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Record W2332109757 · doi:10.1021/co1000597

Combinatorial Synthesis of Mixed Transition Metal Oxides for Lithium-Ion Batteries

2011· article· en· W2332109757 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.

Bibliographic record

VenueACS Combinatorial Science · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChemistryLithium (medication)Transition metalIonLithium metalCombinatorial chemistryInorganic chemistryMetalNanotechnologyOrganic chemistryPhysical chemistryAnodeElectrodeCatalysis

Abstract

fetched live from OpenAlex

Many methods exist for the synthesis of lithium metal oxides for use as positive electrode materials in lithium-ion batteries; however, no such method to date is both combinatorial (able to process broad ranges of compositional space quickly and efficiently) and well-studied to ensure confidence in the procedure. This study develops a procedure for microliter-scale solution-processing synthesis using a combinatorial solutions-processing robot. Two compositional systems (LiNi(x)Mn(2-x)O(4) and Li-Al-Mn oxide) were synthesized to compare the method to existing syntheses to ensure confidence in the procedure. Samples produced by this new synthetic procedure have crystal structures and lattice constants that closely match those of bulk-prepared samples found in the literature.

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)0.001
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 score0.050
Threshold uncertainty score0.852

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 communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.237
Teacher spread0.216 · 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