Component optimization for electrochemical water oxidation to hydrogen peroxide
Abstract/Contents
- Abstract
- Treating wastewater is a resourceful and economical approach to providing potable water to our growing population. Because chlorination causes carcinogenic byproducts, and wastewater can be heavily contaminated, other purification methods are needed. One method involves using UV-light and hydrogen peroxide (H2O2) to oxidize contaminants and has already been implemented around world. However, H2O2 is often produced unsustainably via the anthraquinone process. An alternative is to produce H2O2 via a two-electron water oxidation reaction (2e-WOR) at the anode of an electrochemical cell. Despite this proposal, much research is needed before this technology can be implemented, hence the work of this thesis. Herein, we optimize parameters of various components in the 2e-WOR -- the electrode, electrolyte, and electrochemical cell -- to improve H2O2 production. First, we introduce a stable anode of manganese (Mn) doped titanium dioxide (TiO2), in which increasing the amount of Mn increases its catalytic activity. Through a facile solution gelation process, we synthesize TiO2 with various amounts of Mn in its crystal lattice. In a 0.5 M H2SO4 electrolyte, we found the onset potential to decrease by 370 mV with the addition of Mn, while in a 2 M KHCO3 electrolyte, the onset decreased by 260 mV. It was discovered that the selectivity towards H2O2, oxygen, and peroxysulfate, also depends on the amount of Mn and the electrolyte. Next, we moved to optimizing components of the electrolyte and fixing the anode material to be commercial fluorine doped tin oxide (FTO) on glass. After varying the applied voltage, HCO3-- to CO32-- ratio, total dissolved inorganic carbon concentration, and cationic species, we present an optimized electrolyte mixture of 0.5 M KHCO3 and 3.5 M K2CO3 under 3.25 V vs. RHE. We compare our optimized electrolyte to the field standard 2 M KHCO3 electrolyte and find a twelve-fold increase in the selectivity and H2O2 production rate. The optimized electrolyte also led to a 20-time higher concentration of accumulated H2O2 over 3 hours. We then implemented a machine learning (ML) model to aid in the optimization of the electrochemical H2O2 production process and to map out various performance parameters of the system. From the model, we discovered a further optimized electrolyte composition of 0.92 M KHCO3 and 3.08 M K2CO3, which has become the new standard electrolyte for the field. Our results also demonstrate the efficacy of using ML when experimental data and mechanistic knowledge is limited. Finally, we turn to the electrochemical cell/setup. We optimize the electrolyte flow rate to maximize efficiency on an FTO anode. We then switch to a new and improved indium tin oxide on platinum on titanium (ITO/Pt/Ti) layered anode, which triples the H2O2 production rate. With this anode, we were able to achieve the highest production rate of ~ 40 µmoles/min/cm2 from a voltage of 3.4 V vs. RHE. We also achieved a continuous production rate of ~ 23 µmoles/min/cm2 from a voltage of 3 V vs. RHE over four hours. With the stated improvements in H2O2 production via the 2e-WOR, we hope to bring this technology closer to implementation for clean and sustainable H2O2 production.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Vallez, Lauren |
|---|---|
| Degree supervisor | Zheng, Xiaolin, 1978- |
| Thesis advisor | Zheng, Xiaolin, 1978- |
| Thesis advisor | Guo, Jinghua, 1964- |
| Thesis advisor | Tang, Sindy (Sindy K.Y.) |
| Degree committee member | Guo, Jinghua, 1964- |
| Degree committee member | Tang, Sindy (Sindy K.Y.) |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Mechanical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Lauren Vallez. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/jm766bq0356 |
Access conditions
- Copyright
- © 2023 by Lauren Vallez
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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