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Record W4400864943 · doi:10.1002/advs.202405561

Prediction of Room‐Temperature Superconductivity in Quasi‐Atomic H<sub>2</sub>‐Type Hydrides at High Pressure

2024· article· en· W4400864943 on OpenAlexafffund
Qiwen Jiang, Defang Duan, Hao Song, Zihan Zhang, Zihao Huo, Shuqing Jiang, Tian Cui, Yansun Yao

Bibliographic record

VenueAdvanced Science · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Saskatchewan
FundersNational Key Research and Development Program of ChinaFundamental Research Funds for the Central UniversitiesJilin UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsSuperconductivityAntibonding molecular orbitalCondensed matter physicsHigh pressureFermi levelMaterials scienceMetallic hydrogenElectronPhysicsAtomic orbitalMetalThermodynamicsMetallurgyNuclear physics

Abstract

fetched live from OpenAlex

Abstract Achieving superconductivity at room temperature (RT) is a holy grail in physics. Recent discoveries on high‐ T c superconductivity in binary hydrides H 3 S and LaH 10 at high pressure have directed the search for RT superconductors to compress hydrides with conventional electron–phonon mechanisms. Here, an exceptional family of superhydrides is predicated under high pressures, M H 12 ( M = Mg, Sc, Zr, Hf, Lu), all exhibiting RT superconductivity with calculated T c s ranging from 313 to 398 K. In contrast to H 3 S and LaH 10 , the hydrogen sublattice in M H 12 is arranged as quasi‐atomic H 2 units. This unique configuration is closely associated with high T c , attributed to the high electronic density of states derived from H 2 antibonding states at the Fermi level and the strong electron–phonon coupling related to the bending vibration of H 2 and H‐ M ‐H. Notably, MgH 12 and ScH 12 remain dynamically stable even at pressure below 100 GPa. The findings offer crucial insights into achieving RT superconductivity and pave the way for innovative directions in experimental research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.210
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2024
Admission routes2
Has abstractyes

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