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Inferring colloidal interaction from scattering by machine learning

CARBON TRENDS (2023)

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Summary: This paper presents a machine learning strategy for determining the effective interaction in condensed phases of matter using scattering, and shows its superior performance in accuracy, efficiency, and applicability compared to existing parametric approaches. The method allows for quantification of interaction in highly correlated systems using scattering and diffraction experiments.

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