Understanding the hydrogen storage behavior of promising Al–Mg–Na compositions using thermodynamic modeling
Bibliographic record
Abstract
Thermodynamic modeling of the Al–Mg–Na–H system is performed in this work to understand the phase relationships and reaction mechanisms in this system. The Al–Na system is reassessed using the modified quasichemical model for the liquid phase. All the terminal solid solutions were remodeled using the compound energy formalism. The thermodynamic properties of the ternary systems are estimated from the models of the binary systems and the ternary compound using the CALPHAD method. The reaction pathways for the systems MgH 2 /AlH 3 , MgH 2 /NaAlH 4 , and MgH 2 /Na 3 AlH 6 are calculated and compared to the experimental data from the literature. Details about the reaction mechanisms and temperatures, the amount of the products, and their composition are revealed and discussed in this work. The calculations show that in the composites MgH 2 /NaAlH 4 and MgH 2 /Na 3 AlH 6 , the components spontaneously destabilize mutually in specific relative amounts by forming NaMgH 3 , which may play only a catalytic role on the decomposition of (MgH 2 + Al) mixture, NaAlH 4 , or Na 3 AlH 6 . Also, Al destabilizes MgH 2 and NaMgH 3 by forming β phase and reducing the decomposition temperatures of these hydrides by more than 50 °C. The constructed database is successfully used to reproduce the pressure–composition isotherms (PCIs) for Mg-10 at% Al and Mg-4 at% Al alloys at 350 °C. The results provide a better understanding of the reaction mechanisms in the PCIs found in the literature concerning the number of plateau pressures and their sloping. It is shown that the first plateau pressure observed during the PCIs of Al–Mg alloys depends on Al content and is higher than that of pure Mg. This difference is due to Al solubility in hcp-Mg.
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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 | 0.001 | 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".