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Record W2614705128 · doi:10.1002/aenm.201700275

A Metal‐Free and Biotically Degradable Battery for Portable Single‐Use Applications

2017· article· en· W2614705128 on OpenAlexafffund
Juan Pablo Esquivel, Perla Alday, Omar Ibrahim, Belén Fernández, Erik Kjeang, N. Sabaté

Bibliographic record

VenueAdvanced Energy Materials · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsSimon Fraser University
FundersH2020 Marie Skłodowska-Curie ActionsEuropean Research CouncilBritish Columbia Knowledge Development FundBill and Melinda Gates FoundationNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationElectrochemical Society
KeywordsBattery (electricity)Materials scienceLithium metalAnodeVoltageCurrent collectorOrganic radical batteryRedoxElectricityComputer scienceNanotechnologyElectrical engineeringElectrodePower (physics)EngineeringChemistry

Abstract

fetched live from OpenAlex

This article presents a new approach for environmentally benign, low‐cost batteries intended for single‐use applications. The proposed battery is designed and fabricated using exclusively organic materials such as cellulose, carbon, and wax and features an integrated quinone‐based redox chemistry to generate electricity within a compact form factor. This primary capillary flow battery is activated by the addition of a liquid sample and has shown continuous operation up to 100 min with an output voltage that can be conveniently scaled to match the voltage needs of portable electronic devices (1.5–3.0 V). Once depleted, the battery can be disposed of without the need for any recycling facility, as its components are nontoxic and shown to be biotically degradable in a standardized test. The practical utility of the battery is demonstrated by direct substitution of a lithium ion coin cell in a diagnostic application.

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 score0.002
Threshold uncertainty score0.005

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.026
GPT teacher head0.261
Teacher spread0.235 · 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

Citations89
Published2017
Admission routes2
Has abstractyes

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