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A reduction-oxidation reaction is commonly called a redox reaction. In a redox reaction, electrons are transferred from one species to another rather than being shared between or among atoms. The reducing agent or reductant is the species that loses electrons and gets oxidized in the process. The species that gains electrons and gets reduced in the process is the oxidizing agent or oxidant. Redox reactions are represented as two separate equations called half-reactions, where one equation...
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Besides iodine, other oxidizing or reducing agents can serve as titrants in redox titrations. Common oxidizing titrants include KMnO4, cerium(IV), and K2Cr2O7. The choice of oxidizing titrants depends on factors like stability, cost, analyte strength, and reaction rate between the analyte and titrant. KMnO4 is a strong oxidizing titrant that reduces from Mn(VII) to Mn(II) in a highly acidic solution, simultaneously oxidizing the analyte to a higher oxidation state. In this case, KMnO4 acts as a...
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Identifying Stable Electrocatalysts Initialized by Data Mining: Sb2 WO6 for Oxygen Reduction.

Xue Jia1, Zixun Yu1,2, Fangzhou Liu2

  • 1Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, Sendai, 980-8577, Japan.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|December 7, 2023
PubMed
Summary

Data mining identified Sb2WO6 as a potential electrocatalyst, but experiments revealed surface changes under alkaline conditions. Refined strategies are needed to account for electrochemistry-induced stability and activity.

Keywords:
aqueous stabilitydata miningelectrocatalystselectrochemistry-induced surface stabilitymetal oxidespH-dependent microkinetic modeling

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Area of Science:

  • Materials Science
  • Electrochemistry
  • Computational Chemistry

Background:

  • Data mining of materials databases is a growing strategy for discovering new electrocatalysts.
  • Identifying effective low-cost metal oxide (MO) electrocatalysts presents opportunities and challenges.
  • Discrepancies between computational predictions and experimental results can hinder catalyst discovery.

Purpose of the Study:

  • To analyze the opportunities and challenges of data mining for electrocatalyst identification.
  • To investigate a specific discrepancy between data mining and experimental findings for MO electrocatalysts.
  • To understand the electrochemical behavior and surface evolution of Sb2WO6 under oxygen reduction reaction (ORR) conditions.

Main Methods:

  • Utilized a computational search engine to identify stable metal oxides (MOs) at relevant pH and potentials.
  • Performed experimental characterization and electrochemical testing of candidate electrocatalysts.
  • Employed advanced pH-field coupled microkinetic modeling to analyze surface phenomena.

Main Results:

  • Data mining identified Sb2WO6 as a stable MO electrocatalyst for ORR in acidic media.
  • Experimental results showed Sb2WO6 is unstable in alkaline ORR conditions, contradicting initial predictions.
  • Electrochemical passivation under ORR potentials formed a stable, 4e-ORR active surface on Sb2WO6 in alkaline media.

Conclusions:

  • Data mining is a promising tool for electrocatalyst exploration but requires refinement.
  • Computational strategies must incorporate electrochemistry-induced surface stability and activity.
  • Understanding surface transformations is crucial for accurate electrocatalyst prediction and design.