arXiv subjects

Peter Kraus

Publications and source records attributed to Peter Kraus.

3 recordsLinked to original sources

arXiv2026

In situ and operando laboratory X-ray absorption spectroscopy at high temperature and controlled gas atmosphere with a plug-flow fixed-bed cell

The capabilities of a plug-flow fixed-bed cell for operando studies of heterogeneous catalysts are demonstrated using laboratory-based X-ray absorption spectroscopy (XAS) with a von Hamos spectrometer. The cell operates at temperatures up to 1000 deg C and pressures up to 10 bar, equipped with three mass flow controllers and two infrared lamps for rapid heating under inert/reactive gas atmospheres. Proof-of-principle studies include in situ MnO oxidation in 5% Ni/MnO and operando Ni nanoparticle evolution in 20-NiO/COK-12 (20.2% NiO on SiO2) during CO2 methanation before/after activation. Within 5-15 min per spectrum, oxidation state changes are resolved while catalytic activity is simultaneously quantified by online GC. Extended datasets and methods are available in the ancillary file SI.pdf (Supplementary Information file). A shortened version of this work has been published as a Technical Note in Journal of Analytical Atomic Spectrometry (2026, 41, 1208-1211, DOI: 10.1039/D6JA00027D). This manuscript provides an extended version including additional datasets, analysis, and methodological details beyond the published article.

physics.app-ph↗

arXiv2024

Datatractor: Metadata, automation, and registries for extractor interoperability in the chemical and materials sciences

Two key issues hindering the transition towards FAIR data science are the poor discoverability and inconsistent instructions for the use of data extractor tools, i.e., how we go from raw data files created by instruments, to accessible metadata and scientific insight. If the existing format conversion tools are hard to find, install, and use, their reimplementation will lead to a duplication of effort, and an increase in the associated maintenance burden is inevitable. The Datatractor framework presented in this work addresses these issues. First, by providing a curated registry of such extractor tools their discoverability will increase. Second, by describing them using a standardised but lightweight schema, their installation and use is machine-actionable. Finally, we provide a reference implementation for such data extraction. The Datatractor framework can be used to provide a public-facing data extraction service, or be incorporated into other research data management tools providing added value.

physics.data-an↗

arXiv2021

Materials genes of heterogeneous catalysis from clean experiments and artificial intelligence

Heterogeneous catalysis is an example of a complex materials function, governed by an intricate interplay of several processes, e.g., the different surface chemical reactions, and the dynamic re-structuring of the catalyst material at reaction conditions. Modelling the full catalytic progression via first-principles statistical mechanics is impractical, if not impossible. Instead, we show here how a tailored artificial-intelligence approach can be applied, even to a small number of materials, to model catalysis and determine the key descriptive parameters ("materials genes") reflecting the processes that trigger, facilitate, or hinder catalyst performance. We start from a consistent experimental set of "clean data", containing nine vanadium-based oxidation catalysts. These materials were synthesized, fully characterized, and tested according to standardized protocols. By applying the symbolic-regression SISSO approach, we identify correlations between the few most relevant materials properties and their reactivity. This approach highlights the underlying physicochemical processes, and accelerates catalyst design.

cond-mat.mtrl-sci↗