Revealing mass transfer of nano-emulsified vegetable oil reagents across varying hydraulic condition: from microfluidic chip to pore structure scale

The dataset generated in this study was designed to quantitatively support the multiscale investigation of NEVO transport and mass transfer dynamics described above. Specifically, high-resolution time-series image data and corresponding concentration measurements were obtained from controlled microfluidic experiments conducted at both the microfluidic chip scale and the pore-structure scale under systematically varied flow conditions. All experiments were performed under replicated hydraulic conditions to ensure reproducibility, and image sequences were processed using quantitative image analysis to extract morphology-specific metrics, including sheet-like, cluster-like, throat-like, and corner-shaped residual configurations. The resulting dataset enables direct comparison of transport behavior across scales and flow regimes and provides the empirical basis for model calibration and validation. By explicitly linking pore-scale morphology evolution to macroscopic breakthrough behavior, the dataset serves as a mechanistic bridge between microfluidic observations and continuum-scale transport modeling in subsurface remediation systems.