Functional Materials Based on Metal Hydrides
Bibliographic record
Abstract
Our extreme and growing energy consumption, based on fossil fuels, has significantly increased the levels of carbon dioxide in the atmosphere, which may lead to global and irreversible climate changes. We have plenty of renewable energy, e.g., sun and wind, but the fluctuations over time and geography call for a range of new ideas and, possibly, novel technologies. The most difficult challenge appears to be the development of the efficient and reliable storage of renewable energy. Hydrogen has long been considered as a potential means of energy storage; however, storage of hydrogen is also challenging. Therefore, a wide range of hydrogen-containing materials, with energy-related functions, has been discovered over the past few decades. The chemistry of hydrogen is very diverse, and so also are the new hydrides that have been discovered, not only in terms of structure and composition but also in terms of their properties. This has led to a wide range of new possible applications of metal hydrides that permeate beyond solid-state hydrogen storage. A variety of new hydrides, proposed as battery materials, has been discovered. These can exploit properties as fast ion conductors or as conversion-type electrodes with much higher potential energy capacities, compared to materials currently used in commercial batteries. Solar heat storage is also an area of great potential for metal hydrides, in principle offering orders of magnitude better storage performance than phase change materials. Recently, hydrides with optical and superconducting properties have also been investigated. This Special Issue of Inorganics, entitled “Functional Materials Based on Metal Hydrides”, is dedicated to the full range of emerging electronic, photonic, and energy-related, inorganic, hydrogen-containing materials.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".