Electrocatalysts for voltage reversal tolerant anodes in proton exchange membrane fuel cells and CO2 reduction to formate
Bibliographic record
Abstract
Catalyst durability in renewable energy systems (including CO₂ electroreduction and Hydrogen fuel cells) is vital to the overall lifetime of the systems. To protect hydrogen fuel cells during cell voltage reversal, oxygen evolution reaction (OER) catalysts (typically RuO₂ or IrO₂) are added to the anode of proton exchange membrane fuel cells (PEMFCs). In this thesis, the durability of these OER catalysts was investigated by measuring the mass changes of heat-treated IrOx powders (350, 450 and 550 °C) drop cast on an electrochemical quartz crystal microbalance (EQCM). IrOx catalysts showed difference in frequency response due to the differential uptake of water and formation of oxyhydroxide species during cyclic voltammetry (CV) experiments (1.2, 1.4 and 1.6 to 0.05 V vs. RHE) confirmed by XPS. Platinum on carbon catalyst (Pt/C) suffered from carbon corrosion during potential holds at 1.8 and 2.0 V. The addition of IrOx powders to Pt/C protected the layer against carbon corrosion creating a simulated reversal tolerant anode. Additionally, OER catalysts were ranked by OER activity and dissolved Ir³⁺ in the electrolyte after an ex situ accelerated stress test (AST) in a representative PEMFC anode environment. The ex situ results are compared with reversal times obtained in a single cell PEMFC subjected to anode accelerated stress test (AAST). Generally, catalysts with higher OER mass activity and Ir³⁺ dissolution had longer reversal times. Heat treatment of unsupported IrOx increased OER durability in the fuel cell anode environment. Catalyst instability strongly affects the viability of electroreduction of CO₂ (ERC) systems as well. To improve the durability and efficiency of ERC catalysts, five Bimetallic Sn-Pb catalyst compositions were electrodeposited (from fluoroborate or oxide media) on two carbon supports. Sn majority catalysts with 15 to 35% Pb generated stable faradaic efficiencies (FE) up to 95% during constant potential electrolysis whereas pure Sn experienced an extensive (up to 30%) decrease in FE. After electrolysis, XRD analysis showed a SnO₂ phase present on 35% Pb catalysts but not on pure Sn catalysts. It is proposed that the presence of Pb in Sn majority catalysts stabilized SnO₂ and enhanced faradaic efficiency durability during ERC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".