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Reduction behaviour of rice husk ash for preparation of high purity silicon

2011· article· en· W2077612703 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2011
Typearticle
Languageen
FieldEngineering
TopicBauxite Residue and Utilization
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsHuskSiliconReduction (mathematics)Materials sciencePulp and paper industryChemistryMetallurgyMathematicsEngineeringBotany

Abstract

fetched live from OpenAlex

The reduction of rice husk ash (RHA) silica for the preparation of high purity silicon was studied using magnesium as the reducing agent. Composite magnesium–RHA pellets with magnesium content varying from 0–25 wt% in excess of stoichiometry requirement were made and heated in the temperature range of 600–900 oC under flowing argon. It was found through differential thermal analysis (DTA) and temperature profile recording that the reaction of RHA silica with magnesium was triggered at about 575 oC. Quantitative XRD analyses of the reduction products showed that both initial magnesium content of the pellets and the reduction dwell temperature had a significant influence on the yield of silicon. In this study, a charge with 5 wt% magnesium in excess of the stoichiometric amount at reduction temperature of 900 oC gave a maximum silicon yield.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.988

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 head0.018
GPT teacher head0.226
Teacher spread0.208 · 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