a dense microalgal culture based on only light transmittance properties.

Coupled turbidity and spectroscopy problems: a simple algorithm for the volumetric analysis of optically thin or dilute two-phase systems

We report an algorithm for measuring the phase volume fraction and solute concentration of a two-phase system, applicable to either optically thin or optically dilute spatially homogeneous systems. Probing light is directed into the sample, and the elastically scattered light (EE) is collected as one signal and the inelastically scattered light (IE) collected as another signal. The IE can be pure fluorescence or Raman or an unresolved combination of the two. As the IE and the EE are produced by fundamentally different processes, they are independent. The algorithm, derived from radiation transfer theory, shows that phase volume and concentration are linear functions of the EE and IE. The parameters are derived from a training set. We present examples of how the algorithm performs when the assumption of spatial homogeneity is violated and when light-induced photochemistry causes changes in the IE. Although this is a generally valid algorithm with many potential applications, its use is discussed briefly in the context of blood and tissue analysis since the algorithm was originally designed for noninvasive in vivo probing of human skin.

Improvement of the chemical content prediction of a model powder system by reducing multiple scattering using polarized light spectroscopy

Near-infrared spectroscopy (NIRS) is a powerful non-destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in line in industries, in vivo with biomedical applications, or in field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentration. Instead of spectral pre-processing, which is commonly used by NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, i.e., coupling polarized light with NIR spectrometry, to free spectra from scattering effect. This should allow us to retrieve linear and steady conditions for spectral analysis. When tested in visible-NIR (Vis-NIR) range (400-800 nm) on model media, mixtures of scattering and absorbing particles, the setup provided significant improvements in absorber concentration estimation precision as well as in the quality and robustness of the calibration model.

Potential of a spectroscopic measurement method using adding-doubling to retrieve the bulk optical properties of dense microalgal media

In the context of algal mass cultivation, current techniques used for the characterization of algal cells require time-consuming sample preparation and a large amount of costly, standard instrumentation. As the physical and chemical properties of the algal cells strongly affect their optical properties, the optical characterization is seen as a promising method to provide an early diagnosis in the context of mass cultivation monitoring. This article explores the potential of a spectroscopic measurement method coupled with the inversion of the radiative transfer theory for the retrieval of the bulk optical properties of dense algal samples. Total transmittance and total reflectance measurements were performed over the 380-1020 nm range on dense algal samples with a double integrating sphere setup. The bulk absorption and scattering coefficients were thus extracted over the 380-1020 nm range by inverting the radiative transfer theory using inverse-adding-doubling computations. The experimental results are presented and discussed; the configuration of the optical setup remains a critical point. The absorption coefficients obtained for the four samples of this study appear not to be more informative about pigment composition than would be classical methods in analytical spectroscopy; however, there is a real added value in measuring the reduced scattering coefficient, as it appears to be strongly correlated to the size distribution of the algal cells.

Interference correction by extracting the information of interference dominant regions: application to near-infrared spectra

Interference such as baseline drift and light scattering can degrade the model predictability in multivariate analysis of near-infrared (NIR) spectra. Usually interference can be represented by an additive and a multiplicative factor. In order to eliminate these interferences, correction parameters are needed to be estimated from spectra. However, the spectra are often mixed of physical light scattering effects and chemical light absorbance effects, making it difficult for parameter estimation. Herein, a novel algorithm was proposed to find a spectral region automatically that the interesting chemical absorbance and noise are low, that is, finding an interference dominant region (IDR). Based on the definition of IDR, a two-step method was proposed to find the optimal IDR and the corresponding correction parameters estimated from IDR. Finally, the correction was performed to the full spectral range using previously obtained parameters for the calibration set and test set, respectively. The method can be applied to multi target systems with one IDR suitable for all targeted analytes. Tested on two benchmark data sets of near-infrared spectra, the performance of the proposed method provided considerable improvement compared with full spectral estimation methods and comparable with other state-of-art methods.

Full correction of scattering effects by using the radiative transfer theory for improved quantitative analysis of absorbing species in suspensions

Sample-to-sample photon path length variations that arise due to multiple scattering can be removed by decoupling absorption and scattering effects by using the radiative transfer theory, with a suitable set of measurements. For samples where particles both scatter and absorb light, the extracted bulk absorption spectrum is not completely free from nonlinear particle effects, since it is related to the absorption cross-section of particles that changes nonlinearly with particle size and shape. For the quantitative analysis of absorbing-only (i.e., nonscattering) species present in a matrix that contains a particulate species that absorbs and scatters light, a method to eliminate particle effects completely is proposed here, which utilizes the particle size information contained in the bulk scattering coefficient extracted by using the Mie theory to carry out an additional correction step to remove particle effects from bulk absorption spectra. This should result in spectra that are equivalent to spectra collected with only the liquid species in the mixture. Such an approach has the potential to significantly reduce the number of calibration samples as well as improve calibration performance. The proposed method was tested with both simulated and experimental data from a four-component model system.