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Record W2997626934 · doi:10.1021/acsomega.9b03207

Theoretical Investigation of 6-Mercaptopurine Isomers’ Adsorption on the Au(001) Surface: Revealing the Fate of Different Isomers

2019· article· en· W2997626934 on OpenAlexaff
Hongjiang Ren, Xinwei Cao, Yahuang Zhang, Morteza Chehelamirani, Dennis R. Salahub

Bibliographic record

VenueACS Omega · 2019
Typearticle
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsAdsorptionChemistryDensity functional theoryDenticityAtom (system on chip)CrystallographyBinding energyComputational chemistryPhysical chemistryCrystal structureAtomic physics

Abstract

fetched live from OpenAlex

Density functional theory (DFT) calculations were performed for the adsorption of different isomers of 6-mercaptopurine on the Au(001) surface. All of the configurations of four thione and two thiol isomers were considered. The results show that the thione isomers adsorbed more strongly on the Au(001) surface compared with the thiol ones. In all of the configurations, the calculated binding energy of ma-8 is the largest, in which the S atom of 6-mercaptopurine binds strongly with one Au atom on the monodentate sites and 6-mercaptopurine retains a flat geometry, predominantly with an approximately 30° orientation between the C–S bond and the Au–Au bond of the catalyst. Additionally, the 6-mercaptopurines in ma-2, mb-5, and mc-3 also bind more strongly onto the surface, which show relatively higher stability on the surfaces, indicating a high preference for adsorption. Charge density differences and TDOS analyses for the four configurations also show that the electronic charges are accumulated between Au and S atoms in the Au–S bonds, indicating occurrence of adsorption and chemical-bond formation.

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 score0.042
Threshold uncertainty score0.524

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 head0.229
Teacher spread0.216 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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