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Record W2883996816 · doi:10.5772/intechopen.74602

Innovative Microreactors for Low-grade Feedstock Gasification

2018· book-chapter· en· W2883996816 on OpenAlexaff
Said Samih, Sherif Farag, Jamal Chaouki

Bibliographic record

VenueInTech eBooks · 2018
Typebook-chapter
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMicroreactorRaw materialProcess engineeringMaterials scienceEngineeringChemistry

Abstract

fetched live from OpenAlex

The first fluidized bed thermogravimetric analyzer (FBTGA) has been developed. The proof of concept of the FBTGA has been carried out on the thermal decomposition of calcium hydroxide. The kinetics and modeling of coal pyrolysis and gasification were investigated in the FBTGA. The obtained activation energies for the individual gases that are produced from coal pyrolysis are 19 to 21% lower than those found for similar coals in the literature. This decrease in the activation energies is explained by a temperature gradient of 185 to 209C. For the CO shift reaction, the resulting activation energy is 46.6 kcal/ mol, increasing by 20% from the one used in the literature. The second reactor presented in this work is a TGA powered by electromagnetic irradiation. As an application for this reactor, a novel kinetic model based on a dual attempt to predict not only the yield but also the composition of bio-oil is presented. The validation of the developed models demonstrated an excellent capability of predicting the yield and quality of the produced oil. The third reactor is a saddle reactor, which consists of two V-shaped pairs of arms and minimizes the impact of the heat and mass transfer limitation on chemical reactions.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.552
Threshold uncertainty score1.000

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 head0.026
GPT teacher head0.243
Teacher spread0.216 · 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
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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