MétaCan
Menu
Back to cohort
Record W4295836752 · doi:10.1149/1945-7111/ac91a8

The Poor Academic’s DC-Offset for Reversing Polarity in Electrochemical Cells: Application to Redox Flow Cells

2022· article· en· W4295836752 on OpenAlexfundno aff
Kiana Amini, Eric M. Fell, Michael J. Aziz

Bibliographic record

VenueJournal of The Electrochemical Society · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsnot available
FundersDivision of Chemical, Bioengineering, Environmental, and Transport SystemsNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergyPacific Northwest National LaboratoryNational Science Foundation
KeywordsReversingElectrochemistryPolarity (international relations)VoltageBattery (electricity)Offset (computer science)Electrochemical cellElectrodeMaterials scienceFlow batteryRedoxOpen-circuit voltageElectrical engineeringChemistryComputer scienceOptoelectronicsAnalytical Chemistry (journal)EngineeringInorganic chemistryPhysicsCellChromatographyPower (physics)

Abstract

fetched live from OpenAlex

We provide a simple and inexpensive manual DC-offset method for extending the accepted voltage range of a battery cycler to negative voltages, without interfering with the actual operation of the electrochemical cell under the test or exceeding the voltage specs of the battery cycler instrument. We describe the working principles of the method and validate the proposed setup by operating short-term and long-term redox flow battery cycling using compositionally symmetric cell, with open-circuit voltage of zero, and full cell configurations. The method can be used to extend the capability of battery cycler instrumentation to operate any electrochemical cell that requires the polarity to be reversed during operation. Applications include cycling of other symmetric cells (e.g., Li-ion cells), implementation of polarity reversal steps for rejuvenation of electroactive species or rebalancing electrochemical cells, and alternating polarity for electrochemical synthesis.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.008
GPT teacher head0.257
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 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicAdvanced battery technologies researchFrench-language works237,207