MétaCan
Menu
Back to cohort
Record W4293067442 · doi:10.1002/batt.202200182

An Aluminum‐Benzo[1,2‐b:4,5‐b’]dithiophene‐4,8‐dione Organic Rechargeable Battery Featuring Low Self‐Discharge

2022· article· en· W4293067442 on OpenAlexafffund
Yijia Wang, Kok Long Ng, Gisele Azimi

Bibliographic record

VenueBatteries & Supercaps · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsCathodeAnodeBattery (electricity)Intercalation (chemistry)ElectrodePlateau (mathematics)Materials scienceOrganic radical batteryAluminiumEnergy storageVoltageChemical engineeringCell voltageInternal resistanceNanotechnologyChemistryInorganic chemistryElectrochemistryComposite materialPhysical chemistryElectrical engineeringThermodynamics

Abstract

fetched live from OpenAlex

Abstract The achievable cell‐level specific energy density of existing aluminum‐ion batteries (AIBs) employing AlCl4− intercalation type cathodes is intrinsically limited by the chloroaluminate anolyte. Towards achieving AIBs with higher specific energy, it is imperative to explore alternative cell chemistries that fundamentally tap the capacity of Al metal anode. Here, we report a benzo[1,2‐b:4,5‐b’]dithiophene‐4,8‐dione (BDTD) organic electrode material with favorable AlCl2+ intercalation mechanism. This BDTD cathode delivers a specific capacity of 143 mAh g−1, and the resulting battery exhibits a well‐defined voltage plateau at ∼1.2 V. This characteristic voltage plateau is mainly driven by the predominant diffusive charge storage in BDTD cathode, which accounts for up to 85 % of the total charge‐storage contribution. As a result, the BDTD cathode demonstrates exceptional self‐discharging resistance by recovering >95 % of its capacity upon 24‐h resting.

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 score0.003

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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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

Citations5
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueBatteries & SupercapsSame topicAdvancements in Battery MaterialsFrench-language works237,207