Hydrogen dissociation and diffusion through molten metal alloy membranes
Bibliographic record
Abstract
Existing dense metallic hydrogen separation membranes deactivate above 823 K (550 °C). Recently, high-temperature molten gallium membranes were reported to have hydrogen diffusion coefficients 10 times greater than solid palladium; however, the overall hydrogen flux falls short of state-of-the-art palladium-based membranes due to slow dissociative adsorption of hydrogen. To increase this rate, we investigate molten alloys of transition metals for the first time. Rates of hydrogen dissociation on 15 top candidate molten metal alloys were quantified using the H 2 -D 2 isotopic exchange reaction. Alloys exhibited higher dissociative adsorption rates than pure metals. For instance, the experimentally determined apparent activation energy for hydrogen dissociation significantly decreased from 187 kJ/mol for pure molten bismuth to 91 kJ/mol for molten Cu 0.03 Bi 0.97 . Density functional theory (DFT) calculations corroborated these findings, indicating considerably lower barriers for H 2 dissociation on Cu 0.03 Bi 0.97 versus pure bismuth. Experimentally determined hydrogen diffusion, obtained using a Sievert's apparatus, were similar for Bi, Cu 0.03 Bi 0.97 , and Ni 0.03 Bi 0.97 . This suggests that the primary benefit of alloying transition metals with low-melting metals is to increase the rate of dissociative adsorption rather than diffusion. Ab initio molecular dynamics (AIMD) calculations indicated that Cu atoms prefer to be in the bulk over the surface of Cu 0.03 Bi 0.97 . Copper atoms solvated by bismuth take electrons from bismuth to become negatively charged. We propose this electronic modification of bismuth by sub-surface copper leads to bismuth acting as the active sites for homolytic hydrogen dissociation, thereby improving performance. • Alloying transition metals with low melting metals increases H 2 dissociation rate. • Alloying transition metals improves hydrogen diffusion. • Homolytic H 2 dissociation occurs on electronically modified Bi atoms on Cu-Bi.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".