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Record W2549425694 · doi:10.1021/acs.jpclett.6b02444

Coexistence of Superconductivity and Superhardness in Beryllium Hexaboride Driven by Inherent Multicenter Bonding

2016· article· en· W2549425694 on OpenAlexaff
Lailei Wu, Biao Wan, Hanyu Liu, Huiyang Gou, Yansun Yao, Zhiping Li, Jingwu Zhang, Faming Gao, Ho‐kwang Mao

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2016
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsSuperconductivityBerylliumCondensed matter physicsMaterials sciencePhysicsNuclear physics

Abstract

fetched live from OpenAlex

Unique multicenter bonding in boron-rich materials leads to the formation of complex structures and intriguing properties. Here global structural searches are performed to unearth the structure of beryllium hexaboride (BeB 6 ) synthesized decades ago. Three BeB 6 phases (α, β, and γ) were predicted to be stable at ambient and high pressures. The ground state at ambient pressure, α-BeB 6, consists of a strong and uniformly distributed covalent B–B network, which results in exceptional elastic properties and a hardness of 46 GPa comparable to γ-B. Even more surprisingly, α-BeB 6 retains credible electron phonon coupling in the boron sublattice, and is predicted to be superconducting at 9 K. Above 4 GPa, β-BeB 6 is stabilized with alternating boron slabs and triangular beryllium layers analogous to the structure of MgB 2 . The β-BeB 6 is predicted to be superconducting at 24 K, similar to Nb 3 (Al,Ge). The γ-BeB 6 is stable above 340 GPa. The understanding of intrinsic multicenter-bonding mechanism and related properties demonstrated in the very example of BeB 6 provides new insights for the design of tunable multifunctional materials.

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 score0.002
Threshold uncertainty score0.250

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.262
Teacher spread0.248 · 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

Citations30
Published2016
Admission routes1
Has abstractyes

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