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Record W4391884455 · doi:10.1021/acscatal.3c06046

Solar-Driven Cellulose Photorefining into Arabinose over Oxygen-Doped Carbon Nitride

2024· article· en· W4391884455 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

VenueACS Catalysis · 2024
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsUniversity of Calgary
FundersCanada First Research Excellence Fund
KeywordsCelluloseChemistryArabinoseOxygenFormic acidOxidative phosphorylationRadicalCarbon fibersOrganic chemistryMaterials scienceBiochemistryXylose

Abstract

fetched live from OpenAlex

Biomass photorefining is a promising strategy to address the energy crisis and transition toward carbon carbon-neutral society. Here, we demonstrate the feasibility of direct cellulose photorefining into arabinose by a rationally designed oxygen-doped polymeric carbon nitride, which generates favorable oxidative species (e.g., O 2 –, • OH) for selective oxidative reactions at neutral conditions. In addition, we also illustrate the mechanism of the photocatalytic cellulose to arabinose conversion by density functional theory calculations. The oxygen insertion derived from oxidative radicals at the C1 position of glucose within cellulose leads to oxidative cleavage of β-1,4 glycosidic linkages, resulting in the subsequent gluconic acid formation. The following decarboxylation process of gluconic acid via C1–C2 α-scissions, triggered by surface oxygen-doped active sites, generates arabinose and formic acid, respectively. This work not only offers a mechanistic understanding of cellulose photorefining to arabinose but also sets up an example for illuminating the path toward direct cellulose photorefining into value-added bioproducts under mild conditions.

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 categoriesMeta-epidemiology (narrow)
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 score0.187
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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