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(In)stability of 10-Methylphenothiazine Cations in Common Electrolytes

2025· article· en· W4406508353 on OpenAlexaff
Maddison Eisnor, Antoine Juneau, Jonathan R. Adsetts, Danny Chhin, Steen B. Schougaard, Janine Mauzeroll

Bibliographic record

VenueACS electrochemistry. · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsUniversité du Québec à MontréalMcGill University
Fundersnot available
KeywordsElectrolyteStability (learning theory)ChemistryComputer sciencePhysical chemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide 10-Methylphenothiazine (MPT) is used in energy devices, often to prevent overcharging. Surprisingly, there is a lack of fundamental knowledge on the stability of MPT dication, which is transiently produced during operation. Herein, we used spectroelectrochemistry and cyclic voltammetry to investigate the effect of different Li-based electrolytes (LiPF 6, LiClO 4, LiSbF 6 ) and temperatures on the chemical reactivity of the MPT dication (MPT 2+ ). This work shows that while the radical cation is extremely stable, MPT 2+ is a superacid that can react with most common battery electrolytes, specifically LiClO 4 . Experiments conducted with 2,4,6-trimethylpyridine (TMP) and density functional theory (DFT) calculations suggest that a possible degradation pathway involves the deprotonation of MPT 2+ to form a reactive singly charged iminium ion (ImPT + ), with the electrolyte acting as a proton acceptor. This work offers insights into the reactivity of MPT 2+ under battery-relevant conditions, providing an opportunity for the rational design of phenothiazine-based devices with improved stability.

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 score0.017
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.248
Teacher spread0.241 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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