An Epoxy‐Free Sample Preparation Approach to Enable Imaging of Ionomer and Carbon in Polymer Electrolyte Membrane Fuel Cells
Bibliographic record
Abstract
Abstract Performance and durability of electrodes in proton exchange membrane fuel cells (PEMFCs), as one of the most promising zero‐emission power generation technologies, depend on the composition, microstructure, and distribution of its components—metal catalyst, carbon support, and ionomer. Their improvement requires an in‐depth understanding of the electrodes’ structure‐property‐performance relationship, for which transmission electron microscopy (TEM) has been an invaluable tool. However, the conventional TEM sample preparation, namely epoxy‐embedding ultramicrotomy, poses impediments in imaging ionomer and distinguishing it from carbon. Therefore, in this research, an epoxy‐free ultramicrotome technique is implemented on beginning‐of‐life (BOL) and end‐of‐life (EOL) PEMFC samples. For the first time, TEM and electron tomography‐TEM images reveals fascinating details of the ionomer network, carbon particles’ structure, and Pt distribution in BOL, as well as their structural changes after the cell degradation. Finally, the structural descriptors, extracted by a proprietary quantification method, are correlated with visual observations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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".