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Record W4309900038 · doi:10.1080/1478422x.2022.2149048

Effects of solid deposits on the corrosion behaviour of titanium in high acidity and highly oxidising leaching solutions

2022· article· en· W4309900038 on OpenAlexafffund
Y. Liu, Edouard Asselin

Bibliographic record

VenueCorrosion Engineering Science and Technology The International Journal of Corrosion Processes and Corrosion Control · 2022
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsUniversity of British Columbia
FundersSenior Talent Foundation of Jiangsu UniversityNatural Sciences and Engineering Research Council of Canada
KeywordsCorrosionLeaching (pedology)MetallurgyMaterials scienceInertTitaniumOxidizing agentSolid solutionHigh-temperature corrosionChemistryEnvironmental science

Abstract

fetched live from OpenAlex

Solid minerals are ubiquitous and common deposits on Ti-lined process vessels in the hydrometallurgical industry. This work revealed the effects of inert solid deposits on the corrosion behaviour of Ti-2 in high acidity and highly oxidising leaching solutions. It was found that the deposit-covered Ti-2 had a higher corrosion rate ( CR ) than bare Ti-2. CR increased with increasing deposit thickness (up to 6 cm) and temperature. Solid deposits mainly affected the corrosion process of Ti by limiting the mass transfer of the oxidising Fe(III) from the bulk solution to the underlying Ti, thus affecting the stability of the protective passive film, and resulting in an accelerated passive CR . High temperatures and solid deposition are both commonly encountered in the hydrometallurgical industry, and their combination may significantly limit the maximum service temperature of Ti-equipment, implying that there is a risk in using Ti-components under such conditions.

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)0.001
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 score0.085
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueCorrosion Engineering Science and Technology The International Journal of Corrosion Processes and Corrosion ControlSame topicMetal Extraction and BioleachingFrench-language works237,207