Aluminium siting in zeolite RTH from a combined machine learning – NMR approach | Synapse
March 3, 2026Open Access
Aluminium siting in zeolite RTH from a combined machine learning – NMR approach
Key Points
Aluminum siting in zeolite frameworks can be effectively analyzed using machine learning methods, revealing intricate structural details.
The integration of Nuclear Magnetic Resonance (NMR) enhances the understanding of aluminum positions within zeolites, significantly improving framework characterization.
NMR analysis includes detailed spectral data that machine learning algorithms can use to predict aluminum distribution accurately.
This approach supports exploration into new materials with tailored properties, paving the way for enhanced applications in various industries.
Abstract
Combining NMR with machine learning opens new opportunities to address the still‑challenging elucidation of aluminum siting in zeolite frameworks.