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Record W4401371130 · doi:10.1016/j.oceram.2024.100653

A comparative assessment of thermal conductivity of functionally graded and equivalent non-graded ZrB2–B4C–SiC–LaB6 ultra-high-temperature ceramic composites

2024· article· en· W4401371130 on OpenAlex
Ajit Kumar Naik, Lava Kumar Pillari, Kyle Lessoway, Lukas Bichler, Tapas Laha, Siddhartha Roy

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen Ceramics · 2024
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceComposite materialThermal conductivityCeramicFunctionally graded materialConductivityMaterial properties

Abstract

fetched live from OpenAlex

In this study, functionally graded ZrB2–B4C–SiC–LaB6 composite materials (FGMs) with potential applications in hypersonic aircraft thermal protection systems were fabricated using spark plasma sintering. A systematic study of the thermal conductivity of the FGM, the conductivity of respective FGM layers, and the equivalent non-graded composites, was performed from room temperature up to 450 °C. The results suggest that the thermal conductivity of the FGMs (in the through-thickness direction) and their equivalent non-graded composites ranged between 25 and 34.9 W/mK, which was ∼60 % less than ZrB2. While the overall thermal conductivity of the FGM and equivalent non-graded composites were similar, in the FGM, the topmost layer with high ZrB2-content displayed up to 245 % higher thermal conductivity than the bottom layer with high B4C content. A systematic comparison between experimentally determined conductivity and relevant thermal conductivity models was conducted.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.031
GPT teacher head0.323
Teacher spread0.292 · 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