MétaCan
Menu
Back to cohort
Record W2565476982 · doi:10.1103/physrevb.92.174106

Structures and stability of novel transition-metal<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>(</mml:mo><mml:mrow><mml:mi>M</mml:mi><mml:mspace width="0.16em"/><mml:mo>=</mml:mo><mml:mspace width="0.16em"/><mml:mi>Co</mml:mi><mml:mo>,</mml:mo><mml:mspace width="0.16em"/><mml:mi>Rh</mml:mi><mml:mo>,</mml:mo><mml:mspace width="0.16em"/><mml:mi>Co</mml:mi><mml:mspace width="0.16em"/><mml:mi mathvariant="normal">and</mml:mi><mml:mspace width="0.16em"/><mml:mi>Ir</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math>borides

2015· article· lv· W2565476982 on OpenAlexafffund
Yachun Wang, Lailei Wu, Yangzheng Lin, Qingyang Hu, Zhiping Li, Hanyu Liu, Yunkun Zhang, Huiyang Gou, Yansun Yao, Jingwu Zhang, Faming Gao, Ho‐kwang Mao

Bibliographic record

VenuePhysical Review B · 2015
Typearticle
Languagelv
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
FundersNatural Science Foundation of Hebei ProvinceDepartment of Education of Hebei ProvinceNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMaterials scienceStability (learning theory)Transition metalMetalConvex hullAlgorithmStoichiometryMachine learningCrystallographyPhysicsComputer scienceRegular polygonPhysical chemistryGeometryMathematicsChemistryMetallurgy

Abstract

fetched live from OpenAlex

Recent progress of high-pressure technology enables the synthesis of novel metal borides with diverse compositions and interesting properties. A precise characterization of these borides, however, is sometimes hindered by multiphase intergrowth and grain-size limitation in the synthesis process. Here, we theoretically explored new transition-metal borides $(M\phantom{\rule{0.16em}{0ex}}=\phantom{\rule{0.16em}{0ex}}\mathrm{Co}$, Rh, and Ir) using a global structure searching method and discovered a series of stable compounds in this family. The predicted phases display a rich variety of stoichiometries and distinct boron networks resulting from the electron-deficient environments. Significantly, we identified a new $\mathrm{Ir}{\mathrm{B}}_{1.25}$ structure as the long-sought structure of the first synthesized Ir-B compound. The simulated x-ray diffraction pattern of the proposed $\mathrm{Ir}{\mathrm{B}}_{1.25}$ structure matches well with the experiment, and the convex hull calculation establishes its thermodynamic stability. Results of the present paper should advance the understanding of transition-metal borides and stimulate experimental explorations of these new and promising 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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 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

Citations11
Published2015
Admission routes2
Has abstractyes

Explore more

Same venuePhysical Review BSame topicBoron and Carbon Nanomaterials ResearchFrench-language works237,207