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Record W4403190196 · doi:10.3390/su16198630

Recovery of Magnetic Ni Particles from Spent Catalyst Leachate by Direct Cementation

2024· article· en· W4403190196 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

VenueSustainability · 2024
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsLeachateCementation (geology)Environmental scienceCatalysisWaste managementMagnetic separationMetallurgyMaterials scienceChemistryEngineeringCement

Abstract

fetched live from OpenAlex

An alternative method based on cementation for the recovery of nickel from spent Ni/Al2O3 reforming catalyst pregnant leach solution (PLS) was proposed to overcome the limitations of traditional two-step extraction and precipitation processes. Thermodynamic analysis was used to evaluate the potential interference of key reactions, such as nickel and sacrificial metal leaching, with the selective cementation of nickel from the PLS. Key variables in the cementation process were optimized using response surface methodology (RSM) combined with Box–Behnken design (BBD). Under optimal conditions—pH 2.2 ± 0.1, processing time of 15 min, and Al/Ni molar ratio of 2.65—a maximum nickel recovery of 73.2% was achieved. Extensive characterization confirmed the high quality of the cemented nickel product: (i) ICP-OES indicated nickel purity of 99.47%, (ii) XRD patterns verified the presence of pure face-centered cubic nickel, (iii) SEM-EDS and vibrating sample magnetometry confirmed the high purity of the metallic nickel particles.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.432

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 head0.008
GPT teacher head0.253
Teacher spread0.245 · 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