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Record W2602680938 · doi:10.1149/ma2016-02/1/139

pH-Controlled Electrolysis of Electrolytic Manganese Dioxide (EMD) for Improved Rechargeable MnO<sub>2</sub>/Zn Batteries

2016· article· en· W2602680938 on OpenAlexaff
Farhang Nesvaderani, Arman Bonakdarpour, David P. Wilkinson

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsManganesePyrolusiteAlkaline batteryElectrolyteInorganic chemistryElectrolysisCathodeChemistryAqueous solutionElectrochemistryLead dioxideAlkaline water electrolysisCrystal structureMaterials scienceChemical engineeringElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Alkaline batteries with the MnO 2 /Zn chemistry offer a number of advantages over other aqueous batteries (e.g., lead acid) including: a) high energy density, b) lower cost, and c) longer shelf life. The main active material used in the cathode electrode of these batteries is manganese dioxide, which has a low production cost, low toxicity, high specific capacity, low self-drain rate, and is abundant in nature. However, alkaline batteries cannot be easily recharged due to the rapid capacity loss and low energy efficiency of the MnO 2 product used. An approach to improving the rechargeability of alkaline batteries may be synthesizing higher quality and/or modified manganese dioxide material. Manganese dioxide is a highly versatile substance that can grow into various crystal structures with different synthesis methods and be used in applications such as lithium-ion batteries, water oxidation electrocatalysts, etc. The preferred manganese dioxide used in alkaline batteries is electrolytic manganese dioxide (EMD) with a crystal structure which is an intergrowth of two different phases, pyrolusite and ramsdellite, which consist of arrays of MnO 6 octahedra in 1 x 1 and 1 x 2 tunnels, respectively. The tunnels in the structure allow for the intercalation/deintercalation of protons during the discharge and charge processes. The EMD structure also contains protons (Ruetschi and Coleman protons) in the form of OH - complexes (also referred to as structural water) which provide a proton bridge, thus increasing the rate of proton diffusion into the lattice structure. The structural water content of EMD is an important parameter for the overall performance and has not been thoroughly reported before. Electrodeposition of EMD relies on the oxidation of Mn 2+ to Mn 4+ on a stable, conductive metal anode (e.g. titanium, nickel, etc.) in an acidic environment (typically H 2 SO 4 ) which determines the water content. The EMD samples were electrodeposited by electrolysis of MnSO 4 onto a titanium anode (4 cm × 14 cm × 2 mm) in an electrolyte solution containing 1.25 M MnSO 4 and H 2 SO 4 ranging from 0.5-5 M of H 2 SO 4 at 95 o C using a current density of 115 A m -2 . Electrosynthesis was performed for a period of 15 hours, thereafter, the deposits were chipped, grounded, washed, and filtered. The samples were then characterized using Thermogravemetric Analysis (TGA), X-Ray Diffraction (XRD), and Brunauer–Emmett–Teller (BET) surface area analysis techniques. Electrochemical properties of the EMD sample were examined with flat-plate cells using a zinc anode and a 9M KOH electrolyte solution and were cycled at a rate of C/10. Electrochemical impedance spectroscopy analysis was performed using a half-cell set-up using a nickel mesh as the counter electrode and an Hg/HgO reference electrode. The EMD samples synthesized with a manganese salt to acid ratio of 1.25:2 show a structural water content and surface area which are nearly twice that of the commercially available EMD products. Additionally, the ramsdellite fraction of the EMD samples increases by about 40%. EMD samples prepared in 2M acid solution exhibit improved cycling performance (see Figure) and energy efficiency when compared to commercial EMD products. The increase in water content is one possible explanation for the enhancement of the protonic conductivity of the in-house EMD as well as its improved physical characteristics. Synthesis and characterization of EMD samples and their electrochemical results will be presented Figure 1

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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)0.001
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 score0.016
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.219
Teacher spread0.211 · 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
Published2016
Admission routes1
Has abstractyes

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