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Record W2002635816 · doi:10.1002/cjce.20623

Influence of reaction conditions and red brick on fast pyrolysis of rice residue (husk and straw) in a spout‐fluid bed

2011· article· en· W2002635816 on OpenAlexvenueaboutno aff
Rui Li, Zhaoping Zhong, Baosheng Jin, Xiaoxiang Jiang, Chun‐Hua Wang, Anqi Zheng

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsHuskPyrolysisStrawHeat of combustionMaterials scienceSawdustChemistryResidue (chemistry)CharPulp and paper industryCombustionBotanyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Fast pyrolysis of rice residue (husk and straw) was carried out in a spout‐fluid bed. In this study, the effects of reaction conditions (pyrolysis temperature, flow state, feed rate and feed size) and red brick (RB) using as bed material on the pyrolysis product distribution and bio‐oil qualities were investigated. Two phases composed the bio‐oil obtained from fast pyrolysis of rice residue. The results showed that at around 460°C the bio‐oil yields could reach the maxima, which were 48.2% and 53.1% for rice husk and straw respectively. Due to the heat and mass transfer motion, higher yields of bio‐oil and organics in upper phase could be obtained in spout‐fluid state compared with fluid state, which indicated that the spout‐fluid state might be more beneficial for fast pyrolysis. In additional, lower feed rates and larger particle sizes were found unfavourable for the bio‐oil production. The application of RB as bed material instead of quartz sand (QS) resulted in less bio‐oil and char, but more organics in upper phase. Furthermore, the quality of the upper phases was improved by RB, with the characteristics of high heating value and lower water and oxygen contents than QS. © 2011 Canadian Society for Chemical Engineering

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)0.000
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 score0.009
Threshold uncertainty score0.350

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 head0.007
GPT teacher head0.170
Teacher spread0.164 · 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.

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

Citations20
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicThermochemical Biomass Conversion ProcessesFrench-language works237,207