Catalyst design for water treatment using ab initio simulation

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2023-11-30
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Abstract

Shortage of clean water sources due to climate change, development of industrialization, and population growth is a concerning problem worldwide. Heterogenous catalysis is a promising strategy to reduce the concentration of undesirable substances during water treatment. In this thesis, I apply ab initio simulation to identify key material properties and fundamental reaction mechanisms that dictate catalyst performance for the treatment of two important water contaminants: nitrate and per-fluoroalkyl substances (PFAS). This insight in turn informs design strategies for designing better catalysts for these applications. Perfluorooctanoic acid (PFOA) is one of the most prevalent PFAS contaminants in surface and ground water. Working with experimentalist collaborators, we reported that hexagonal boron nitride (hBN) is a promising photocatalyst for PFOA degradation under UVC illumination, with an activity ~2x higher than TiO2. In my thesis, I applied density functional theory (DFT) in a grand canonical (GC) formalism (Bhati and Chen et al., J. Phys. Chem. C, 2020, 124, 49, 26625–26639) to determine the photo-catalytic mechanism responsible for PFOA degradation on hBN. (Chen et al. Environ. Sci. Technol., 2022, 56, 12, 8942–8952) I confirmed the favorability of the proposed photo-oxidation step of PFOA on the hBN surface: CnF2n+1COO− + h+ → CnF2n+1ꞏ + CO2. Furthermore, by investigating the electronic properties of hBN, I found that NB substitutional point defect introduces mid-gap states that enable the UVC light absorption and enhance charge carrier separation. Therefore, introducing more NB defects is a promising strategy to enhance the photocatalytic degradation performance of hBN. My work also helped to determine the role of surface hydrophobicity in promoting PFOA degradation, which is attributed both to stronger adsorption of the hydrophobic fluorinated tale of PFOA and the exclusion of water molecules that can scavenge photo-excited holes. (Wang and Chen et al., submitted) Thus, increasing surface hydrophobicity is another strategy for enhancing catalyst performance during PFOA degradation. Using this insight, we are now developing covalent organic framework (COF) catalysts with tunable functionality to tailor hydrophobic and electrostatic interactions, thus maximizing PFOA adsorption.
Besides PFOA, nitrate is another pervasive surface and groundwater contaminant found worldwide. Nitrate anions are highly soluble and mobile, and can cause harmful health effects in humans, including diseases such as blue baby syndrome, cancer, etc. Investigating the reaction network of electrocatalytic nitrate reduction, we found Cu and Pd catalysts can play a synergistic role in nitrate removal. (Lim and Chen et al., ACS Catal. 2023, 13, 1, 87–98) Using DFT, we discerned how the electronic properties of the metal catalyst affect the nitrate reduction reaction mechanism, steering the product selectivity to either N2 or NH3. (Chen and Senftle, submitted) We propose that metals like Pd, with less-occupied and more-delocalized d orbital exhibit higher N2 selectivity due to adsorbate-adsorbate interactions that promote N–N bond formation over N–H bond formation. This insight sets the theoretical basis for the design of better Pd/Cu bimetallic catalysts for the selective disposal of nitrate from water.

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EMBARGO NOTE: This item is embargoed until 2025-12-01
Degree
Doctor of Philosophy
Type
Thesis
Keywords
ab initio simulation, water treatment, PFOA degradation, nitrate removal, heterogeneous catalysis, catalyst design
Citation

Chen, Yu. "Catalyst design for water treatment using ab initio simulation." (2023). PhD diss., Rice University. https://hdl.handle.net/1911/115434

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