Unveiling Competitive Adsorption in TiO Photocatalysis through Machine-Learning-Accelerated Molecular Dynamics, DFT, and Experimental Methods.

The efficient harnessing of solar power for water treatment via photocatalytic processes has long been constrained by the challenge of understanding and optimizing the interactions at the photocatalyst surface, particularly in the presence of nontarget cosolutes. The adsorption of these cosolutes, such as natural organic matter, onto photocatalysts can inhibit the degradation of pollutants, drastically decreasing the photocatalytic efficiency. In the present work, computational methods are employed to predict the inhibitory action of a suite of small organic molecules during TiO photocatalytic degradation of -chlorobenzoic acid (CBA).

Delineating the Effects of Molecular and Colloidal Interactions of Dissolved Organic Matter on Titania Photocatalysis.

In the face of significant challenges to practical applications of photocatalysis for water treatment, recent reports revealed a potential route to overcome a problem posed by dissolved organic matter (DOM). These studies showed that inhibition of photocatalytic processes by DOM is driven largely by competition for active surface sites on TiO or other catalysts, and controlling the type of DOM present in solution could significantly mitigate DOM fouling. Whether or not control of solution parameters could achieve the same preventative action is not known.