Synthesis of Nanostructured Mg2Ni for Hydrogen Storage by Mechanical Alloying via High-Pressure Torsion
Bibliographic record
Abstract
Mg2Ni is a highly promising candidate for solid-state hydrogen storage due to its high storage capacity. However, its synthesis is challenging due to the high melting point of Ni (1455 °C) and the boiling point of Mg (1090 °C). In this study, elemental powder mixtures of Mg and 30 at% Ni were processed by high-pressure torsion (HPT) to synthesize the Mg2Ni intermetallic compound through mechanical methods. The formation of 11 wt% of Mg2Ni after 50 turns of HPT was confirmed by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS), reaching a maximum of 59 wt% after 100 turns. Rietveld refinement confirmed a nanocrystalline size for the Mg2Ni phase synthesized via HPT. Hydrogenation tests showed that the Mg-Ni synthesized by HPT can absorb hydrogen at 350 °C even after several weeks of air exposure. Furthermore, a maximum absorption capacity of 3.8 wt% was reached after 20 h of hydrogen exposure for the sample with 100 turns. This capacity is close to the theoretical capacity of 3.9 wt% for this composition. The results confirm that combining HPT with subsequent heat treatment is an efficient strategy to increase the Mg2Ni fraction after HPT processing.
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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) | 0.001 | 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".