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Record W3025411984 · doi:10.1149/ma2020-01462624mtgabs

Carbon Electrocatalysts for High Performance Bromine and Iodine Redox Flow Battery Electrodes

2020· article· en· W3025411984 on OpenAlexaff
A. Keith Jameson, Előd Gyenge, Nicholas P. Stadie, Devin McGlamery

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFlow batteryElectrolyteRedoxBattery (electricity)Energy storageBromineChemistryInorganic chemistryChemical engineeringElectrodeElectrocatalystMaterials scienceNanotechnologyElectrochemistryOrganic chemistryThermodynamicsPower (physics)Physical chemistry

Abstract

fetched live from OpenAlex

Redox flow battery (RFB) electrodes act as bi-functional electrocatalysts, improving the kinetics of the redox reactions of interest without being consumed in the reaction itself. This property of flow batteries allows them to be fully discharged without damaging the electrode, and also allows for the power and energy densities of RFBs to be uncoupled and designed separately. The power density is largely dependent on the activity of the electrocatalyst, whereas the energy density is determined by the solubility of the electroactive species in the external electrolyte tank. Due to the advantages of RFBs, they have been heavily studied and implemented for applications in large-scale energy storage and are often used in tandem with renewable energy sources. Zinc-bromine hybrid flow batteries have arguably become the most promising and common flow battery technology behind that of the all-vanadium RFB, but are held back by low power densities that result from the slower Br2/Br- half-cell kinetics compared to that of the Zn2+/Zn half-cell. Analogous zinc-iodine based flow batteries have recently become the subject of much scientific interest as well, as the electrolyte is less toxic and corrosive to common battery materials compared to bromine, and a high concentration of electroactive species can be achieved due to the formation of the triiodide ion (I3 -) (up to ~12 M). In addition, some scientific research has recently shifted towards flow batteries constructed from heteropolyhalides (such as I2Br-or Br2Cl-) by combining different halogen-based electrolytes. Flow batteries constructed with Br2/Br-and I2/I-half-cells have been able to achieve some of the highest energy densities reported for aqueous flow batteries to date, but improvements still need to be made to the electrode materials. We investigated a variety of different carbon electrocatalysts for fabrication of low-cost and durable electrodes for the I2/I-, Br2/Br-, and heteropolyhalide redox couples in RFB technology. A variety of carbon blacks and phosphorus-doped graphitic carbons (PCx) were drop-casted onto a glassy carbon electrode substrate and their electrocatalytic performance was assessed via a variety of techniques including cyclic voltammetry, rotating disc electrode studies, and electrochemical impedance spectroscopy. Phosphorus-doped graphitic carbon was synthesized via the reaction of phosphorus chloride and benzene in different volumes ratios to obtain samples with variable amounts of phosphorus content (PC, PC3, PC5, PC8), characterized by X-ray diffraction analysis and 31P NMR. The electrocatalytic activity of various carbon blacks had a strong dependence on their surface area and porosity. The electrocatalytic activity of the phosphorus-doped graphitic carbons exhibit a bell curve relationship with the degree of phosphorus-doping, where PC5 and PC3 exhibited higher electrocatalytic behaviour towards the halogen/halide redox reactions than PC and PC8. These observations can be explained by 31PNMR indicating an increased amount of P-O bonds with increasing amounts of doping, with the oxygen containing functional group being catalytic. Excessive doping leads to faults in the lattice structure of the P-doped graphite. The surface area of the electrocatalyst material had the largest impact overall on the electrocatalytic performance of the electrode.

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)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.225
Teacher spread0.212 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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