6533b831fe1ef96bd1298ccd

RESEARCH PRODUCT

A Generalized Method for High‐Speed Fluorination of Metal Oxides by Spark Plasma Sintering Yields Ta 3 O 7 F and TaO 2 F with High Photocatalytic Activity for Oxygen Evolution from Water

Martin PanthöferMuhammad Nawaz TahirMartin Alexander LangeMarcus Von Der AuMuhammad AshrafMihail MondeshkiBjörn MeermannPhil OpitzAhsanulhaq QurashiJens PfeiferLeon PrädelFabian SimonJens HartmannAntje CossmerWolfgang TremelIbrahim Khan

subject

Materials scienceMechanical EngineeringOxygen evolutionTantalumSpark plasma sinteringNanoparticlechemistry.chemical_elementSintering02 engineering and technology010402 general chemistry021001 nanoscience & nanotechnology01 natural sciences0104 chemical sciencesCatalysischemistry.chemical_compoundchemistryChemical engineeringMechanics of MaterialsPhotocatalysisGeneral Materials ScienceTetrafluoroethylene0210 nano-technology

description

A general method to carry out the fluorination of metal oxides with poly(tetrafluoroethylene) (PTFE, Teflon) waste by spark plasma sintering (SPS) on a minute scale with Teflon is reported. The potential of this new approach is highlighted by the following results. i) The tantalum oxyfluorides Ta3 O7 F and TaO2 F are obtained from plastic scrap without using toxic or caustic chemicals for fluorination. ii) Short reaction times (minutes rather than days) reduce the process time the energy costs by almost three orders of magnitude. iii) The oxyfluorides Ta3 O7 F and TaO2 F are produced in gram amounts of nanoparticles. Their synthesis can be upscaled to the kg range with industrial sintering equipment. iv) SPS processing changes the catalytic properties: while conventionally prepared Ta3 O7 F and TaO2 F show little catalytic activity, SPS-prepared Ta3 O7 F and TaO2 F exhibit high activity for photocatalytic oxygen evolution, reaching photoconversion efficiencies up to 24.7% and applied bias to photoconversion values of 0.86%. This study shows that the materials properties are dictated by the processing which poses new challenges to understand and predict the underlying factors.

https://doi.org/10.1002/adma.202007434