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Record W4391259647 · doi:10.1038/s41467-024-44741-1

Indirect H2O2 synthesis without H2

2024· article· en· W4391259647 on OpenAlexafffund
Arthur G. Fink, Roxanna S. Delima, Alexandra R. Rousseau, Camden Hunt, Natalie E. LeSage, Aoxue Huang, Monika Stolar, Curtis P. Berlinguette

Bibliographic record

VenueNature Communications · 2024
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of British Columbia
FundersStewart Blusson Quantum Matter Institute, University of British ColumbiaCanada First Research Excellence FundCanada Research ChairsCanadian Institute for Advanced Research
KeywordsAnthraquinoneHydrogen peroxideElectrochemistryAnthraquinonesCarbon fibersHydrogenChemistryChemical engineeringMaterials scienceElectrodeNanotechnologyOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Industrial hydrogen peroxide (H 2 O 2 ) is synthesized using carbon-intensive H 2 gas production and purification, anthraquinone hydrogenation, and anthrahydroquinone oxidation. Electrochemical hydrogenation (ECH) of anthraquinones offers a carbon-neutral alternative for generating H 2 O 2 using renewable electricity and water instead of H 2 gas. However, the H 2 O 2 formation rates associated with ECH are too low for commercialization. We report here that a membrane reactor enabled us to electrochemically hydrogenate anthraquinone (0.25 molar) with a current efficiency of 70% at current densities of 100 milliamperes per square centimeter. We also demonstrate continuous H 2 O 2 synthesis from the hydrogenated anthraquinones over the course of 48 h. This study presents a fast rate of electrochemically-driven anthraquinone hydrogenation (1.32 ± 0.14 millimoles per hour normalized per centimeter squared of geometric surface of electrode), and provides a pathway toward carbon-neutral H 2 O 2 synthesis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.277
Teacher spread0.263 · 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 designNot applicable
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

Citations57
Published2024
Admission routes2
Has abstractyes

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