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Record W2059995124 · doi:10.1103/physrevb.77.052103

Metastable high-pressure single-bonded phases of nitrogen predicted via genetic algorithm

2008· article· en· W2059995124 on OpenAlexaff
Yansun Yao, John S. Tse, К. Tanaka

Bibliographic record

VenuePhysical Review B · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMetastabilityCrystal structureMaterials scienceCrystal structure predictionEnthalpyAtom (system on chip)NitrogenCrystallographyPhysicsAtomic physicsCondensed matter physicsThermodynamicsChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

The recently proposed genetic algorithm for crystal structure prediction combined with first-principles structural optimizations is used to investigate the high-pressure structures of solid nitrogen. Starting from a population of randomly generated eight-atom structures at $80\phantom{\rule{0.3em}{0ex}}\mathrm{GPa}$, the evolutionary process not only recovers the four lowest-energy nonmolecular structures (CG, $C2∕c$, black phosphorus, and $Cmcm$ chain) predicted theoretically or known experimentally, but also reveals a metastable single-bonded three-dimensional structure. The stability of this structure at $80\phantom{\rule{0.3em}{0ex}}\mathrm{GPa}$ is established by phonon calculations. At this pressure, the enthalpy of the structure is $0.17\phantom{\rule{0.3em}{0ex}}\mathrm{eV}$/atom higher than that of the cubic gauche phase. The energetic difference between this structure and other nonmolecular high-pressure phases is explained from analysis of the local structural motifs.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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

Citations78
Published2008
Admission routes1
Has abstractyes

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