Study of Non-PGM ORR Catalyst Degradation Using Synchrotron Techniques
Bibliographic record
Abstract
Several recent reports on the development of oxygen reduction reaction (ORR) non-platinum group metal (non-PGM) catalysts have shown an impressive progress towards high ORR activity [1-2]. By now, in RDE testing, these catalysts are quite routinely reaching E½ values of 0.8 V versus reversed hydrogen electrode [1]. The high initial performance notwithstanding, truly durable non-PGM catalysts, capable of maintaining ORR activity for hundreds or thousands of hours at low pH values of the polymer electrolyte fuel cell (PEFC), are yet to be developed. The development of such catalysts must involve a carefully thought-out experimental design and the use of reliable multiple techniques to provide answers to the quarter-of-a-century-old questions about the structure of the ORR active site(s) in metal-nitrogen-carbon (M-N-C) catalysts. According to some previous in-situ XAS studies [3-4], a vast majority of non-PGM catalysts consist of two forms of transition metal, iron coordinated by nitrogen species (Fe-Nx) and non-coordinated iron nanoparticles (FeNP). While the existence of these species has been detected using different methods, the in-situ XAS reviled a specific redox behavior accompanied with spin switching behavior of the Fe-Nx species when subjected to potential bias simulating PEFC environment [2-4]. There is still a large ambiguity, however, about the actual nature of the M-N-C active sites and their degradation modes. Among many challenges facing this research, it is important to take a closer look at other elements present in such catalysts, such as nitrogen and carbon. This is especially needed for non-PGM catalysts without nitrogen-coordinated Fe (e.g. FeNP) with very high activity [5]. Herein, we present a study of a Fe-based non-PGM catalyst derived from multiple nitrogen precursors. The study has been performed using synchrotron X-ray absorption techniques coupled with standard electrochemical methods, including RRDE and MEA testing. We look at the structures involving all elements in the catalyst by employing high-energy photons at Argonne National Laboratory (to monitor in-situ Fe-containing species) and low-energy photons at Stanford Synchrotron Lightsource to monitor carbon and nitrogen species (C and N K-edge), claimed to play an important part in the ORR active site sites. With better understanding of the structure-to-function relationship in Fe-N-C species as the main objective, we study the effect of durability cycling (Figure1) on the catalyst performance and structural changes involving all elements in Fe-N-C species. Figure 1
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".