42:33

Giovanni Vignale: Geometric Density Functional Theory

33:01

Janosh Riebesell: Foundational Machine Learning Potentials - Challenges and Opportunities

10:22

FAIRmat Tutorial 14 Part 5: Interfacing complex simulation and analysis workflows with NOMAD

23:04

FAIRmat Tutorial 14 Part 4: Extending NOMAD-Simulations to support custom methods and outputs

40:12

FAIRmat Tutorial 14 Part 3: Developing schemas and parsers for FAIR computational data storage

54:08

FAIRmat Tutorial 14 Part 2: Working with the NOMAD-Simulations schema plugin

16:59

FAIRmat Tutorial 14 Part 1: Introduction to NOMAD

49:11

FAIRmat Tutorial 13 Part 2: NOMAD’s Base Sections and Built in schemas for ELN

01:02:07

FAIRmat Tutorial 13 Part 3: Schema & Plugin development

28:39

FAIRmat Tutorial 13 Part 4: Deploying your NOMAD plugins

11:48

FAIRmat Tutorial 13 Part 1: Introduction

41:44

FAIRmat Tutorial 12: Introduction to NOMAD and NOMAD OASIS - Insights into technical aspects

01:04:50

FAIRmat Tutorial 12: Hands-on Demonstration - Explore schemas, parsers, and data analysis

01:11:29

Pioneers in electronic structure theory - Episode 2 - Ulf von Barth

24:41

FAIRmat users meeting - A postdoc's perspective on NOMAD and NOMAD Oasis

20:26

FAIRmat users meeting - NFDI and good practice in research data management - a funder's perspective

22:55

FAIRmat users meeting - FAIR Data Principles in Perovskite Solar Cell Research using NOMAD

21:23

FAIRmat users meeting - Introduction to FAIRmat by Pepe Márquez

22:14

FAIRmat Tutorial 11: Introduction to research data management

26:36

FAIRmat Tutorial 11: Introduction to the FAIR data principles

22:42

FAIRmat Tutorials 11: Data management plans - Purpose, content, examples

49:09

Brian Pauw: Glimpses of the future: a "full stack", highly automated materials reasearch laboratory

34:38

Kevin M. Jablonka: Why Machine Learning Can Find a New Material, but Not a Needle in a Haystack

45:46

Maia G. Vergniory: High-throughput search of topological materials and meta-materials

01:11:03

Pioneers in electronic structure theory - Episode 1 - Hardy Groß

46:11

Taylor D. Sparks: Moving beyond screening via generative machine learning models

45:03

FAIRmat Tutorial 10: Numerical precision in ab initio calculations

27:40

FAIRmat Tutorial 10: How to explore and upload to the NOMAD Archive and Repository

33:33

FAIRmat Tutorial 10: Knowledge-based XC functional exploration

39:47

FAIRmat Tutorial 10: Workflows and how to link DFT and beyond-DFT calculations

29:53

Carmen Herrmann: Molecular electronics and spintronics as a challenge for first-principles methods

28:00

Markus Kühbach: On Software Tools for Reproducible Atom Probe Research

21:24

Andrea Albino: The ELN functionality in NOMAD applied to an epitaxial synthesis use case

13:25

Ahmed Mansour: Data Management Plans: The foundation for proper handling of research data

26:02

Christoph T. Koch: Introduction to FAIRmat

08:08

FAIRmat Tutorial 9: NOMAD Plugins Outlook

24:09

FAIRmat Tutorial 9: Writing parsers for text-based file formats

10:35

FAIRmat Tutorial 9: Parsing complex tabular files

28:00

FAIRmat Tutorial 9: Schemas with normalizing functions

45:22

FAIRmat Tutorial 9: How to create a NOMAD plugin

15:19

FAIRmat Tutorial 8: Searching your ELN data

17:45

FAIRmat Tutorial 8: Using base classes and references

23:53

FAIRmat Tutorial 8: Tabular parsers and adding plots

20:04

FAIRmat Tutorial 8: Writing a custom schema

18:27

FAIRmat Tutorial 8: NOMAD usage

27:52

FAIRmat Tutorial 8: Introduction, vocabulary & key concepts

01:27:06

Daniel Schwalbe Koda: Machine learning for interatomic potentials

14:36

FAIRmat Tutorial 7: Uploading molecular dynamics data and examining the metadata by Joseph Rudzinski

27:57

FAIRmat Tutorial 7: Introduction to FAIRmat and NOMAD by Luca Ghiringhelli

43:02

FAIRmat Tutorial 7: Extracting data from the archive and trajectory analysis by Joseph Rudzinski

19:44

FAIRmat Tutorial 7: Molecular dynamics overview page and workflow visualizer by Joseph Rudzinski

42:51

Kentaro Kutsukake: Bayesian optimization for material processes

54:01

Gian-Marco Rignanese: Materials property prediction from limited and multi-fidelity datasets

01:29:33

Sergei Kalinin: Automated experiments - Workflow design

01:33:18

Bjork Hammer: Machine learning - Acceleration of global optimization

01:25:27

Markus Scheidgen: NOMAD - managing and accessing FAIR research data

01:28:10

Luca Ghiringhelli: Introduction to artificial intelligence and its application to materials science

09:25

FAIRmat Tutorial 6: Data sharing, visualisation and analysis in NOMAD by Sherjeel Shabih

25:50

FAIRmat Tutorial 6: Experiment from planning to data collection by M. Krieger, J. Lehmeyer, A. Fuchs

25:00

FAIRmat Tutorial 6: Q&A