MétaCan
Menu
Back to cohort
Record W2901312986 · doi:10.1139/cjc-2018-0256

Pressure-induced metallization of condensed-phase RDX: molecular dynamic simulations in conjunction with MSST method

2018· article· en· W2901312986 on OpenAlexvenueno aff
Zi-Qiu Bai, Jing Chang, Guang‐Fu Ji, Ni-Na Ge

Bibliographic record

VenueCanadian Journal of Chemistry · 2018
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
FundersState Key Laboratory Cultivation Base for Nonmetal Composites and Functional MaterialsSouthwest University of Science and TechnologyNational Natural Science Foundation of China
KeywordsHydrostatic pressureShock (circulatory)AnisotropyChemistryPhase (matter)Crystal (programming language)Molecular dynamicsChemical physicsHydrostatic equilibriumPhase transitionShock waveShock response spectrumThermodynamicsMaterials scienceOpticsComputational chemistry

Abstract

fetched live from OpenAlex

The anisotropy of impact sensitivity and microscopic electron properties of the cyclotrimethylene trinitramine (C3H6N6O6) (RDX) under shock loading are investigated in our work. The simulation is performed using molecular dynamic (MD) simulations in conjunction with multi-scale shock technique (MSST). By calculating the microscopic electronic properties and combining the thermodynamic properties, we predict that the metallization pressure of the RDX crystal is approximately 170 GPa under shock loading, which is slightly less than the metallization pressure under hydrostatic pressure. We also found that the microscopic electronic properties are related to the impact sensitivity. When the shock loading is along the z direction, the time of the transition from the insulating state to the metallization of the RDX crystal lags behind the shock loading along the x or y direction. Therefore, we predict that the RDX crystal has a lower sensitivity when the shock loading is along the z direction.

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)0.001
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.238
Teacher spread0.232 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of ChemistrySame topicEnergetic Materials and CombustionFrench-language works237,207