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Demixing Instability in Dense Molten<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>MgSiO</mml:mi><mml:mn>3</mml:mn></mml:msub></mml:math>and the Phase Diagram of MgO

2013· article· lv· W2331734780 on OpenAlexaff
Brian Boates, Stanimir Bonev

Bibliographic record

VenuePhysical Review Letters · 2013
Typearticle
Languagelv
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsDalhousie University
FundersU.S. Department of Energy
KeywordsComputer science

Abstract

fetched live from OpenAlex

The phase diagrams of MgSiO3 and MgO are studied from first-principles theory for pressures and temperatures up to 600 GPa and 20,000 K. Through the evaluation of finite-temperature Gibbs free energies, using density-functional theory within the generalized gradient approximation as well as with hybrid exchange-correlation functionals, we find evidence for a vast pressure-temperature regime where molten MgSiO3 decomposes into liquid SiO2 and solid MgO, with a volume change of approximately 1.2%. The demixing transition is driven by the crystallization of MgO--the reaction only occurs below the high-pressure MgO melting curve. The predicted transition pressure at 10,000 K is in close proximity to an anomaly reported in recent laser-driven shock experiments of MgSiO3. We also present new results for the high-pressure melting curve of MgO and its B1-B2 solid phase transition, with a triple point at 364 GPa and 12,000 K.

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 score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
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 head0.015
GPT teacher head0.249
Teacher spread0.235 · 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

Citations59
Published2013
Admission routes1
Has abstractyes

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