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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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

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