Estimation of Adsorbed Amounts in Organoclay by Machine Learning.

Adsorption properties of organoclay have been investigated for decades focusing on the morphology and physicochemical properties of two-dimensional interlayers. Experimental studies have previously revealed that the adsorption mechanisms depend on the molecular species of the organocation and adsorbate, making it difficult to estimate the adsorbed amount without experiments. Considering that the adsorption of aromatic compounds has been reported by using various clays, organocations, and adsorbates, machine learning is a promising method to overcome the difficulty.