Aluminium siting in zeolite RTH from a combined machine learning – NMR approach
Authors:
- Daniel WillimetzDWDaniel Willimetz
- Joaquin Martínez-OrtigosaJMJoaquin Martínez-Ortigosa
- Deborah Anima Brako-AmoafoDBDeborah Anima Brako-Amoafo
- Lukáš GrajciarLGLukáš Grajciar
- J. Alejandro Vidal-MoyaJVJ. Alejandro Vidal-Moya
- Carlos BornesCBCarlos Bornes
- Fernando ReyFRFernando Rey
- Teresa BlascoTBTeresa Blasco
- Christopher J. HeardCHChristopher J. Heard
Open Access
- 28 January 2026
- journal article
- research article
- Published by Royal Society of Chemistry (RSC) in Journal of Materials Chemistry A
- Vol. 14 (18) , 10882-10890
Abstract
Combining NMR with machine learning opens new opportunities to address the still‑challenging elucidation of aluminum siting in zeolite frameworks.Keywords
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Funding Information
- Generalitat Valenciana (CIPROM/2024/050)
- Ministerstvo Školství, Mládeže a Tělovýchovy (90254)
- Grantová Agentura České Republiky (23-07616S)
- HORIZON EUROPE Framework Programme (101180584)
- Agencia Estatal de Investigación (CEX2021–001230-S)
- European Regional Development Fund (PID2022–136934OB-I00)
- European Commission (TED2021–130191B-C41)
- Horizon 2020 Framework Programme (101008500)
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