Investigating the Equilibration Time of Catalyst Coated Membranes Using AC and DC Methods
Bibliographic record
Abstract
It is important to ensure that the water content of a catalyst coated membrane (CCM) has equilibrated before it is used in the manufacturing of a proton exchange membrane (PEM) fuel cell stack. Equilibration is achieved when the water content in the CCM reaches equilibrium with controlled relative humidity (RH) and temperature conditions. A CCM consists of a membrane coated with a catalyst layer (CL) electrode on both sides. The ionomer, which is a component of both the membrane and the CLs, absorbs/desorbs water as the CCM equilibrates, and as such, the ionic conductivity of the CCM is directly impacted. The electronic conductivity is indirectly impacted as dimensional changes in the ionomer result in changes to the network of electronically conducting materials in the CLs. Alternating current (AC) and direct current (DC) methods were investigated to measure the through-plane ionic resistance and in-plane electronic resistance as the CCM equilibrated. When CCM is manufactured it is wound around a plastic core with an impermeable leader and trailer portion protecting the surface of the CCM from the core and from the environment. As such, only the two edges of the roll are exposed to environmental conditions. It is in this state that the CCM must equilibrate to the manufacturing environment. To simulate this, discrete 4 samples of a commercially available CCM (Ion Power) were tested in a sample holder with pressure applied to replicate the roll winding tension. The sample holder covered the top, bottom, and two sides (roll direction) of the CCM, leaving the other two sides exposed to controlled conditions in an environmental chamber. The measurements described below were taken as the samples equilibrated from 50% RH to 45% RH at a constant temperature. The first method is an AC technique used to measure the through-plane sample impedance. The correlation between the RH of ionomers and their ionic conductivity is well established in literature [Cooper 2009, Maréchal 2007, Anantaraman 1996]. To measure the ionic conductivity of the sample, a sinusoidal alternating voltage was applied to silver foil strips on the top and bottom of the sample. This results in an alternating current passing through the sample. Electrochemical impedance spectroscopy (EIS) was used to measure the impedance as a function of frequency. From this data it was possible to extract the conductivity of the membrane and the equilibration time was investigated by tracking the impedance of the samples at 1 kHz. The second method is a DC technique, which employs more readily available equipment and reduces the data analysis complexity compared to the AC technique. The DC setup used four probes made of gold plated foil strips contacting each corners of the sample: two probes to measure a voltage difference and two to apply current to the sample. Current flows through the CL via a carbon/platinum network, which is only indirectly affected by water content as the ionomer expands or contracts due to water absorption or desorption [Morris 2014]. A constant current was applied to the sample undergoing equilibration and the voltage difference was monitored to determine the equilibration time. Both methods showed sensitivity to changing RH and exhibited reasonably constant results after a sufficient time, indicating that the samples had equilibrated to the environment. Figure 1 shows the impedance (1 kHz) of a CCM initially equilibrated to 50% RH as it equilibrates to 45% RH. The impedance increased rapidly for the first few hours and then slowed down before eventually reaching an approximately constant value, indicating equilibrium with the environment was achieved after approximately 18 h. The results of the DC method were consistent with those of the AC method. The novelty of this research is in providing quantitative methods to determine when a CCM roll has equilibrated with its environment. Once equilibrated, the CCM roll can be used in the manufacturing of fuel cell stacks. This research will help increase the efficiency of the manufacturing process and improve the quality assurance of the final product. Research funding from both MITACS (Accelerate program) and NSERC (Engage Plus program) is gratefully acknowledged, as is early and significant work by Anne Moore and Jeff Laflamme. References Anantamaran, A. V.; Gardner, C. L. J. Electroanal. Chem., 414, 115 (1996) Cooper K. R. ECS Transactions, 25, 995 (2009) Maréchal, M; Souquet, J. -L.; Guindet, J; Sanchez, J. -Y. Electrochem. Comm., 9, 1023 (2007) Morris, D.; Liu, S.; Gonzalez, D.; & Gostick, J. ACS Applied Materials & Interfaces, 18609 (2014) 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".