Analysis of Inkjet Printed Catalyst Coated Membranes for Polymer Electrolyte Electrolyzers
Bibliographic record
Abstract
Inkjet printing (IJP) is studied as a novel fabrication method for catalyst coated membranes (CCMs) for polymer electrolyte electrolyzers. IrO 2 and Pt/C inks were deposited by IJP over the membrane to fabricate anode and cathode electrodes, respectively. Optical microscopy, scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) were used for ex-situ surface and thickness characterization of the anode catalyst layer (CL). SEM images show the CL is uniform and well adhered to the membrane. EDX images show even distribution of the catalyst and ionomer in the CL. Hydrogen cross-over, cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) tests were performed to estimate hydrogen cross-over, double layer capacitance (C dl ) and cell resistances. Cross-over results show that the membrane is not damaged during printing. A kinetic study revealed Tafel slopes similar to those in literature. Electrochemical performance tests showed that inkjet printed electrolyzer CCMs achieved 1 and 2 A/cm 2 current densities at average potentials of 1609 mV and 1696 mV (NRE211) and average of 1743 mV and 1977 mV (N117) respectively. The electrolyzer performance improved slightly when the printing piezo-voltage decreased but with a cost of higher fabrication time. The stability of the electrode was inline with literature data. The proposed electrodes outperform most of the previously reported electrolyzer data in the literature using commercial IrO 2 catalyst.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".