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Record W2027059106 · doi:10.1021/jp910895g

SO<sub>2</sub>Adsorption and Transformations on γ-Al<sub>2</sub>O<sub>3</sub>Surfaces: A Density Functional Theory Study

2010· article· en· W2027059106 on OpenAlexaff
John M. H. Lo, Tom Ziegler, Peter D. Clark

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2010
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAdsorptionDensity functional theoryThermogravimetric analysisChemistryInfrared spectroscopyExothermic reactionSulfitePhysical chemistrySpectral lineRange (aeronautics)Analytical Chemistry (journal)Computational chemistryInorganic chemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

The processes of physical and chemical adsorption of SO 2 on clean (100), dehydrated (110), and hydrated (110) surfaces of γ-Al 2 O 3 have been investigated using periodic density functional theory. In total, 18 stable forms of adsorbed SO 2 have been identified on the three types of γ-Al 2 O 3 surfaces. The computed binding energies of SO 2 on these surfaces span the range of 15−70 kcal/mol, which agrees well with the experimental heat of SO 2 adsorption determined using thermogravimetric methods. Among these surfaces, SO 2 shows a preference to adsorb to the dehydrated surface, and the transformation into surface sulfite was observed. Theoretical vibrational frequencies of these species have been computed, and a good agreement was found with the experimental infrared spectra. It was shown that the characteristic 1060 cm −1 band on the IR spectra could be attributed, in addition to the proposed sulfate species SO 4, to the HSO 3 species on the hydrated (110)C surface and the SO 3 species on both dehydrated and hydrated (110)C surfaces. The transformations of adsorbed SO 2 to SO 3 /HSO 3 were found to be highly exothermic with only moderate kinetic barriers on all the three surfaces.

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)
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 score0.012
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 integrity0.0000.001
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 head0.194
Teacher spread0.187 · 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

Citations52
Published2010
Admission routes1
Has abstractyes

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