Hydrogen‐Based Superconductors: Superconducting Mechanisms under Pressure Tuning and Future Development
Bibliographic record
Abstract
Comprehensive Summary Hydride superconductors are promising candidates for high‐temperature superconductivity across a wide pressure range. This review presents a comprehensive review of their structural, electronic, and superconducting properties, with a focus on how pressure influences phase stability and enhances critical temperature ( T c ). We categorize hydrides into three pressure regimes: ambient pressure, low pressure (<100 GPa), and high pressure (>100 GPa). Ambient pressure compounds, such as perovskite‐like hydrides and SM 2 TMH 6 structures, exhibit moderate T c values. Low‐pressure hydrides benefit from unique strategies like molecular doping and electron precompression to improve their T c . The high‐pressure hydrides exhibit higher T c values, including room‐temperature superconductivity, but require extreme conditions for synthesis and characterization. We also highlight recent theoretical and experimental advances, outlining current challenges and prospects. This review not only highlights the potential of hydride superconductors but also provides a roadmap for future research in this exciting and rapidly developing field. Key Scientists
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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".