MétaCan
Menu
Back to cohort
Record W2749402232 · doi:10.1038/s41467-017-00420-y

Photoelectrochemical oxidation of organic substrates in organic media

2017· article· en· W2749402232 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

VenueNature Communications · 2017
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCanada Research ChairsCanadian Institute for Advanced Research
KeywordsCatalysisReagentChemistryWater splittingPhotochemistryOrganic synthesisPhotoelectrochemistryNanotechnologyMaterials scienceCombinatorial chemistryChemical engineeringEnvironmental chemistryElectrochemistryOrganic chemistryPhotocatalysis

Abstract

fetched live from OpenAlex

Abstract There is a global effort to convert sunlight into fuels by photoelectrochemically splitting water to form hydrogen fuels, but the dioxygen byproduct bears little economic value. This raises the important question of whether higher value commodities can be produced instead of dioxygen. We report here photoelectrochemistry at a BiVO 4 photoanode involving the oxidation of substrates in organic media. The use of MeCN instead of water enables a broader set of chemical transformations to be performed (e.g., alcohol oxidation and C-H activation/oxidation), while suppressing photocorrosion of BiVO 4 that otherwise occurs readily in water, and sunlight reduces the electrical energy required to drive organic transformations by 60%. These collective results demonstrate the utility of using photoelectrochemical cells to mediate organic transformations that otherwise require expensive and toxic reagents or catalysts.

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)0.001
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 score0.020
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0020.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.311
Teacher spread0.294 · 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