Thermodynamics and kinetics of hydriding and dehydriding reactions in Mg-based hydrogen storage materials
Bibliographic record
Abstract
Mg-based materials are one of the most promising hydrogen storage candidates due to their high hydrogen storage capacity, environmental benignity, and high Clarke number characteristics. However, the limited thermodynamics and kinetic properties pose major challenges for their engineering applications. Herein, we review the recent progress in improving their thermodynamics and kinetics, with an emphasis on the models and the influence of various parameters in the calculated models. Subsequently, the impact of alloying, composite, and nano-crystallization on both thermodynamics and dynamics are discussed in detail. In particular, the correlation between various modification strategies and the hydrogen capacity, dehydrogenation enthalpy and temperature, hydriding/dehydriding rates are summarized. In addition, the mechanism of hydrogen storage processes of Mg-based materials is discussed from the aspect of classical kinetic theories and microscope hydrogen transferring behavior. This review concludes with an outlook on the remaining challenge issues and prospects.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".