MétaCan
Menu
← Back to cohort
Record W2365509149 · doi:10.1149/ma2015-01/1/132

Model-Assisted 4-Electrode Cell Design for Li-Based Electrolyte Characterization

2015· article· en· W2365509149 on OpenAlexaff
M. Farkhondeh, Mark Pritzker, Michael Fowler, Charles Delacourt

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsElectrolyteElectrodeOpen-circuit voltagePolarization (electrochemistry)Materials scienceShort circuitEquivalent circuitIonic conductivityBattery (electricity)DiffusionLimiting currentAnalytical Chemistry (journal)VoltageChemical physicsChemistryElectrochemistryElectrical engineeringThermodynamicsPower (physics)Physics

Abstract

fetched live from OpenAlex

With the emergence of high power Li-ion batteries for electric vehicle (EV) and hybrid electric vehicle (HEV) applications, the need to estimate the transport properties of battery electrolytes becomes evident. The poor transport properties (e.g., diffusivity, ionic conductivity) of non-aqueous electrolytes become a limiting factor, especially when high currents are to be drawn from the battery. Various methods to measure the transport properties of electrolytes have been suggested. To date, most methods involve assembling a 2-electrode symmetric cell with the liquid electrolyte confined between two identical metallic electrodes, applying current pulses for a certain period of time and recording the relaxation of the voltage when the circuit is open until it reaches zero.1 However, due to the complicated, not well-understood kinetics of electro-deposition/-stripping reactions at the surface of the metallic electrodes, it is not possible to directly relate the cell voltage evolution during the current pulse (closed circuit) or at the onset of the relaxation step (open circuit) to the variations of electrolyte concentration/potential across the cell. This leads to the loss of useful information that might be gained from these experiments and a larger measurement error. Moreover, the constraint of working under open-circuit conditions restricts the characterization to fewer methods including the restricted-diffusion and semi-infinite-diffusion galvanostatic polarization techniques. In the current work, the possibility of estimating electrolyte transport properties using a 4-electrode symmetric cell is examined. The proposed cell has cylindrical geometry with the working/counter electrodes located at the two ends of the cell and the reference electrodes placed on the inner wall midway between the working/counter electrodes (Fig.1). All electrodes are Li metal foils. Current is applied between the working/counter electrodes and the potential difference between the reference electrodes is recorded. This arrangement enables the response of the cell during both the open-circuit and closed circuit portions of the experiment to be exploited for measurement of the electrolyte transport properties. Since the reference electrodes are not connected to a sink/source of current, the net charge transferred at their interfaces with the electrolyte is zero. However, because of the non-zero width of the reference electrodes lying along the cell, a bipolar effect occurs whereby anodic and cathodic reactions occur simultaneously at different locations along the electrodes depending on the electrolyte potential profile across their width.2 Because of the bipolar effect, the reference electrodes locally perturb the concentration and potential of the electrolyte which in turn affects the measured potential difference. We have developed a model based on concentrated-solution theory3 that includes this bipolar effect in order to quantitatively describe the operation of this cell. In this presentation, we present simulation results for various operating conditions and examine design parameters such as the cell aspect ratio, reference electrode width and spacing for known physico-chemical properties of a binary Li-based electrolyte. Guidelines for assembling such a cell and performing characterization experiments are provided. With further experimental validation of this concept and design, the 4-electrode cell can be extended to include an array of multiple reference electrodes and provide a wealth of knowledge about the potential and species concentration profiles across the cell. Figure 1: Schematic view of a cylindrical symmetric cell with two reference electrodes located between the working and counter electrodes. References 1. A. Nyman, M. Behm and G. Lindbergh, Electrochim. Acta, 53:6356–6365, 2008. 2. G. Loget, D. Zigah, L. Bouffier, N. Sojic and A. Kuhn, Acc. Chem. Res., 46:2513–2523, 2013. 3. J. S. Newman and K. E. Thomas-Alyea. Electrochemical Systems. Wiley Interscience, 2004. Figure 1

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
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 head0.030
GPT teacher head0.216
Teacher spread0.186 · 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 designSimulation or modeling
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting Abstracts→Same topicFuel Cells and Related Materials→French-language works237,207→