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Record W2312329054 · doi:10.1021/jp209296b

Probing the Room Temperature Deuterium Absorption Kinetics in Nanoscale Magnesium Based Hydrogen Storage Multilayers Using Neutron Reflectometry, X-ray Diffraction, and Atomic Force Microscopy

2012· article· en· W2312329054 on OpenAlexafffund
W. Peter Kalisvaart, Erik J. Luber, É. Poirier, Christopher Harrower, A. Teichert, Dirk Wallacher, Nico Grimm, Roland Steitz, H. Fritzsche, David Mitlin

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2012
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsNational Research Council CanadaNational Institute for NanotechnologyUniversity of Alberta
FundersNational Research Council CanadaOntario Innovation Trust
KeywordsMaterials scienceHydrogen storageNanocrystalline materialAmorphous solidNucleationAnalytical Chemistry (journal)Neutron diffractionDeuteriumCrystallographyChemistryCrystal structureNanotechnologyMetallurgy

Abstract

fetched live from OpenAlex

Magnesium hydride has high storage capacity (7.6 wt % H) but very slow sorption kinetics. Addition of catalytic phases on the surface as well as alloying with transition metals is known to improve the properties. In this study, the sorption kinetics of a 50-nm Mg layer and Mg-10%Cr-10%V layer, capped with a CrV/Pd bilayer catalyst, are compared using a combination of neutron reflectometry (NR), X-ray diffraction (XRD), and atomic force microscopy to elucidate the effects of alloying on the hydrogen storage properties of Mg at room temperature. From NR it is found that the Cr–V alloyed layer shows both a delay in expansion in the first absorption cycle and a delay in contraction in the first desorption, which indicates a delay in nucleation of MgD 2 and formation of substoichiometric MgD 2-δ, respectively. Compared to pure Mg, the kinetics are strongly improved as no blocking MgD 2 layer is formed. XRD showed a strong reduction in the Mg grain size for the Cr–V alloyed layer after one cycle. For pure Mg, the grain size is almost unchanged although the film becomes nanocrystalline in the hydrided state. NR is shown to be highly sensitive to both the deuterium distribution as well as the layer thickness, which makes it a valuable tool for studying reaction mechanisms and quantification of the expansion of both crystalline and amorphous energy storage materials.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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.

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

Citations19
Published2012
Admission routes2
Has abstractyes

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Same venueThe Journal of Physical Chemistry CSame topicHydrogen Storage and MaterialsFrench-language works237,207