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Record W3127225730 · doi:10.1063/5.0036832

IrN4 and IrN7 as potential high-energy-density materials

2021· article· en· W3127225730 on OpenAlexaff
Xin Du, Yansun Yao, Jing Wang, Qiuping Yang, Guochun Yang

Bibliographic record

VenueThe Journal of Chemical Physics · 2021
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsUniversity of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsNitrideMaterials scienceEnergy densityAmbient pressurePlanarMetalNanotechnologyThermodynamicsMetallurgyEngineering physicsComputer sciencePhysics

Abstract

fetched live from OpenAlex

Transition metal nitrides have attracted great interest due to their unique crystal structures and applications. Here, we predict two N-rich iridium nitrides (IrN4 and IrN7) under moderate pressure through first-principles swarm-intelligence structural searches. The two new compounds are composed of stable IrN6 octahedrons and interlinked with high energy polynitrogens (planar N4 or cyclo-N5). Balanced structural robustness and energy content result in IrN4 and IrN7 being dynamically stable under ambient conditions and potentially as high energy density materials. The calculated energy densities for IrN4 and IrN7 are 1.3 kJ/g and 1.4 kJ/g, respectively, comparable to other transition metal nitrides. In addition, IrN4 is predicted to have good tensile (40.2 GPa) and shear strengths (33.2 GPa), as well as adequate hardness (20 GPa). Moderate pressure for synthesis and ambient pressure recoverability encourage experimental realization of these two compounds in near future.

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 score0.047
Threshold uncertainty score0.633

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)0.0010.000

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 head0.239
Teacher spread0.230 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

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