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Record W4321598966 · doi:10.1038/s41467-023-36726-3

Renewable formate from sunlight, biomass and carbon dioxide in a photoelectrochemical cell

2023· article· en· W4321598966 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.

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsMcGill University
FundersGovernment of Jiangsu ProvinceSoutheast UniversityNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsFormateRenewable energyBiomass (ecology)Environmental scienceMaterials scienceCarbon dioxideFaraday efficiencyFossil fuelNanotechnologyChemistryElectrochemistryCatalysisOrganic chemistryElectrodeEcology

Abstract

fetched live from OpenAlex

Abstract The sustainable production of chemicals and fuels from abundant solar energy and renewable carbon sources provides a promising route to reduce climate-changing CO 2 emissions and our dependence on fossil resources. Here, we demonstrate solar-powered formate production from readily available biomass wastes and CO 2 feedstocks via photoelectrochemistry. Non-precious NiOOH/α-Fe 2 O 3 and Bi/GaN/Si wafer were used as photoanode and photocathode, respectively. Concurrent photoanodic biomass oxidation and photocathodic CO 2 reduction towards formate with high Faradaic efficiencies over 85% were achieved at both photoelectrodes. The integrated biomass-CO 2 photoelectrolysis system reduces the cell voltage by 32% due to the thermodynamically favorable biomass oxidation over conventional water oxidation. Moreover, we show solar-driven formate production with a record-high yield of 23.3 μmol cm −2 h −1 as well as high robustness using the hybrid photoelectrode system. The present work opens opportunities for sustainable chemical and fuel production using abundant and renewable resources on earth—sunlight, biomass and CO 2 .

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.998

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)0.0000.000

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 head0.011
GPT teacher head0.280
Teacher spread0.268 · 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