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Record W2414249371 · doi:10.1021/acs.jctc.6b00222

Surface Adsorption from the Exchange-Hole Dipole Moment Dispersion Model

2016· article· en· W2414249371 on OpenAlexafffund
Matthew S. Christian, Alberto Otero‐de‐la‐Roza, Erin R. Johnson

Bibliographic record

VenueJournal of Chemical Theory and Computation · 2016
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDensity functional theoryChemistryThymineAdsorptionIntermolecular forceDipoleDispersion (optics)NucleobaseComputational chemistryPhysical chemistryMoleculePhysicsOrganic chemistryQuantum mechanics

Abstract

fetched live from OpenAlex

The accurate calculation of intermolecular interaction energies with density functional theory requires methods that include a treatment of long-range, nonlocal dispersion correlation. In this work, we explore the ability of the exchange-hole dipole moment (XDM) dispersion correction to model molecular surface adsorption. Adsorption energies are calculated for six small aromatic molecules (benzene, furan, pyridine, thiophene, thiophenol, and benzenediamine) and the four DNA nucleobases (adenine, thymine, guanine, and cytosine) on the (111) surfaces of the three coinage metals (copper, silver, and gold). For benzene, where the experimental reference data is most precise, the mean absolute error in the computed absorption energies is 0.04 eV. For the other aromatic molecules, the computed binding energies are found to be within 0.09 eV of the available reference data, on average, which is well below the expected experimental uncertainties for temperature-programmed desorption measurements. Unlike other dispersion-corrected functionals, adequate performance does not require changes to the canonical XDM implementation, and the good performance of XDM is explained in terms of the behavior of the exchange hole. Additionally, the base functional employed (B86bPBE) is also optimal for molecular studies, making B86bPBE-XDM an excellent candidate for studying chemistry on material surfaces. Finally, the noncovalent interaction (NCI) plot technique is shown to detect adsorption effects in real space on the order of tenths of an eV.

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 score0.358
Threshold uncertainty score0.117

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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

Citations54
Published2016
Admission routes2
Has abstractyes

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