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DOE OSTI · 3002726

Machine-learning-informed scattering correlation analysis of sheared colloids

Ding, Lijie [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000227454606)·Chen, Yihao [Univ. of Pennsylvania, Philadelphia, PA (United States)] (ORCID:0000000299565719)·Do, Changwoo [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000183588417)
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Abstract

We have carried out theoretical analysis, Monte Carlo simulations and machine-learning analysis to quantify microscopic rearrangements of dilute dispersions of spherical colloidal particles from coherent scattering intensity. Both monodisperse and polydisperse dispersions of colloids were created and underwent a rearrangement consisting of an affine simple shear and non-affine rearrangement using the Monte Carlo method. We calculated the coherent scattering intensity of the dispersions and the correlation function of intensity before and after the rearrangement and generated a large data set of angular correlation functions for varying system parameters, including number density, polydispersity, shear strain and non-affine rearrangement. Singular value decomposition of the data set shows the feasibility of machine-learning inversion from the correlation function for the polydispersity, shear strain and non-affine rearrangement using only three parameters. A Gaussian process regressor is then trained on the data set and can retrieve the affine shear strain, non-affine rearrangement and polydispersity with relative errors of 3%, 1% and 6%, respectively. Altogether, our model provides a framework for quantitative studies of both steady and non-steady microscopic dynamics of colloidal dispersions using coherent scattering methods.

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Gaussian process regressionMonte Carlo simulationscolloidsmachine learningsmall-angle scattering

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Ding, Lijie [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000227454606), Chen, Yihao [Univ. of Pennsylvania, Philadelphia, PA (United States)] (ORCID:0000000299565719), Do, Changwoo [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000183588417). 2025-05-31. Machine-learning-informed scattering correlation analysis of sheared colloids. https://doi.org/10.1107/s1600576725003280

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