Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

AKE: Arbeitskreis Energie

AKE 1: Innovative Energy Transformation Concepts

AKE 1.6: Vortrag

Montag, 18. März 2024, 16:45–17:00, TC 006

AI-Driven In-situ Experimental Spectroscopy Analysis in Energy Chemistry — •Haobo Li — The University of Adelaide

Single-atom catalysts (SACs) offer significant potential across various applications, yet our understanding of their formation mechanism remains limited. Notably, the pyrolysis of zeolitic imidazolate frameworks (ZIFs) stands as a pivotal avenue for SAC synthesis, of which the mechanism can be assessed through infrared (IR) spectroscopy. However, the prevailing analysis techniques still rely on manual interpretation. Here, we report a artificial intelligence (AI)-driven analysis of the IR spectroscopy to unravel the pyrolysis process of Pt-doped ZIF-67 to synthesize Pt-Co3O4 SAC. Demonstrating a total Pearson correlation exceeding 0.7 with experimental data, the algorithm provides correlation coefficients for the selected structures, thereby confirming crucial structural changes with time and temperature, including the decomposition of ZIF and formation of Pt-O bonds. These findings reveal and confirm the formation mechanism of SACs. As demonstrated, the integration of AI algorithms, theoretical simulations, and experimental spectral analysis introduces an approach to deciphering experimental characterization data, implying its potential for broader adoption.

Keywords: Infrared spectroscopy analysis; Single-atom catalyst fromation; ZIF pyrolysis mechanism; LASSO regression; DFT calculated database