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• W2903155745 abstract "Identifying and quantifying the processes governing nanoparticle transport in porous media using breakthrough curves with or without retention profiles from laboratory column experiments is frequently subject to uncertainty due to the limited information content of such datasets. An integrated system of automated, non-invasive magnetic susceptibility monitoring and numerical modelling (MSMM) has been developed to provide exceptionally detailed datasets for assessing the validity of transport models of magnetic nanoparticles within a column. MSMM produces the equivalent of a breakthrough curve for each monitored location along the column and uses the enhanced dataset to constrain numerical models more effectively. The results of 2 example column experiments using magnetite nanoparticles are presented to demonstrate the approach: (i) using quartz sand (with 46,002 susceptibility measurements over 37 h) and (ii) using crushed Triassic Sandstone (with 19,654 measurements over 20 h). The quartz sand experiment showed no nanoparticle retention: MSMM showed the system could be well described by an advection-dispersion model, which predicted a breakthrough curve consistent with that derived from magnetic monitoring and with the breakthrough curve acquired independently using a fluorescein tracer. In contrast, no breakthrough was observed in the sandstone experiment, but even in the absence of a breakthrough curve, MSMM indicated that the retention processes were spatially heterogeneous and consistent with a combination of parameterised models of physical straining and limited capacity irreversible attachment." @default.
• W2903155745 created "2018-12-11" @default.
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• W2903155745 creator A5075615586 @default.
• W2903155745 date "2019-02-01" @default.
• W2903155745 modified "2023-10-18" @default.
• W2903155745 title "Magnetic susceptibility monitoring and modelling (MSMM): A non-invasive method for acquiring and modelling exceptionally large datasets from column experiments with manufactured nanoparticles" @default.
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• W2903155745 doi "https://doi.org/10.1016/j.colsurfa.2018.12.003" @default.
• W2903155745 hasPublicationYear "2019" @default.
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