Probing the Room Temperature Deuterium Absorption Kinetics in Nanoscale Magnesium Based Hydrogen Storage Multilayers Using Neutron Reflectometry, X-ray Diffraction, and Atomic Force Microscopy
Bibliographic record
Abstract
Magnesium hydride has high storage capacity (7.6 wt % H) but very slow sorption kinetics. Addition of catalytic phases on the surface as well as alloying with transition metals is known to improve the properties. In this study, the sorption kinetics of a 50-nm Mg layer and Mg-10%Cr-10%V layer, capped with a CrV/Pd bilayer catalyst, are compared using a combination of neutron reflectometry (NR), X-ray diffraction (XRD), and atomic force microscopy to elucidate the effects of alloying on the hydrogen storage properties of Mg at room temperature. From NR it is found that the Cr–V alloyed layer shows both a delay in expansion in the first absorption cycle and a delay in contraction in the first desorption, which indicates a delay in nucleation of MgD 2 and formation of substoichiometric MgD 2-δ, respectively. Compared to pure Mg, the kinetics are strongly improved as no blocking MgD 2 layer is formed. XRD showed a strong reduction in the Mg grain size for the Cr–V alloyed layer after one cycle. For pure Mg, the grain size is almost unchanged although the film becomes nanocrystalline in the hydrided state. NR is shown to be highly sensitive to both the deuterium distribution as well as the layer thickness, which makes it a valuable tool for studying reaction mechanisms and quantification of the expansion of both crystalline and amorphous energy storage materials.
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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".