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Record W2159394592 · doi:10.1002/cssc.201500538

Reduced Graphene Oxide Bipolar Membranes for Integrated Solar Water Splitting in Optimal pH

2015· article· en· W2159394592 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

VenueChemSusChem · 2015
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Manitoba
KeywordsGrapheneMaterials scienceOverpotentialOxideMembraneDissociation (chemistry)Chemical engineeringCatalysisOhmic contactWater splittingNanotechnologyLayer (electronics)PhotocatalysisChemistryElectrodeElectrochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The integration of light absorbers and catalysts for the water splitting process requires a membrane capable of both ion and electron management and product separation to realize efficient solar fuels systems. Bipolar membranes can maintain a pH gradient for optimal reaction conditions by the dissociation of water. Such membranes that contain graphene in the interfacial layer are fabricated by the chemical reduction of a uniformly deposited graphene oxide layer to convert sp(3) catalyst regions to sp(2) conductive regions. The resulting electrical and water dissociation properties are optimized by adjusting the exposure conditions, and treatments of less than 5 min render an interface that exceeds the conductivity requirements for integrated solar water splitting and increases the overpotential by <0.3 V. Integration with photoelectrodes is examined by characterizing the electrical interface formed between graphene and Si microwires, and we found that efficient Ohmic junctions are possible.

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)0.001
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 score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.256
Teacher spread0.228 · 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