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Record W4399581741 · doi:10.3390/ma17122867

Advancements in Heavy Metal Stabilization: A Comparative Study on Zinc Immobilization in Glass-Portland Cement Binders

2024· article· en· W4399581741 on OpenAlexaff
Abdelhadi Bouchikhi, Amine el Mahdi Safhi, Walid Maherzi, Yannick Mamindy‐Pajany, Wolfgang Kunther, Mahfoud Benzerzour, N.-E. Abriak

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsPortland cementZincMaterials scienceCementMetalComposite materialMetallurgyWaste managementEngineering

Abstract

fetched live from OpenAlex

Recent literature has exhibited a growing interest in the utilization of ground glass powder (GP) as a supplementary cementitious material (SCM). Yet, the application of SCMs in stabilizing heavy metallic and metalloid elements remains underexplored. This research zeroes in on zinc stabilization using a binder amalgam of GP and ordinary Portland cement (OPC). This study juxtaposes the stability of zinc in a recomposed binder consisting of 30% GP and 70% OPC (denoted as 30GP-M) against a reference binder of 100% CEM I 52.5 N (labeled reference mortar, RM) across curing intervals of 1, 28, and 90 days. Remarkably, the findings indicate a heightened kinetic immobilization of Zn at 90 days in the presence of GP—surging up to 40% in contrast to RM. Advanced microstructural analyses delineate the stabilization locales for Zn, including on the periphery of hydrated C3S particles (Zn–C3S), within GP-reactive sites (Si*–O–Zn), and amid C–S–H gel structures, i.e., (C/Zn)–S–H. A matrix with 30% GP bolsters the hydration process of C3S vis-à-vis the RM matrix. Probing deeper, the microstructural characterization underscores GP’s prowess in Zn immobilization, particularly at the interaction zone with the paste. In the Zn milieu, it was discerning a transmutation—some products born from the GP–Portlandite reaction morph into GP–calcium–zincate.

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 categoriesInsufficient payload (model declined to judge)
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 score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.047
GPT teacher head0.327
Teacher spread0.280 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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