Synchrotron X-ray Radiography as a Highly Precise and Accurate Method for Measuring the Spatial Distribution of Liquid Water in Operating Polymer Electrolyte Membrane Fuel Cells
Bibliographic record
Abstract
For the first time, the precision and the accuracy of liquid water content measurements in operating polymer electrolyte membrane (PEM) fuel cells from synchrotron X-ray radiographic imaging are determined. We define the precision of X-ray radiographic-based water measurements by combining two types of uncertainties. In the uncertainty of type A, the standard deviation of the average through-plane water thickness distribution is determined as a function of time and space. In the uncertainty of type B, the effects of the instrumentation (camera readout noise and X-ray energy level) in the Beer-Lambert law are considered. The volume of liquid water in the gas diffusion layer (GDL) is quantified with the greatest precision (plus or minus 5%) when using a beam energy of 24 keV and a low camera readout noise. The accuracy of our synchrotron X-ray-based liquid water measurements is determined from the direct comparison to neutron radiography measurements reported by Kotaka et al. (Electrochim. Acta. 146, 2014). The GDL through-plane distributions and volumes of liquid water measured by two techniques are in excellent agreement. From this work, synchrotron X-ray radiography is shown to be a powerful technique that is both precise and accurate for measuring the spatial distribution of liquid water in miniature operating PEM fuel cells.
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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) | 0.000 | 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".