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Record W4240590937 · doi:10.1149/ma2018-01/20/1282

Prediction of Ce(III) Electrodeposition at Various Electrochemical Conditions in Molten LiCl-KCl Eutectic

2018· article· en· W4240590937 on OpenAlexaff
Young Taek Jee, Jong-Il Yun

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicMolten salt chemistry and electrochemical processes
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsEutectic systemMolten saltOverpotentialElectrowinningElectrochemistryElectrolysisAnhydrousUraniumElectrodeElectrolyteMaterials scienceReference electrodeChemistryInorganic chemistryAnalytical Chemistry (journal)MetallurgyChromatographyAlloy

Abstract

fetched live from OpenAlex

Molten salt is one of the widely used liquid media for a selective extraction through electrolysis. In the nuclear industry, pyroprocessing which utilizes LiCl-KCl molten salt in its core unit processes is suggested as a candidate of non-proliferative fuel recycling process. In an electrorefiner, the uranium metal is selectively collected on a solid electrode through the electrochemical reduction of uranium ion dissolved in LiCl-KCl. The deposit shows a dendritic characteristic which dramatically increases an electroactive surface area of the working electrode. As the surface area increases, current density decreases, and the overall electrochemical condition including potential gradient and exchange current along the diffusion layer is, therefore, changed as well in a real time. Despite of its critical influence on the precision of process simulation, there is no model which reflects this transient change of the electrode. In this work, cerium is selected as a surrogate of uranium. Its behaviors of electrodeposition at various conditions (time, current, concentration, and overpotential) are investigated, and a methodology for quantitative prediction of deposit formation on the working electrode is suggested. All sample preparation and experiments were carried out in a glove box filled with high purity argon gas (99.9999 % Ar, [H2O] and [O2] < 1ppm). Oxidation or hydrolysis was completely avoided in advance. 44 wt.% of LiCl and 56 wt.% of KCl (both 99 % purity, anhydrous, Sigma-Aldrich) were mixed for the preparation of LiCl-KCl eutectic. This eutectic and CeCl3 (99.99 % purity, anhydrous, Sigma-Aldrich) were put together into an alumina crucible. This sample was placed in a high temperature furnace which sustained the temperature 773 ± 2 K. Two 1 mm diameter tungsten rods were used as working and counter electrodes, and a silver wire was immersed in 1 wt.% AgCl-LiCl-KCl as the reference electrode. All electrochemical experiments were performed with a potentiostat (Autolab, PGSTAT302N). Prior to the electrodeposition, cyclic voltammetry (CV) was measured to obtain redox peak of cerium and to check the existence of impurity in a system. Then chronoamperometry (CA) was carried out at a fixed potential of -2.05 V (vs. 1 wt.% Ag/AgCl), which is slightly more negative value than that of the reduction peak for successful electrodeposition. As shown in Figure 1, CA plots showed three different characteristics as the concentration of Ce(III) increased. At low concentration (< 0.45 wt.%, black plots), almost constant or gradual increase of current flow was observed. On the other hand, at high concentration (0.48 wt.% >, red plots), the magnitude of current flow increased drastically with illustrating clear linear slope. Therefore, it can be interpreted that, under the same condition of applied potential, the larger the concentration, the greater the current flow due to more electroactive species around the electrode, and thus the larger the growth of the surface area with the larger amount of electrodeposition. At the concentration between 0.45 wt.% and 0.48 wt.% of Ce(III), the CA plot expressed an intermediate behavior which can be shifted from one to the other characteristic at any time depending on the formation of deposit. Even though the CA plots showed different characteristics based on the concentration parameter, they all sketched linear trend. The amount of charge transferred which corresponded to the amount of metal deposit was able to be expressed as a function of time with slope and y-intercept. The slopes of CA plots at high concentration condition were directly proportional to the concentration. The y-intercept, the first plateau of CA plot, could be defined from the current of reduction peak of CV, which is proportional to the concentration. The current signal of reduction peak was affected by immersed depth of working electrode and overpotential. In conclusion, under assumption of no physical detachment or loss of electrodeposit, the preliminary prediction of the amount of electrodeposit was possible with three parameters (time, concentration, and overpotential) which were substantially related to the determination of induced current during CA experiment. This prediction should be achieved in a scrupulous way with consideration of concentration parameter because of different behaviors of electrodeposition. 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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.228
Teacher spread0.218 · 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".

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Citations0
Published2018
Admission routes1
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