Catalyzed Light Hydride Nanomaterials Embedded in a Micro-Channels Hydrogen Storage Container
Bibliographic record
Abstract
Activated alloys synthesized by arc-melting were examined as catalysts for improving the hydrogen sorption characteristics of nanostructured magnesium hydride, proposed as a reversible hydrogen storage material. The MgH(2)-catalyst absorbing materials were prepared by ball milling of pure MgH(2) with hydrided Zr(47)Ni(53), Zr(9)Ni(11), and other alloys investigated. The nanostructured MgH(2)-intermetallic systems were tested at 250 degrees C and catalyst addition of eutectoid Zr(47)Ni(53) resulted in the fastest desorption time and highest initial desorption rate. The catalyzed Mg-hydride with activated Zr(9)Ni(11) and Zr(7)Ni(10) phases showed fast desorption kinetics. Moreover, the results demonstrated that the composition of dispersed Zr(x)Ni(y)catalysts has a strong influence on the amount of accumulated hydrogen and desorption rate of Mg-nanocomposite. Part two covers advanced micro-channels hydrogen storage module design based on the results of semi-empirical computer simulations of heat and mass transfers in the container. The micro-channels reservoir concept offers many advantages over the conventional metal hydride hydrogen storage system. It is a micro-structured system that can pack a lot of power into a small space and dissipate effectively the heat of the sorption reactions. This review summarizes recent patents related to CNTS.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".