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Record W3191515642 · doi:10.1017/s1551929521000869

An Application of Electron Energy Loss Spectroscopy to a Cycled Nickel Positive Electrode of a Nickel Metal Hydride Battery

2021· article· en· W3191515642 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMicroscopy Today · 2021
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsNational Research Council CanadaNatural Resources Canada
FundersNational Research Council Canada
KeywordsNickelHydrideBattery (electricity)MetalElectronMaterials scienceElectron energy loss spectroscopyElectrodeSpectroscopyInorganic chemistryChemistryMetallurgyPhysical chemistryNanotechnologyPhysicsThermodynamicsPower (physics)

Abstract

fetched live from OpenAlex

Transmission electron microscopy (TEM) offers significant potential for studying chemical changes that occur in a battery electrode at a spatial resolution approaching atomic dimensions, provided a representative specimen can be prepared. The purpose of this paper is to show that it is possible to examine an electrode in the charged condition using TEM, while avoiding major changes in chemistry from specimen preparation. We also demonstrate the power of electron energy-loss spectroscopy (EELS) for phase identification at high spatial resolution. The origin of “fading” of an electrode after repeated charge-discharge cycling is also discussed.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.004
GPT teacher head0.268
Teacher spread0.263 · 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