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Record W2326122293 · doi:10.1021/ic402824k

Oxo-Exchange of Gas-Phase Uranyl, Neptunyl, and Plutonyl with Water and Methanol

2014· article· en· W2326122293 on OpenAlexaff
Ana F. Lucena, Samuel O. Odoh, Jing Zhao, Joaquim Marçalo, Georg Schreckenbach, John K. Gibson

Bibliographic record

VenueInorganic Chemistry · 2014
Typearticle
Languageen
FieldChemistry
TopicRadioactive element chemistry and processing
Canadian institutionsUniversity of Manitoba
FundersBasic Energy Sciences
KeywordsChemistryUranylMethanolIon exchangeActinideInorganic chemistryPhase (matter)Density functional theoryKineticsComputational chemistryIonOrganic chemistry

Abstract

fetched live from OpenAlex

A challenge in actinide chemistry is activation of the strong bonds in the actinyl ions, AnO2(+) and AnO2(2+), where An = U, Np, or Pu. Actinyl activation in oxo-exchange with water in solution is well established, but the exchange mechanisms are unknown. Gas-phase actinyl oxo-exchange is a means to probe these processes in detail for simple systems, which are amenable to computational modeling. Gas-phase exchange reactions of UO2(+), NpO2(+), PuO2(+), and UO2(2+) with water and methanol were studied by experiment and density functional theory (DFT); reported for the first time are experimental results for UO2(2+) and for methanol exchange, as well as exchange rate constants. Key findings are faster exchange of UO2(2+) versus UO2(+) and faster exchange with methanol versus water; faster exchange of UO2(+) versus PuO2(+) was quantified. Computed potential energy profiles (PEPs) are in accord with the observed kinetics, validating the utility of DFT to model these exchange processes. The seemingly enigmatic result of faster exchange for uranyl, which has the strongest oxo-bonds, may reflect reduced covalency in uranyl as compared with plutonyl.

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 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 score0.013
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 studies0.0000.000
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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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

Citations23
Published2014
Admission routes1
Has abstractyes

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