MétaCan
Menu
Back to cohort
Record W2780231153 · doi:10.1149/2.1451714jes

Factors Affecting the Performance and Applicability of SrTiO<sub>3</sub>Photoelectrodes for Photoinduced Cathodic Protection

2017· article· en· W2780231153 on OpenAlexafffund
Yao Yang, Y. Frank Cheng

Bibliographic record

VenueJournal of The Electrochemical Society · 2017
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsMaterials scienceCathodic protectionCathodeScavengerCarbon steelCorrosionPhotoelectric effectCarbon fibersChemical engineeringMetallurgyOptoelectronicsPhotochemistryComposite materialElectrodeElectrochemistryChemistryRadicalComposite numberOrganic chemistry

Abstract

fetched live from OpenAlex

In this work, various factors affecting the applicability and performance of prepared SrTiO3 photoelectrodes for photoinduced cathodic protection (CP) were investigated. The capability of the photoelectrode for photoinduced CP depends on the type of steels to be protected. A higher photo current density is required to cathodically protect X52 carbon steel than 304 stainless steel. Threshold areas of the photoelectrode relative to that of the cathode exist for both steels to enable photoinduced CP. The threshold area ratio of the SrTiO3 photoelectrode to X52 carbon steel is 8: 1 in 3.5 wt% NaCl solution, while, for 304 stainless steel, the area ratio of 1: 1 is sufficient for photoinduced CP. The photoinduced CP performance depends on the hole scavenger used in the photoelectrode cell. Na2S is an effective hole scavenger, and both X52 carbon and 304 stainless steels are cathodically polarized by photoelectrons to sufficiently negative values for a full CP. Moreover, the SrTiO3 photoelectrode can fully protect X52 steel only when the light intensity is up to 125 mW/cm2, while a light intensity of 50 mW/cm2 enables a full CP on 304 stainless steel. The photoinduced CP performance is also subject to the corrosivity of the solutions.

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)0.001
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 score0.019
Threshold uncertainty score0.327

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 integrity0.0000.001
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 head0.018
GPT teacher head0.229
Teacher spread0.212 · 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 designBench or experimental
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

Citations24
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicConcrete Corrosion and DurabilityFrench-language works237,207