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Record W2949688214 · doi:10.1021/ic502932x

Topotactic Solid-State Metal Hydride Reductions of Sr<sub>2</sub>MnO<sub>4</sub>

2015· article· en· W2949688214 on OpenAlexafffund
Bradley C. Hernden, Joey A. Lussier, Mario Bieringer

Bibliographic record

VenueInorganic Chemistry · 2015
Typearticle
Languageen
FieldChemistry
TopicInorganic Chemistry and Materials
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryHydrideSolid-stateMetalInorganic chemistryCrystallographyPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We report novel details regarding the reactivity and mechanism of the solid-state topotactic reduction of Sr2MnO4 using a series of solid-state metal hydrides. Comprehensive details describing the active reducing species are reported and comments on the reductive mechanism are provided, where it is shown that more than one electron is being donated by H(-). Commonly used solid-state hydrides LiH, NaH, and CaH2, were characterized in terms of reducing power. In addition the unexplored solid-state hydrides MgH2, SrH2, and BaH2 are evaluated as potential solid-state reductants and characterized in terms of their reductive reactivities. These 6 group I and II metal hydrides show the following trend in terms of reactivity: MgH2 < SrH2 < LiH ≈ CaH2 ≈ BaH2 < NaH. The order of the reductants are discussed in terms of metal electronegativity and bond strengths. NaH and the novel use of SrH2 allowed for targeted synthesis of reduced Sr2MnO(4-x) (0 ≤ x ≤ 0.37) phases. The enhanced control during synthesis demonstrated by this soft chemistry approach has allowed for a more comprehensive and systematic evaluation of Sr2MnO(4-x) phases than previously reported phases prepared by high temperature methods. Sr2MnO3.63(1) has for the first time been shown to be monoclinic by powder X-ray diffraction and the oxidative monoclinic to tetragonal transition occurs at 450 °C.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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

Citations16
Published2015
Admission routes2
Has abstractyes

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