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Record W4303621791 · doi:10.53063/synsint.2022.23119

Optimum temperature, time and atmosphere of precursor pyrolysis for synthesis of B4C ceramics

2022· article· en· W4303621791 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSynthesis and Sintering · 2022
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsnot available
Fundersnot available
KeywordsPyrolysisAtmosphere (unit)ArgonMaterials scienceCeramicChemical engineeringMetallurgyChemistryOrganic chemistryMeteorology

Abstract

fetched live from OpenAlex

In this paper, the variables of the pyrolysis operation such as temperature, time, and atmosphere were studied and optimized. At first, the effect of increasing pyrolysis time at lower temperatures was investigated to understand the mutual influence of pyrolysis time and temperature in enhancing the efficiency of B4C synthesis. Then, three pyrolysis atmospheres were selected to find the optimal conditions: burial method in box furnace (air), pyrolysis in tubular furnace (argon), and pyrolysis in box furnace (air). The pyrolyzed powders were finally located inside the tubular furnace at 1500 °C for 4 h under argon atmosphere to synthesize B4C ceramics. X-ray diffractometry (XRD) was employed to determine the optimal processing conditions. The temperature of 600 °C and the holding time of 2 h were selected as the optimal pyrolysis conditions. Meanwhile, the burial method was chosen as the best atmosphere despite having a higher percentage of impurity because of the much lower cost compared to the argon atmosphere.

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.

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 score0.192
Threshold uncertainty score0.625

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 head0.006
GPT teacher head0.178
Teacher spread0.172 · 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