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Discovery of efficient Enzyme-like Metal Organic frameworks to activate biomethane at low temperature

Progetto
The main objective in DEMO is to provide high-level hands-on, computational and transferable skill training to 13 Doctoral Candidates (DC) through a Joint Doctorate Program and to create a new generation of experts in hybrid catalysis. DEMO uses light (C1-C4) alkanes as example to study the conversion of a sustainable molecule (biomethane) into a relevant chemical in industry (methanol). This project combines 9 world-class research groups, experts in chemical engineering, organic chemistry, catalysis, modelling and spectroscopy from 7 countries. The 9 partners in academic (3), research centre (3), SME (2) and industrial (1) fields will provide recruited DCs with unique perspectives, preparing DCs for their personal career in research with specific skillsets. DEMO will integrate machine learning, organic chemistry, ab initio modelling, high-throughput and reactor engineering and in situ spectroscopy to discover enzyme-like species in Metal Organic Frameworks (MOFs). Specifically, DEMO will follow an interconnected strategy to discover optimal catalyst candidates: a) virtually generate a dataset with active species in MOFs and screen via Machine Learning; b) test the dataset value of a large sample dataset via experimental high-throughput engineering and modelling; c) understand testing outputs through in situ spectroscopy, titration kinetics and modelling; d) optimise protocols for synthetic materials towards biological analogies and engineer reaction conditions to search solvation phenomena. This way, DEMO expects to have a broad impact on the scientific community, EU industry and society by providing high-quality training in hybrid catalysis.
  • Dati Generali
  • Aree Di Ricerca

Dati Generali

Partecipanti

BORDIGA Silvia   Responsabile scientifico  

Referenti (2)

LO IACONO Cristiano   Amministrativo  
ROCHAS Fabio   Amministrativo  

Dipartimenti coinvolti

CHIMICA   Principale  

Tipo

HEU MSCA Doctoral Networks (DN)

Finanziatore

EUROPEAN COMMISSION
Ente Finanziatore

Partner

Università degli Studi di TORINO

Contributo Totale (assegnato) Ateneo (EURO)

490.075,2€

Periodo di attività

Settembre 1, 2023 - Agosto 31, 2027

Durata progetto

48 mesi

Aree Di Ricerca

Settori (5)


PE5_6 - New materials: oxides, alloys, composite, organic-inorganic hybrid, nanoparticles - (2022)

Settore CHIM/02 - Chimica Fisica

PIANETA TERRA, AMBIENTE, CLIMA, ENERGIA e SOSTENIBILITA' - Chimica e Ambiente

SCIENZE DELLA VITA e FARMACOLOGIA - Farmacologia, Biochimica e Biologia Molecolare

SCIENZE MATEMATICHE, CHIMICHE, FISICHE - Materiali Avanzati

Parole chiave (4)

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Chemical reactions
Machine learning
New materials
heterogeneous catalysis
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