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Record W4385241138 · doi:10.3390/cryst13081153

Water Adsorption on MgO Surfaces: A Vibrational Analysis

2023· article· en· W4385241138 on OpenAlexaff
Maria Dekermenjian, Alexandre Merlen, Andréas Ruediger, Michel Rérat

Bibliographic record

VenueCrystals · 2023
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Oxide Properties and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsRaman spectroscopyAdsorptionReactivity (psychology)MoleculeNanoparticleSpectroscopyMaterials scienceAnalytical Chemistry (journal)Spectral lineInfrared spectroscopyChemistryPhysical chemistryInorganic chemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Using DFT calculations, we have considered different adsorption configurations of water molecules on MgO surfaces. In some cases, we have observed a chemical reaction between water and the surface, with the formation of hydroxyl groups. We have systematically compared the calculated Raman spectra of the final optimized structures with the measured spectra from MgO nanoparticles. Our results confirm the high reactivity of MgO surfaces with water. Some obtained structures can be considered precursors for the transformation of MgO into Mg(OH)2. We suggest that some of them could be identified using Raman spectroscopy. Our study confirms the high potentiality of Raman spectroscopy, associated with numerical calculations, for the study of chemical reactivity of nanoparticles.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.255
Teacher spread0.228 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

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