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Record W1997863523 · doi:10.1021/jp003803h

Sulfite Stabilization and Reduction of the Aqueous Mercuric Ion:  Kinetic Determination of Sequential Formation Constants

2001· article· en· W1997863523 on OpenAlexaff
Lisa L. Van Loon, Elizabeth A. Mader, Susannah L. Scott

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSulfiteChemistryAqueous solutionDissociation (chemistry)RedoxReaction rate constantInorganic chemistryIonKineticsMercury (programming language)SulfurPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The aqueous sulfite ion reacts with Hg 2+ (aq) to form 1:1 and 2:1 coordination complexes. The Hg(SO 3 ) 2 2- complex is redox stable. However, dissociation of a sulfite ligand forms redox-unstable HgSO 3 . Under conditions where Hg(SO 3 ) 2 2- predominates, the rate of reduction of the mercuric ion to Hg 0 by coordinated sulfite depends inversely on the concentration of uncoordinated sulfite, while it is unaffected by the amount of sulfite liberated by dissociation. Analysis of the kinetics yields the sequential sulfite binding constants K 1 = 2.1 × 10 13 and K 2 = 1.0 × 10 10 at μ = 0.10 M. These values lead to the prediction that HgSO 3 is more abundant in clouds than is Hg(SO 3 ) 2 2- under virtually all atmospheric conditions. The product of the redox reaction appears to be a strongly bound Hg 0 ·SO 2 complex, which is at least 3 orders of magnitude more soluble than uncomplexed Hg 0 (aq) . This finding may have important implications for the partitioning of atmospheric mercury from the gas phase into atmospheric water droplets prior to its wet deposition.

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 score0.005
Threshold uncertainty score0.122

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)0.0000.000

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 head0.014
GPT teacher head0.253
Teacher spread0.239 · 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

Citations79
Published2001
Admission routes1
Has abstractyes

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