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Record W3184009290 · doi:10.1002/anie.202106238

Molecular Tailoring of an n/p‐type Phenothiazine Organic Scaffold for Zinc Batteries

2021· article· en· W3184009290 on OpenAlexaff
Nan Wang, Zhaowei Guo, Zhigang Ni, Jie Xu, Xuan Qiu, Jing Ma, Peng Wei, Yonggang Wang

Bibliographic record

VenueAngewandte Chemie International Edition · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsRedoxPhenothiazineZincIodideChemistryElectrochemistryElectrodeAqueous solutionInorganic chemistryMaterials scienceChemical engineeringOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract The p‐type or n‐type redox reactions of organics are being used as the reversible electrodes to build the next‐generation rechargeable batteries with sustainable and tunable characteristics. However, the n‐type organics that store cations generally exhibit low potential (<0.8 V vs. Zn/Zn2+), while the p‐type organics that store anions suffer from limited capacity (<100 mAh g−1). Herein, we demonstrate that bis(phenylamino)phenothiazin‐5‐ium iodide (PTD‐1) containing both n‐type and p‐type redox moieties exhibits a hybrid charge storage mechanism (n/p‐type at low potential, p‐type at high potential). Such a hybrid mechanism combines the advantages of n‐ and p‐type reactions and compensates for the associated drawbacks of each. Accordingly, the aqueous Zn//PTD‐1 full cell shows a high voltage (1.8 Vmaximum or 1.1 Vaverage), a high capacity 188.24 mAh gPTD‐1−1 (achieved at 40 mA g−1), a long‐life and a supercapacitor‐like high power. These results shed new light on the design of advanced organic electrodes.

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 head0.018
GPT teacher head0.274
Teacher spread0.257 · 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

Citations155
Published2021
Admission routes1
Has abstractyes

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