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Record W2001085035 · doi:10.1021/es800232r

New Evidence for Rejuvenation of Phosphorus Retention Capacity in EAF Steel Slag

2008· article· en· W2001085035 on OpenAlexaboutno aff
Aleksandra Drizo, John P. Cummings, David J. Weber, Eamon Twohig, Greg Druschel, Bill Bourke

Bibliographic record

VenueEnvironmental Science & Technology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsnot available
Fundersnot available
KeywordsSlag (welding)MetallurgyElectric arc furnaceRejuvenationSaturation (graph theory)Materials scienceGround granulated blast-furnace slagPhosphorusSteelmaking

Abstract

fetched live from OpenAlex

The purpose of this research was to investigate phosphorus (P) retention capacity and rejuvenation potential of electric arc furnace (EAF) steel slag from Quebec and New Zealand (NZ) iron melter slag (IMS). Columns filled with slag materials were fed with dairy effluent and subjected to two feeding and one resting cycle(s). P retention capacities and rejuvenation potentials were determined after each feeding cycle. Elemental composition and mineralogical analysis were performed on IMS samples. Finally, chemical fractionation analysis was conducted on both NZ IMS and Quebec EAF steel slags. The results revealed that initiating a resting period in EAF steel slag filters prior to reaching their P saturation point increased the overall filter P retention capacity by 49.5 and 42.4% compared to 28% in a filter which had its resting period initiated after reaching P saturation. The rejuvenation property could play a significant role in full-scale applications by prolonging life expectancy and increasing cost efficiency. P retention and rejuvenation by NZ slag materials was negligible relative to EAF steel slag material from Quebec. Chemical fractionation analysis revealed differences between materials, indicating that the highest quantities of P were bound to Ca and Fe in EAF steel slag and to Ca and Al fractions in iron melter slag. This study also demonstrates that slag's performance is dependent on the source of the material and the steel making practices. Therefore, testing of the P adsorptive capability and, if relevant, the rejuvenation potential of individual steel mill slags, should be a prerequisite prior to their use in field 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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.041
GPT teacher head0.239
Teacher spread0.199 · 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 designObservational
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

Citations44
Published2008
Admission routes1
Has abstractyes

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