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Record W3033878940 · doi:10.1021/acs.iecr.0c01600

Enhanced Hydromagnesite Process for CO<sub>2</sub> Sequestration by Desilication of Serpentine Ore in NaOH Solution

2020· article· en· W3033878940 on OpenAlexaff
Xiaojuan Zhang, Yan Zeng, Zhibao Li

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsMcGill University
FundersNational Natural Science Foundation of China
KeywordsLeaching (pedology)Ammonium carbonateMagnesiumCarbonateChemistryChemical engineeringMineralogyMaterials scienceInorganic chemistryMetallurgyGeology

Abstract

fetched live from OpenAlex

A new CO2 fixation process was highly enhanced by desilication of serpentine ore with concentrated NaOH solution and NH3 recycling. In the process, desilicated serpentine containing up to 83 wt % MgO after leaching is treated by NH4Cl solution, from which MgCl2 solution and NH3 gas are generated and are used to capture CO2. Hydromagnesite is produced from the reaction between ammonium carbonate and MgCl2 solution at ambient temperature. The Phase-transition diagram of magnesium carbonate was constructed with the OLI-based chemical model. The leaching behavior of serpentine in concentrated NaOH was systematically studied. Parameters including the initial NaOH concentration, leaching temperature, solid-to-liquid ratio, and reaction time were investigated to achieve efficient separation of Si and Mg. The validity of the proposed process is successfully verified step by step and the target product of hydromagnesite is obtained. The synthetic hydromagnesite exhibit the same structure and similar morphology as natural hydromagnesite. Moreover, valuable 2% Ni-bearing minerals were also produced.

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)0.001
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 score0.024
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.078
GPT teacher head0.341
Teacher spread0.264 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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