This version is available at https://strathprints.strath.ac.uk/13703/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Extraction of Chemical Information of Suspensions RECEIVED DATE (to be automatically inserted after your manuscript is accepted if requiredaccording to the journal that you are submitting your paper to) ABSTRACTAn approach for removing multiple light scattering effects using the radiative transfer theory (RTE) in order to improve the performance of multivariate calibration models is proposed. This approach is then applied to the problem of building calibration models for predicting the concentration of a scattering (particulate) component. Application of this approach to a simulated four component system showed 1 that it will lead to calibration models which perform appreciably better than when empirically scatter corrected measurements of diffuse transmittance (T d ) or reflectance (R d ) are used. The validity of the method was also tested experimentally using a two-component (Polystyrene-water) system. While the proposed method led to a model that performed better than that built using R d , its performance was worse compared to when T d measurements were used. Analysis indicates that this is because the model built using T d benefits from the strong secondary correlation between particle concentration and pathlength travelled by the photons which occurs due to the system containing only two components.On the other hand, the model arising from the proposed methodology uses essentially only the chemical (polystyrene) signal. Thus this approach can be expected to work better in multi-component systems where the pathlength correlation would not exist.

Spectral measurements of complex heterogeneous types of mixture samples are often affected by significant multiplicative effects resulting from light scattering, due to physical variations (e.g., particle size and shape, sample packing, and sample surface, etc.) inherent within the individual samples. Therefore, the separation of the spectral contributions due to variations in chemical compositions from those caused by physical variations is crucial to accurate quantitative spectroscopic analysis of heterogeneous samples. In this work, an improved strategy has been proposed to estimate the multiplicative parameters accounting for multiplicative effects in each measured spectrum and, hence, mitigate the detrimental influence of multiplicative effects on the quantitative spectroscopic analysis of heterogeneous samples. The basic assumption of the proposed method is that light scattering due to physical variations has the same effects on the spectral contributions of each of the spectroscopically active chemical components in the same sample mixture. On the basis of this underlying assumption, the proposed method realizes the efficient estimation of the multiplicative parameters by solving a simple quadratic programming problem. The performance of the proposed method has been tested on two publicly available benchmark data sets (i.e., near-infrared total diffuse transmittance spectra of four-component suspension samples and near-infrared spectral data of meat samples) and compared with some empirical approaches designed for the same purpose. It was found that the proposed method provided appreciable improvement in quantitative spectroscopic analysis of heterogeneous mixture samples. The study indicates that accurate quantitative spectroscopic analysis of heterogeneous mixture samples can be achieved through the combination of spectroscopic techniques with smart modeling methodology.

The effectiveness of a scatter correction approach based on decoupling absorption and scattering effects through the use of the radiative transfer theory to invert a suitable set of measurements is studied by considering a model multi-component suspension. The method was used in conjunction with partial least squares regression to build calibration models for estimating the concentration of two types of analytes: an absorbing (non-scattering) species and a particulate (absorbing and scattering) species. The performances of the models built by this approach were compared with those obtained by applying 2 empirical scatter correction approaches to diffuse reflectance, diffuse transmittance and collimated transmittance measurements. It was found that the method provided appreciable improvement in model performance for the prediction of both the types of analytes. The study indicates that as long as the bulk absorption spectra is accurately extracted, no further empirical pre-processing to remove light scattering effects is required.

This version is available at https://strathprints.strath.ac.uk/44512/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the ABSTRACTSample-to-sample photon path length variations that arise due to multiple scattering can be removed by decoupling absorption and scattering effects using 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 which changes nonlinearly with particle size and shape. For the quantitative analysis of absorbing only (i.e. non-scattering) species present in a matrix that contains a particulate species which absorbs and scatters light, a method to eliminate particle effects completely is proposed which utilizes the particle size information contained in the bulk scattering coefficient extracted using Mie theory to carry out an additional correction step to remove particle effects from bulk absorption spectra. 2This would result in spectra which are equivalent to spectra collected using only the liquid species in the mixture. Such an approach has the potential to significantly reduce the number of calibration samples as well as improving calibration performance. The proposed method was tested using both simulated and experimental data from a 4 component model system.