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Integrated Data-Driven Materials Science and Digitalisation (NSCI0032)

Key information

Faculty
Faculty of Mathematical and Physical Sciences
Teaching department
Faculty of Mathematical and Physical Sciences
Credit value
15
Restrictions
This module is open to MSc Advanced Materials Science (Data-Driven Innovations) students only.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

The module 鈥Integrated Data-Driven Materials Science and Digitalisation鈥 provides students with state-of-the art knowledge and expertise in integrated materials modelling, methods and practical modern advanced cloud-based tools to find `and create needed materials and process data for applications in advanced data-driven and machine learning workflows. It covers contemporary topics in digitalisation based on emerging ontology of materials and processes and connection to manufacturing (digital twins), high-throughput computations and characterisation, multiscale, and multi-equation physics based modelling, including electronic density functional theory (DFT), atomistic molecular dynamics (MD), mesoscopic coarse-grained molecular dynamics (CGMD), granular media (GM) and continuum structural mechanics and computational fluid mechanics (CFD) modelling, enabling modelling technological applications on all relevant scales. Advanced modern tools include cloud-based open e-science materials digitalisation and modelling platforms such as , , , and other emerging platforms.

Module deliveries for 2024/25 academic year

Intended teaching term: Term 1 听听听 Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Intended teaching location
香港六合彩 East
Methods of assessment
100% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
15
Module leader
Professor Adham Hashibon
Who to contact for more information
imd-office@ucl.ac.uk

Last updated

This module description was last updated on 19th August 2024.