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  1. Progetti

EXplainable MACHINe learning: A closed-loop feedback approach for metal hydrides design and discovery

Progetto
Fencing climate change means looking for alternatives to fossil fuels and enhancing renewables energies (RE). In this direction, renewable H2 can be produced by electrolysis of H2O using RE. As an efficient energy vector, it can be stably stored in the solid state in metal hydrides (MH) reaching high volumetric densities. However, the development and characterization of new materials is time consuming and costly. EX-MACHINA aims to implement a rapid and robust tool for new material design through explainable machine learning (ML), focusing on the validation of a protocol and the modelling of thermodynamic (TD) properties of MH at low and high pressure for stationary H2 storage applications. The project will look at new low-cost alloys with outstanding storage performance and hydrogenation properties. The innovative closed-loop feedback approach will allow gaining fundamental knowledge from advanced statistical, characterization and theoretical methods starting from a large data mining to predict materials and models that satisfy key scientific and technological criteria. The novel combination of ML, Calphad and advanced experiments in a closed loop feedback aims to: (1) Develop a sole, enlarged database on MH by integrating available databases, performing CALPHAD calculations of their thermodynamic properties at low and high pressure (2) Unravel interdependencies on structure-property relationships by identifying feature combinations that are the primary contributors to the ML (3) Use advanced synthesis and characterization methods to produce and integrate new experimental data in the ML analysis, advancing modelling and estimation power (4) Boost Experienced Researcher (ER) carrier, with a 2-way transfer of knowledge and by expanding USA-EU collaborative research in the field (5) Maximize exploitation of research outputs by wide dissemination, communication, and open science.
  • Dati Generali
  • Aree Di Ricerca

Dati Generali

Partecipanti

DEMATTEIS Erika Michela   Responsabile scientifico  

Referenti

CALABRETTA Maria   Amministrativo  

Dipartimenti coinvolti

CHIMICA   Principale  

Tipo

Progetti PNRR M4C2 Iniziativa 1.2 - Finanziamento di progetti presentati da giovani ricercatori - Seal of Excellence

Finanziatore

Ministero dell'Università e della Ricerca
Ente Finanziatore

Partner

Università degli Studi di TORINO

Contributo Totale (assegnato) Ateneo (EURO)

150.000€

Periodo di attività

Dicembre 20, 2022 - Dicembre 19, 2025

Durata progetto

36 mesi

Aree Di Ricerca

Settori (11)


PE10_3 - Climatology and climate change - (2022)

PE10_9 - Biogeochemistry, biogeochemical cycles, environmental chemistry - (2022)

PE5_1 - Structural properties of materials - (2022)

Settore ING-IND/22 - Scienza e Tecnologia dei Materiali

CIBO, AGRICOLTURA e ALLEVAMENTI - Allevamento e Produzioni Animali

CIBO, AGRICOLTURA e ALLEVAMENTI - Farmacologia Veterinaria

PIANETA TERRA, AMBIENTE, CLIMA, ENERGIA e SOSTENIBILITA' - Cambiamenti Climatici

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

PIANETA TERRA, AMBIENTE, CLIMA, ENERGIA e SOSTENIBILITA' - Protezione e prevenzione del territorio dai rischi naturali, ambientali e antropici

SCIENZE MATEMATICHE, CHIMICHE, FISICHE - Chimica Organica e Industriale

SCIENZE MATEMATICHE, CHIMICHE, FISICHE - Materiali Avanzati

Parole chiave

EX-MACHINA
No Results Found
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