Combinatorial Analysis of Sparse Experiments on Photocatalytic
Performance of Cement Composites: A Route toward Optimizing Multifunctional
Materials for Water Purification
posted on 2021-04-26, 17:37authored byPamela
Zuniga Fallas, Jaime Quesada Kimzey, Prabhas Hundi, Md Tariqul Islam, Juan C. Noveron, Pedro J. J. Alvarez, Rouzbeh Shahsavari
Blending
TiO2 and cement to create photocatalytic composites
holds promise for low-cost, durable water treatment. However, the
efficiency of such composites hinges on cross-effects of several parameters
such as cement composition, type of photocatalyst, and microstructure,
which are poorly understood and require extensive combinatorial tests
to discern. Here, we report a new combinatorial data science approach
to understand the influence of various photocatalytic cement composites
based on limited datasets. Using P25 nanoparticles and submicron-sized
anatase as representative TiO2 photocatalysts and methyl
orange and 1,4-dioxane as target organic pollutants, we demonstrate
that the cement composition is a more influential factor on photocatalytic
activity than the cement microstructure and TiO2 type and
particle size. Among the various cement constituents, belite and ferrite
had strong inverse correlation with photocatalytic activity, while
natural rutile had a positive correlation, which suggests optimization
opportunities by manipulating the cement composition. These results
were discerned by screening 7806 combinatorial functions that capture
cross-effects of multiple compositional phases and obtaining correlation
scores. We also report •OH radical generation, cement
aging effects, TiO2 leaching, and strategies to regenerate
photocatalytic surfaces for reuse. This work provides several nonintuitive
correlations and insights on the effect of cement composition and
structure on performance, thus advancing our knowledge on development
of scalable photocatalytic materials for drinking water treatment
in rural and resource-limited areas.