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Record W4292651777 · doi:10.21203/rs.3.rs-1907263/v1

SiO2 aerogel multiscale reinforced by glass fibers and SiC nanowhiskers for thermal insulation

2022· preprint· en· W4292651777 on OpenAlexaff
Qiong Wu, Lixia Yang, Zhaofeng Chen, Mengmeng Yang, Tianlong Liu, Manna Li, Phalguni Mukhopadhyaya

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldChemistry
TopicAerogels and thermal insulation
Canadian institutionsUniversity of Victoria
FundersNational Key Research and Development Program of ChinaNanjing UniversityNanjing University of Aeronautics and AstronauticsNational Natural Science Foundation of China
KeywordsAerogelMaterials scienceThermal conductivityComposite materialThermal insulationHeat transferThermal

Abstract

fetched live from OpenAlex

Abstract SiO 2 aerogel attracts much interest as thermal insulation material due to ultra-low density and excellent thermal performance at room temperature. However, the poor mechanical property and a mass of heat transfer by radiation in high temperature limit application of aerogels. Herein, a novel aerogel composites multiscale reinforced by glass fibers with SiC nanowhiskers (SiC nw ) (AFW) was prepared. SiC nw were evenly distributed in glass fibers felts by freezing-drying method to form a uniform multiscale felts. The SiC nw inside felts provided more contact point with aerogel to increase the interfacial adhesion force so that compressive stress of AFW with 4% volume fraction SiC nw was increased to 0.29MPa. SiC nw blocked infrared radiation to decrease the heat transfer. Therefore, Even though SiC nw raised thermal conductivity of aerogels at room temperature, thermal conductivity at 500℃ of AFW with was only 0.040 W/(m·K). In another word SiC nw reduced the sensitivity of thermal conductivity to temperature. AFW shows potential in the field of medium and high temperature insulation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.046
GPT teacher head0.356
Teacher spread0.309 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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