MétaCan
Menu
Back to cohort
Record W1641555178 · doi:10.1063/1.1603217

Why is Al11B2− not a magic number in TOF-MS?

2003· article· en· W1641555178 on OpenAlexafffund
Jian Wan, René Fournier

Bibliographic record

VenueThe Journal of Chemical Physics · 2003
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMagic number (chemistry)Cluster (spacecraft)Icosahedral symmetryBimetallic stripChemistryMAGIC (telescope)CrystallographySpectral lineMass spectrumAtomic physicsDensity functional theoryIonComputational chemistryPhysicsElectronic structureMetal

Abstract

fetched live from OpenAlex

Bimetallic anionic and neutral clusters, consisting of group III elements (Aln−1B1, Aln−2B2, Aln−1In1, and Inn−1Al1, n=11–14), have been theoretically investigated by density functional theory at the B3LYP/6-31G* (LanL2DZ for the In element) level. The calculated optimized equilibrium geometries and total energies of neutral and anionic clusters give a satisfactory interpretation of magic number clusters observed in time of flight mass spectra (TOF-MS). Our results show that Al11B2− is the most stable among Aln−2B2− (n=11–14) cluster anions and keeps an icosahedronlike structure, contrary to what had been suggested previously. Whether a magic number turns out in TOF-MS likely depends more on the stability of the neutral clusters than on the stability of the anions. The Al11B2 neutral cluster is less stable than Al12B2, and this is why Al11B2− does not appear as a magic number in TOF-MS. In addition, we found that icosahedral structures do not always hold for the magic cluster anions considered in the present study.

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 categoriesInsufficient payload (model declined to judge)
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 score0.008
Threshold uncertainty score0.999

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.288
Teacher spread0.265 · 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

Citations12
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Chemical PhysicsSame topicBoron and Carbon Nanomaterials ResearchFrench-language works237,207