The speciation of phosphates adsorbed on γ-alumina revealed by <sup>31</sup>P NMR, AIMD and machine learning
Ab initio molecular dynamics and machine learning are used to unravel the experimental 1D 31 P NMR spectra of phosphates catalytic additives adsorbed on the γ-alumina support.
Authors
- Adrian Hühn
- Mickaël Rivallan (ORCID: https://orcid.org/0000-0003-0556-2443)
- Anne Lesage (ORCID: https://orcid.org/0000-0003-1958-2840)
- Pascal Raybaud (ORCID: https://orcid.org/0000-0003-4506-5062)
- Manuel Corral Valero (ORCID: https://orcid.org/0000-0002-4457-3914)
- Tao Jiang (ORCID: https://orcid.org/0000-0003-0419-7288)
- Carine Michel (ORCID: https://orcid.org/0000-0002-4501-7194)
Institutions
- Université Claude Bernard Lyon 1 (FR)
- École Normale Supérieure de Lyon (FR)
- Centre National de la Recherche Scientifique (FR)
- IFP Énergies nouvelles (FR)
- Laboratoire de Chimie (FR)
Publication Details
- Journal
- Catalysis Science & Technology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d4cy01152j
- Citations
- 2
- Primary Topic
- Chemical Synthesis and Characterization
- Type
- article
- Field-Weighted Citation Impact
- 1.99
Funders
- Agence Nationale de la Recherche
- IFP Energies Nouvelles
- Commissariat Général à l'Investissement
- Grand Équipement National De Calcul Intensif