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Record W2634369545 · doi:10.1149/ma2018-02/2/115

Development of Utility Friendly Olivine Based ESS in Esstalion Technologies – Part-2

2018· article· en· W2634369545 on OpenAlexaff
Yuichiro Asakawa, Jean‐Christophe Daigle, Karim Zaghib, Hiroshi Ueno

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsBattery (electricity)AnodeComputer scienceEnergy storageKey (lock)CathodeRenewable energyMaterials scienceProcess engineeringElectrical engineeringNanotechnologyEnvironmental sciencePower (physics)Engineering physicsAutomotive engineeringPhysicsEngineeringThermodynamics

Abstract

fetched live from OpenAlex

One of the promising approaches for striking a balance of realizing sustainable society and maximizing utility’s profit is to apply energy storage system (ESS). There’re many use cases proposed (1) , such as reserve, regulation, peak shaving, time shift, load following, and renewable integration. To answer these demands, the development of a battery with high rate of charging and discharging, a longer cycle life and safe is imperative. Esstalion Technologies Inc. has developed LFP LTO technologies with outstanding long life and excellent low temperature performance. (2) It is well know that material stability of LFP and LTO is key to those properties (3) , however highly reactive surface of LTO causes undesirable reactions such as gas evolution (4) . Those degradation modes hold back the possibilities of full utilization of material stability of LFP and LTO. We investigated mechanisms of failure modes at cathode and anode interfaces. Based the mechanisms, we overcome the issues, and found unique interface structure realizes the properties of our LFP LTO technology. We propose a brief review of our technologies and we will show an example of our efforts to enhance the key properties of the Li-ion battery. References (1) Pacific Northwest National Laboratory, Protocol for Uniformly Measuring and Expressing the Performance of Energy Storage Systems (2) Y. Asakawa et al., ECS Abstract MA2017-02 112 (3) K. Zaghib, M. Dontigny, A. Guerfi, P. Charest, I. Rodrigues, A. Mauger, C.M. Julien, J. Power Sources 196 (8) (2011) 3949e3954. (4) I. Belharouak et al., J. Electrochem. Soc. 2012 volume 159, issue 8, A1165-A1170

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.149
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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 teacher head, 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
Published2018
Admission routes1
Has abstractyes

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