Understanding the degradation of <scp>Pt</scp> nanoparticles in a fuel cell electrode via identical location electron tomography
Bibliographic record
Abstract
The degradation and high cost of electrodes materials used in proton exchange membrane fuel cells (PEMFCs) are major barriers limiting their commercialization in automotive vehicles [1]. The search for more affordable electrode materials has focused on controlling the surface structure and composition of novel multi‐metallic catalytic nanoparticles on high surface area support membrane [2]. During fuel cell operation, the catalyst nanoparticles can dissolve, re‐deposit and agglomerate, resulting in electrochemical surface area losses, and an associated decrease in catalyst activity [3]. It is therefore critical to understand the degradation mechanism of the nanoparticle catalysts during electrochemical aging in a fuel cell electrodes in order to improve the performance and lifetime of PEMFCs. Here we characterize a newly proposed fuel cell cathode material, comprised of nano‐particulate platinum on a NbO x ‐carbon hybrid support, using identical location electron tomography. A full HAADF‐STEM tomographic tilt series of several representative clusters were obtained before and after acclerated stress tests (30,000 cycles from 0.6 to 1.0 V in an electrochemical cell). Preliminary results are summarized in Figure 1. A three dimensional (3D) schematic of a simple PEMFC shows the overall structure and location of the cathode electrode catalyst material used in this study. Pt nanoparticles, a few nanometers in diameter, decorate the complex, 3D NbO x ‐carbon hybrid support structure, imaged by HAADF STEM under identical conditions in (b) before and after electrochemical cycling and at two tilts separated by 40 0 . The 3D tomographic reconstructions of the structure are aligned and compared in (c). The high fidelity of the reconstructions and the relatively small overall changes observed in the structure enabled the semi‐automated matching of over 500 individual Pt nanoparticles before and after cycling (d). The semi‐automatized approach was accomplished with the aid of quantitative image analysis techniques including histogram normalization and maximum entropy thresholding, and alignment of the before and after reconstructions via a singular valued decomposition of the reconstructed Pt centroids matrix. Preliminary results suggest that a net leaching of the Pt into solution has occurred during cycling, indicated by the overall reduction in size of a vast majority of Pt nanoparticles (e). Analysis of 3D reconstructions obtained from Pt‐NbO x ‐carbon hybrid structures differing in their Pt/NbO x ratio are underway to better elucidate the role of NbO x in the degradation of Pt. Identical location electron tomography before and after electrochemical cycling has provided valuable insight into the degradation mechanism of the PEMFC electrode during cycling, enabling more informed decisions for the design of high‐performance durable electrode materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".