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Record W2622575628 · doi:10.1021/acs.chemmater.7b00836

Structure Solution of Metal-Oxide Li Battery Cathodes from Simulated Annealing and Lithium NMR Spectroscopy

2017· article· en· W2622575628 on OpenAlexafffund
Kristopher J. Harris, Jamie M. Foster, Matteo Z. Tessaro, Meng Jiang, Xingyi Yang, Yan Wu, Bartosz Protas, Gillian R. Goward

Bibliographic record

VenueChemistry of Materials · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCathodeAnnealing (glass)OxideStoichiometryBattery (electricity)Chemical physicsMetalSpectroscopyNuclear magnetic resonance spectroscopyTransition metalCharge orderingNMR spectra databaseMaterials scienceIonChemistrySpectral linePhysical chemistryCharge (physics)ThermodynamicsPhysicsStereochemistry

Abstract

fetched live from OpenAlex

Discerning the arrangement of transition metal atoms in Li[Ni x Mn y Co z ]O 2 cathode materials has remained an open problem for many years despite the commercial importance of some stoichiometries and the even more promising characteristics of others. We present a method for structural determination in this class of cathode materials. A simple definition of the total energy, based on the chemical principle of electroneutrality, is used in combination with a simulated annealing algorithm to generate model structures. The method reproduces the well-known structure of Li[Li 1/3 Mn 2/3 ]O 2 and produces structures of the disordered Li[Ni x Mn x Co 1–2 x ]O 2 phases (where x = 0.02, 0.1, 0.33) that are verified by detailed 7 Li NMR spectra. For each Li[Ni x Mn x Co 1–2 x ]O 2 phase, the solution is found to be heavily disordered, yet retaining significant ion pairing. Since the underlying notion of favoring charge-neutral regions is generic, we anticipate its utility in a much broader family of 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 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 score0.004

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 studies0.0000.000
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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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

Citations18
Published2017
Admission routes2
Has abstractyes

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