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Record W2325110810 · doi:10.2138/am-2000-1015

Magnesium coordination environments in glasses and minerals: New insight from high-field magnesium-25 MAS NMR

2000· article· en· W2325110810 on OpenAlexfundno aff
Scott Kroeker, Jonathan F. Stebbins

Bibliographic record

VenueAmerican Mineralogist · 2000
Typearticle
Languageen
FieldMaterials Science
TopicGlass properties and applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsMagic angle spinningCoordination numberMagnesiumNMR spectra databaseChemistryAmorphous solidCrystallographyNuclear magnetic resonance spectroscopyKnight shiftChemical physicsMineralogyMaterials scienceSpectral lineStereochemistryPhysicsSuperconductivity

Abstract

fetched live from OpenAlex

A comparison of 25 Mg magic angle spinning (MAS) NMR spectra of crystalline and glassy diopside (CaMgSi 2 O 6 ) reveals that the chemical shift in the disordered phase corresponds to that of the mineral, suggesting that sixfold coordination is essentially retained upon vitrification. Likewise, a crystalline leucite analogue (K 2 MgSi 5 O 12 ) known to possess fourfold-coordinated Mg has the same peak position as the corresponding glass. In addition to being a sensitive probe of local structure by analogy with crystalline phases, these data may be understood in terms of the effect of competing cation field strengths: competing network modifier cations with higher field strength induce higher magnesium coordination numbers, with a consequent increase in bond length and decrease in chemical shift. This work demonstrates the utility of NMR at 14.1 Tesla for probing the coordination environment of Mg in glasses and minerals, and suggests great potential for high-field NMR investigations of quadrupolar nuclides with low resonance frequencies in amorphous systems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations117
Published2000
Admission routes1
Has abstractyes

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