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Record W4252695490 · doi:10.31224/osf.io/8yq7n

ENPOLITE: Comparing Lithium-Ion Cells across Energy, Power, Lifetime, and Temperature

2021· preprint· en· W4252695490 on OpenAlexfundno aff
Philipp Dechent, Alexander Epp, Dominik Jöst, Yuliya Preger, Peter M. Attia, Weihan Li, Dirk Uwe Sauer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsnot available
FundersNational Nuclear Security AdministrationDalhousie UniversityOffice of ElectricityBundesministerium für Wirtschaft und EnergieSandia National LaboratoriesU.S. Department of Energy
KeywordsBattery (electricity)Lithium (medication)Power (physics)IonPlot (graphics)Lithium-ion batteryPower densityEnergy densityEnergy storageEnergy (signal processing)Materials scienceNuclear engineeringReliability engineeringComputer scienceChemistryThermodynamicsStatisticsEngineering physicsEngineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

Lithium-Ion battery lifetimes from cyclic and calendar aging tests of more than 1000 cells were compared employing novel plots termed ENPOLITE (energy-power-lifetime-temperature). Battery cell data from in-house measurements and published data were combined into a uniform database; the total dataset size exceeds 1000 GB. At a glance, ENPOLITE plots inform about the nominal capacity, cell format, cell chemistry, average aging test duration, measurement temperature, specific power employed for testing, energy density, and the achieved lifetime for every cell. A battery lifetime coefficient was derived, allowing the comparison of lithium-ion batteries with different weights or volumes, capacities, and cell chemistries. The combination of multiple parameters in ENPOLITE facilitated a thorough comparison of various batteries' respective lifetimes. In addition to the cell-specific parameters during cycling, the specific stored energy and the storage temperature were depicted in a calendar ENPOLITE-Plot.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.012
GPT teacher head0.271
Teacher spread0.259 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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