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Fenton Depolymerization of Cellulosic Biomass in Modified Cuprammonium Solution

2015· article· en· W1600949294 on OpenAlexafffund
Jing Cao, Joe R. Zhao

Bibliographic record

VenueBioResources · 2015
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsTri Y Environmental Research Institute (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDepolymerizationCellulosic ethanolBiomass (ecology)Pulp and paper industryMaterials scienceCellulosePolymer scienceChemical engineeringOrganic chemistryChemistryPolymer chemistryAgronomyEngineering

Abstract

fetched live from OpenAlex

This preliminary study developed a novel cellulose pretreatment method for cost-effective cellulosic utilization using a modified cuprammonium solution as a solvent to dissolve cellulose followed by molecular oxygen/Fenton depolymerization. The modified cuprammonium solution is composed of cuprammonium solution and a special catalyst that could efficiently enhance cellulosic oxygen sensitivity and therefore improve cellulosic depolymerization. The molecular oxygen depolymerization and Fenton depolymerization of cellulosic biomass dissolved in the modified cuprammonium solution were investigated. The results demonstrate that the Fenton reaction efficiently depolymerized the cellulose dissolved in the modified cuprammonium solution and reached the monomers with no loss of organic carbon, and almost all the cellulose maintained solubility without reagglomeration after cuprammonium was removed. Molecular oxygen oxidation reduced the cellulose average degree of polymerization (DP) to approximately 4 with less cost, and the oxygen pre-oxidation increased the H2O2 utilization in the Fenton depolymerization and remarkably reduced the H2O2 requirement.

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 score0.007
Threshold uncertainty score0.426

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 head0.049
GPT teacher head0.289
Teacher spread0.240 · 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

Citations3
Published2015
Admission routes2
Has abstractyes

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