MétaCan
Menu
Back to cohort
Record W2252668247 · doi:10.1038/srep11381

First-principles study on the structural and electronic properties of metallic HfH2 under pressure

2015· article· en· W2252668247 on OpenAlexaff
Yunxian Liu, Xiaoli Huang, Defang Duan, Fubo Tian, Hanyu Liu, Da Li, Zhonglong Zhao, Xiaojing Sha, Hongyu Yu, Huadi Zhang, Bingbing Liu, Tian Cui

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsUniversity of Saskatchewan
FundersProgram for Changjiang Scholars and Innovative Research Team in UniversityNational Key Research and Development Program of ChinaJilin UniversityChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsIonic bondingMetalAtom (system on chip)Crystal structureCharge (physics)HydrideSuperconductivityDensity functional theoryElectron densityChemistryElectronic structureCrystallographyCharge densityPhase (matter)Materials scienceElectronCondensed matter physicsComputational chemistryIonPhysics

Abstract

fetched live from OpenAlex

The crystal structures and properties of hafnium hydride under pressure are explored using the first-principles calculations based on density function theory. The material undergoes pressure-induced structural phase transition I4/mmm → Cmma → P21/m at 180 and 250 GPa, respectively, and all of these structures are metallic. The superconducting critical temperature Tc values of I4/mmm, Cmma, and P21/m are 47-193 mK, 5.99-8.16 K and 10.62-12.8 K at 1 atm, 180 and 260 GPa, respectively. Furthermore, the bonding nature of HfH2 is investigated with the help of the electron localization function, the difference charge density and Bader charge analyses, which show that HfH2 is classified as a ionic crystal with the charges transferring from Hf atom to H.

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)0.003
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 score0.013
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.074
GPT teacher head0.283
Teacher spread0.210 · 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

Citations39
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueScientific ReportsSame topicBoron and Carbon Nanomaterials ResearchFrench-language works237,207