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Record W4394857669 · doi:10.1149/1945-7111/ad3f54

Lithium-Gold Electrochemical Alloying: Clarifying Reaction Pathways and Products Using Operando XRD

2024· article· en· W4394857669 on OpenAlexafffund
Seyedsina Hejazi, Ruilin Liang, Ania S. Sergeenko, Michael D. Fleischauer

Bibliographic record

VenueJournal of The Electrochemical Society · 2024
Typearticle
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsNational Research Council CanadaNational Institute for Nanotechnology
FundersNational Research Council Canada
KeywordsElectrochemistryLithium (medication)Materials scienceChemical engineeringChemistryElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

Gold electrodes are used in lithium-ion battery research despite their high cost and unclear reactivity with lithium. Many equilibrium phases of gold-lithium (Au-Li) exist—solid solutions alpha, beta, and delta, and intermetallic phases AuLi 3 and Au 4 Li 15 . During the first alloying reaction, the equilibrium alpha and beta phases are seemingly bypassed; a phase, presumably delta, forms at a potential of 0.25 V (all potentials vs Li/Li + ), followed by the formation of AuLi 3 at 0.15 V at all conditions tested and Au 4 Li 15 at 0.05 V in select conditions. Alloying reactions are reversible to (delta), followed by the formation of another phase near 0.3 V and a low Li content phase at potentials above 0.4 V during de-alloying. Observed diffraction peaks only partially align with previous reports for all phases other than Au 4 Li 15 . The second alloying/de-alloying cycle is reversible between a low Li content phase (not pure gold) and the terminal phase. Some reaction hysteresis is present at low Li content. While the (delta)/AuLi 3 reaction had a consistent potential during alloying and de-alloying, the potential otherwise varied strongly with temperature, rate, and composition, implying that gold quasi-reference electrodes may not be suitable for lithium-ion battery research.

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 score0.021
Threshold uncertainty score0.745

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 integrity0.0000.002
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 head0.019
GPT teacher head0.273
Teacher spread0.254 · 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

Citations7
Published2024
Admission routes2
Has abstractyes

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