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Record W4407945104 · doi:10.1002/cphc.202401150

High‐Pressure Stability and Electronic Properties of Sodium‐Rich Nitrides: Insights from First‐Principles Calculations

2025· article· en· W4407945104 on OpenAlexaff
Qiuyue Li, Qiuping Yang, Shuai Han, Li Fei, Yansun Yao, Guochun Yang

Bibliographic record

VenueChemPhysChem · 2025
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversity of Saskatchewan
FundersNatural Science Foundation of Hebei ProvinceNational Natural Science Foundation of China
KeywordsNitridePhase (matter)Chemical physicsMaterials scienceStoichiometryRedistribution (election)Electronic structurePhase transitionSodiumGrapheneHigh pressureInstabilityChemistryCondensed matter physicsNanotechnologyThermodynamicsPhysical chemistryComputational chemistryPhysicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract Using first‐principles structure search calculations, we investigated the phase stability of sodium‐nitrogen (Na−N) compounds under high pressure. Our study reveals that increasing pressure promotes the formation of Na‐rich nitrides, leading to the prediction of three previously unreported stoichiometries: Na 2 N, Na 5 N, and Na 8 N. Notably, the electride Na 5 N undergoes a pressure‐induced structural transition from a P 6/ mmm to a P 6 3 / mmc phase. This transformation is characterized by spatial reorientation and redistribution of interstitial anionic electrons (IAEs). In the P 6 3 / mmc phase, IAEs adopt a zero‐dimensional, triangular‐like configuration, whereas in the low‐pressure P 6/ mmm phase, they form an interconnected, graphene‐like network. With increasing pressure, P 6 3 / mmc phase undergoes a transition from metallic to semiconducting behavior due to the increased interaction between sodium and IAEs. Additionally, C 2/ m Na 8 N, featuring triangular‐ and ship‐like IAEs, is predicted to exhibit superconductivity. Our findings provide new insights into the behavior and stability of Na‐rich nitrides under high‐pressure conditions.

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)0.000
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 score0.012
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.202
Teacher spread0.185 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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