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Record W2590031111 · doi:10.3791/55062

Two-way Valorization of Blast Furnace Slag: Synthesis of Precipitated Calcium Carbonate and Zeolitic Heavy Metal Adsorbent

2017· article· en· W2590031111 on OpenAlexaff
Evangelos Georgakopoulos, Rafael M. Santos, Yi Wai Chiang, Vasilije Manović

Bibliographic record

VenueJournal of Visualized Experiments · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of GuelphSheridan College
Fundersnot available
KeywordsLeaching (pedology)Ground granulated blast-furnace slagChemistryAdsorptionAnalcimeCalcium carbonateNuclear chemistryMaterials scienceChemical engineeringInorganic chemistryZeoliteMetallurgyCementOrganic chemistry

Abstract

fetched live from OpenAlex

The aim of this work is to present a zero-waste process for storing CO2 in a stable and benign mineral form while producing zeolitic minerals with sufficient heavy metal adsorption capacity. To this end, blast furnace slag, a residue from iron-making, is utilized as the starting material. Calcium is selectively extracted from the slag by leaching with acetic acid (2 M CH3COOH) as the extraction agent. The filtered leachate is subsequently physico-chemically purified and then carbonated to form precipitated calcium carbonate (PCC) of high purity (<2 wt% non-calcium impurities, according to ICP-MS analysis). Sodium hydroxide is added to neutralize the regenerated acetate. The morphological properties of the resulting calcitic PCC are tuned for its potential application as a filler in papermaking. In parallel, the residual solids from the extraction stage are subjected to hydrothermal conversion in a caustic solution (2 M NaOH) that leads to the predominant formation of a particular zeolitic mineral phase (detected by XRD), namely analcime (NaAlSi2O6∙H2O). Based on its ability to adsorb Ni2+, as reported from batch adsorption experiments and ICP-OES analysis, this product can potentially be used in wastewater treatment or for environmental remediation applications.

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 score0.036
Threshold uncertainty score0.820

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)0.0010.000

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 head0.036
GPT teacher head0.403
Teacher spread0.367 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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