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Record W2091826259 · doi:10.1021/es301209t

Roles of Sulfuric Acid in Elemental Mercury Removal by Activated Carbon and Sulfur-Impregnated Activated Carbon

2012· article· en· W2091826259 on OpenAlexafffund
Eric A. Morris, Donald W. Kirk, Charles Q. Jia, Kazuki Morita

Bibliographic record

VenueEnvironmental Science & Technology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Tokyo
KeywordsSulfuric acidChemistryActivated carbonSulfurAdsorptionMercury (programming language)KineticsInorganic chemistryOxygenCarbon fibersNuclear chemistryOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

This work addresses the discrepancy in the literature regarding the effects of sulfuric acid (H(2)SO(4)) on elemental Hg uptake by activated carbon (AC). H(2)SO(4) in AC substantially increased Hg uptake by absorption particularly in the presence of oxygen. Hg uptake increased with acid amount and temperature exceeding 500 mg-Hg/g-AC after 3 days at 200 °C with AC treated with 20% H(2)SO(4). In the absence of other strong oxidizers, oxygen was able to oxidize Hg. Upon oxidation, Hg was more readily soluble in the acid, greatly enhancing its uptake by acid-treated AC. Without O(2), S(VI) in H(2)SO(4) was able to oxidize Hg, thus making it soluble in H(2)SO(4). Consequently, the presence of a bulk H(2)SO(4) phase within AC pores resulted in an orders of magnitude increase in Hg uptake capacity. However, the bulk H(2)SO(4) phase lowered the AC pore volume and could block the access to the active surface sites and potentially hinder Hg uptake kinetics. AC treated with SO(2) at 700 °C exhibited a much faster rate of Hg uptake attributed to sulfur functional groups enhancing adsorption kinetics. SO(2)-treated carbon maintained its fast uptake kinetics even after impregnation by 20% H(2)SO(4).

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 categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.145
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
Bibliometrics0.0000.002
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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

Citations66
Published2012
Admission routes2
Has abstractyes

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