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Record W4220667515 · doi:10.5539/apr.v14n1p15

Low-Energy Electron Elastic Total Cross Sections for the Large Actinide Atoms Cf, Fm and Md

2022· article· en· W4220667515 on OpenAlexvenueno aff
Z. Felfli, A. Z. Msezane

Bibliographic record

VenueApplied Physics Research · 2022
Typearticle
Languageen
FieldChemistry
TopicInorganic Chemistry and Materials
Canadian institutionsnot available
FundersBasic Energy SciencesU.S. Department of Energy
KeywordsExcited stateMetastabilityAtomic physicsIonGround stateElectronAtomic radiusActinidePhysicsNuclear physics

Abstract

fetched live from OpenAlex

The rigorous Regge pole method has been used to investigate negative-ion formation in the large actinide atoms Cf, Fm and Md through the elastic total cross sections (TCSs) calculation in the electron impact energy range 0.0 ≤ E ≤ 10.0eV. Ground, metastable and excited negative-ion formation as well as shape resonances (SRs) and Ramsauer-Townsend (R-T) minima are found to characterize generally the TCSs which also exhibit fullerene molecular behavior near threshold through the TCSs of the highest excited states, while maintaining atomic character through the ground state TCSs. Additionally, a polarization-induced metastable TCS with a pronounced SR appears for the first time very close to threshold in the Cf TCSs, having flipped over from a deep R-T minimum near threshold in the Bk TCSs. This behavior manifests the impact of the size effect and the 6d-orbital collapse as well as demonstrates the sensitivity of the R-T minima and the SRs to the electronic structure of these atoms, thereby permitting their first ever use as novel confirmation of Cf as a transitional element in the actinide series. Rigorous and unambiguous ground, metastable and excited anionic states BEs extracted from the TCSs are compared with the existing electron affinities.

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 categoriesScience and technology studies
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 score0.021
Threshold uncertainty score0.999

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.328
Teacher spread0.304 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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