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Record W4406309793 · doi:10.1021/jacs.4c12391

Cathode Design Based on Nitrogen Redox and Linear Coordination of Cu Center for All-Solid-State Fluoride-Ion Batteries

2025· article· en· W4406309793 on OpenAlexaff
Datong Zhang, Kentaro Yamamoto, Zulai Cao, Yanchang Wang, Hisao Kiuchi, Toshiki Watanabe, Toshiyuki Matsunaga, Koji Nakanishi, Hidenori Miki, Hideki Iba, Yoshihisa Harada, Koji Amezawa, Kazuhiko Maeda, Hiroshi Kageyama, Yoshiharu Uchimoto

Bibliographic record

VenueJournal of the American Chemical Society · 2025
Typearticle
Languageen
FieldChemistry
TopicInorganic Fluorides and Related Compounds
Canadian institutionsCarbon Engineering (Canada)
FundersJapan Society for the Promotion of ScienceKyoto UniversityJapan Science and Technology AgencyChina Scholarship CouncilMinistry of Education, Culture, Sports, Science and Technology
KeywordsChemistryRedoxFluorideCathodeIonSolid-stateInorganic chemistryCenter (category theory)NitrogenPhysical chemistryOrganic chemistryCrystallography

Abstract

fetched live from OpenAlex

All-solid-state fluoride-ion batteries (FIBs) have attracted extensive attention as candidates for next-generation energy storage devices; however, promising cathodes with high energy density are still lacking. In this study, Cu 3 N is investigated as a cathode material for all-solid-state fluoride-ion batteries, which offers enough anionic vacancies around the 2-fold coordinated Cu center for F – intercalation, thereby enabling a multielectron-transferred fluorination process. The contribution of both cationic and anionic redox to charge compensation, in particular, the generation of molecular nitrogen species in highly charged states, has been proved by several synchrotron-radiation-based spectroscopic technologies. As a result, Cu 3 N exhibits a high reversible capacity of ∼550 mAh g –1, exceeding many conventional fluoride-ion cathodes. It is believed that the new charge compensation chemistry as well as the unique intercalation behaviors of novel mixed-anion Cu–N/F local structures could bring new insights into 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)0.000
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 score0.012
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.260
Teacher spread0.250 · 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

Citations16
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicInorganic Fluorides and Related CompoundsFrench-language works237,207