Stable Hydrogen Storage Cycling in Magnesium Hydride, in the Range of Room Temperature to 300 °C, Achieved Using a New Bimetallic Cr-V Nanoscale Catalyst
Bibliographic record
Abstract
We created a bimetallic chromium vanadium hydrogen sorption catalyst for magnesium hydride (MgH 2 ). The catalyst allows for significant room-temperature hydrogen uptake, over 10 cycles, at absorption pressures as low as 2 bar. This is something that has never been previously achieved. The catalyst also allowed for ultrarapid and kinetically stable hydrogenation cycling (over 225 cycles) at 200 and at 300 °C. Transmission electron microscopy analysis of the postcycled samples revealed a nanoscale dispersion of Cr-V nanocrystallites within the Mg or MgH 2 matrix. TEM analysis of the partially absorbed specimens revealed that even at a high absorption pressure, that is, a high driving force, relatively few hydride nuclei are formed at the surface of the pre-existing magnesium, ruling out the presence of any contracting volume (also termed contracting envelope or core shell) type growth. HRTEM of the cycled and desorbed powder sample demonstrated that the bcc Cr-V phase is crystalline and nanoscale. We experimentally demonstrated that the activation energy for hydrogen absorption is not constant but rather evolves with the driving force. This finding sheds new insight regarding the origins of the wide discrepancy in the literature – reported values of the hydrogenation activation energy in magnesium hydride and in related metal hydride systems.
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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 | 0.000 |
| 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 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".