MétaCan
Menu
Back to cohort
Record W4394576626 · doi:10.1111/jace.19815

Effect of calcium–magnesium–aluminum silicate composition on reaction behavior for X1‐Gd <sub>2</sub> SiO <sub>5</sub> and X2‐Er <sub>2</sub> SiO <sub>5</sub> environmental barrier coatings

2024· article· en· W4394576626 on OpenAlexaff
Ruihui Liang, Xin Zhong, Hong Du, Cui Hu, Fangxia Zhao, Zhenzhong Zhang, Yaran Niu, Xuebin Zheng

Bibliographic record

VenueJournal of the American Ceramic Society · 2024
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsMD Precision (Canada)
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsCorrosionMaterials scienceSilicateMagnesiumCoatingAluminiumCalcium silicatePhase (matter)CalciumMetallurgyChemical engineeringMineralogyComposite materialChemistry

Abstract

fetched live from OpenAlex

Abstract Rare‐earth (RE) silicates environmental barrier coatings (EBCs) are prone to accelerate failure resulted from molten calcium–magnesium–aluminum silicate (CMAS), which presents significant challenges to the design and development of durable EBCs. In this study, X1‐Gd 2 SiO 5 and X2‐Er 2 SiO 5 coatings were explored on their corrosion resistance to CMAS melts with different Ca/Si ratios (1.1, 0.75, 0.64, and 0.42) at 1350°C for 25 and 50 h, respectively. Results showed that with the Ca/Si ratio increasing, CMAS viscosity decreased and a more intense corrosion reaction with coatings occurred. Garnet phase was only observed in X2‐Er 2 SiO 5 coating corroded by CMAS with high Ca/Si ratios, which could be beneficial for improving corrosion resistance. The X2‐Er 2 SiO 5 phase, which is composed of [SO 4 ] and [REO 6 ]/[REO 7 ] polyhedrons, exhibits better corrosion resistance due to its more stable crystal structure, lower reactivity with CMAS, and the radius difference between the RE ions and Ca 2+ .

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 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)0.002
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 score0.034
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.249
Teacher spread0.241 · 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 teacher head, not a consensus.

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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Ceramic SocietySame topicAdvanced ceramic materials synthesisFrench-language works237,207