Knowledge center – MAST3RBoost

Deliverables

WP1 Development of data collection and storage infrastructure for application of machine-learning tools.

D1.1 Implementation of raw-data parsers and common data processing into LABCORE notebook

D1.2 Database kick-started and fed with pre-existing data

D1.3 Data management plan for the project

D1.4 Harmonized methodology on data gathering to build unified database for in-depth ML

D1.5 Descriptor performance in ML

D1.6 Interactive material maps (unsupervised ML), fabrication-structure (supervised ML) models

WP2 Lab-scale maturement of protocols for improved and replicable ultraporous carbons and MOFs assisted by machine learning

WP3 Scale-up and densification of selected ultraporous materials from the carbon and MOF families and their combinations.

WP4 Development and testing of advanced, fibre-reinforced lightweight metal alloys and coatings for hydrogen storage vessel.

D4.1 Report on literature and database gaps in MMCs& coatings for compressed H2 & cryo-Temp

D4.2 Datasheet of thermo-physical and mechanical properties of light metal alloys by WAAM

WP5 Design of vessel and ancillary components, digital twin and integration of short-term hydrogen storage system. Qualification of the demonstrator against application standards.

WP6 Life Cycle Assessment, Life Cycle Costing and overall Risk Assessment.

WP7 Exploitation, Dissemination and Communication.

WP8 Project Management.

Funded by the European Union under grant agreement 101058574. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

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