MétaCan
Menu
Back to cohort
Record W2562354686 · doi:10.1149/2.0281702jes

Spontaneous Reduction of Cupric Complex on Titanium Oxides in Acidic Sulfate–Chloride Media

2016· article· en· W2562354686 on OpenAlexafffund
Jing Liu, Zihe Ren, Edouard Asselin

Bibliographic record

VenueJournal of The Electrochemical Society · 2016
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsX-ray photoelectron spectroscopyChlorideTitaniumCopperOxideInorganic chemistrySulfateAnodizingSecondary ion mass spectrometryTitanium oxideChemistryAlloyElectrochemistryMaterials scienceIonChemical engineeringMetallurgyElectrodePhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

It is discovered in this work that Cu(II) can be spontaneously reduced on titanium oxides in a mixed sulfate-chloride solution at 85°C. X-ray photoelectron spectroscopy (XPS) suggests that after reaction, copper species exist in an oxidation state lower than 2+. Analysis using X-ray powder diffraction (XRD) shows that the reduced copper species could exist in the form of a CuTi alloy. Time of flight secondary ion mass spectrometry (ToF-SIMS) revealed the depth profile of copper signals in the oxide films. ToF-SIMS results demonstrated that copper signals co-existed with titanium oxide signals in the anodized oxide films, and copper species can diffuse deeply into the porous films within 60 minutes of immersion. Further electrochemical and surface characterizations have confirmed that the presence of chloride ions is a crucial factor for the spontaneous reduction of Cu(II). This phenomenon reveals the role of Cu(II) in a mixed sulfate-chloride solution and its effect on titanium oxide films. It also provides an approach to incorporate a CuTi alloy into titanium oxide films.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.220
Teacher spread0.207 · 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

Citations2
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicMetal Extraction and BioleachingFrench-language works237,207