Investigation of SiO2 Nanoparticle Retention in Flow Channels, Its Remediation Using Surfactants and Relevance of Artificial Intelligence in the Future

In this study, the effect of these variables on commercial silica NP retention was presented in a fabricated flow model considering only physical adsorption aspects retention. From our observations, it established that while concentration, rate and salt are key influencing agglomeration retention, temperature highly subdued. The salt-induced particularly severe at moderate salinity (?4 wt% NaCl). To mitigate agglomeration, commonly used anionic surfactant, sodium dodecyl sulfate (SDS) added to solution tabulated. An amount 0.3 SDS found negate significantly, paving way for use solutions, even presence saline conditions. A section prospective artificial intelligence purpose has been included. This study is useful understanding behaviour, especially its mitigation using surfactants, applications.