Abstract

Heterogeneous catalyst surfaces are dynamic entities that respond rapidly to changes in their local gas environment, and the dynamics of the response is a decisive factor for the catalysts’ action and activity. Few probes are able to map catalyst structure and local gas environment simultaneously under reaction conditions at the timescales of the dynamic changes. Here we use the CO oxidation reaction and a Pd(100) model catalyst to demonstrate how such studies can be performed by time-resolved ambient pressure photoelectron spectroscopy. Central elements of the method are cyclic gas pulsing and software-based event-averaging by image recognition of spectral features. A key finding is that at 3.2 mbar total pressure a metallic, predominantly CO-covered metallic surface turns highly active for a few seconds once the O2:CO ratio becomes high enough to lift the CO poisoning effect before mass transport limitations triggers formation of a √5 oxide.

Highlights

  • All datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request, since private communication is necessary for the raw data analys

  • The time resolution for the image-recognition method presented here will practically be limited by the dwell time required to measure a spectral feature sufficiently intense to be used as a triggering signal in the raw data

  • The regime where one approach or leaves the mass transfer limit can be studied with high time resolution

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Summary

Introduction

All datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request, since private communication is necessary for the raw data analys. In the work presented here, we reached time resolutions between 150 and 50 ms, limited by the software and framerate of the camera for the detector. The time resolution for the image-recognition method presented here will practically be limited by the dwell time required to measure a spectral feature sufficiently intense to be used as a triggering signal in the raw data.

Results
Conclusion

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