Motivation

The interface to FAIRmat is most relevant for NFDI-MatWerk, since condensed-matter physics is the basic science perspective on solid-state phenomena. The resulting consequence for the infrastructure is explored in this IUC. FAIRmat focuses their effort on fundamental chemo-physical effects. In the case of atom probe tomography (APT), for example, the correlation of details of the electric field and the electronic density in the specimen needs to be analyzed and understood in order to predict the emission of atoms from steps at the surface. Such predictions are the key to arrive at more accurate and precise predictions of the ion launch to support research on methods on improved reconstruction methods. In contrast, NFDI-MatWerk addresses the relevance of the microstructure for engineering materials and their applications. Therefore, the focus of NFDI-MatWerk is on the correlation of atomic positions and defect states as a function of the chemical potential and the specimen history (processing, heat treatment). For both perspectives, several gigabyte of data needs to be handled and evaluated with machine learning approaches.

Overview

Main requirements:

  • Workflows on how to process measured data (e.g., detector hit positions, time-of-flight per ion) into atomic positions and (molecular) ion types (chemical species) including all metadata with contextualization (e.g., sample preparation, electric field) (FAIRmat)
  • Close interaction with device software via open-source parsers and converters
  • Machine learning/statistical analysis of atom probe tomography (APT) atomic data to detect and interpret defect structures
  • Interface between formats and queries of (meta)data in FAIRmat and NFDI-MatWerk
  • Ontology matching between both communities
  • Workflow combining experimental data, image processing, and theoretical models/properties of defects in microstructured materials (NFDI-MatWerk)
Main Task Area: TA-WSD
Other related Task Areas: TA-OMS
Possible connections within NFDI: FAIRmat
Material/Data: Atom Probe Tomography (APT) for metallic alloys
Main Success Scenario: Through the physical modeling of the measurement process, users get more precise information and a deeper understanding of their experimental results, in particular to distinguish defect states in the microstructure.
Added value for the MatWerk community: Workflows are designed in coordination with FAIRmat such that the exchange of data, metadata, ontologies, and concepts for data curation between the two NFDI consortia is ensured without a loss of information. In this way, both consortia can mutually benefit from ongoing improvements in the infrastructure for condensed-matter physics (FAIRmat) and the interpretation of microstructure data (NFDI-MatWerk).

Goals

  • Develop Data Processing Workflows: Create workflows to process measured Atom Probe Tomography (APT) data into atomic positions and (molecular) ion types, including contextual metadata.
  • Enhance Machine Learning Analysis: Utilize machine learning and statistical analysis to detect and interpret defect structures in APT data.
  • Ensure Interface Compatibility: Establish interfaces for seamless data exchange and query between FAIRmat and NFDI-MatWerk.
  • Align Ontologies: Match and integrate ontologies between FAIRmat and NFDI-MatWerk to ensure consistent data curation.
  • Combine Experimental and Theoretical Workflows: Integrate experimental data, image processing, and theoretical models to analyze defect properties in microstructured materials.

Related Participant Projects

All Infrastructure Use Cases

NFDI-MatWerk
Funded by the German Research Foundation (DFG) under the National Research Data Infrastructure – NFDI 38/1 – 460247524

Sign up for our newsletter

Subscribe to our newsletter for regular updates about materials science topics!

After subscribing, you will receive an email from us with a confirmation link.
Only after clicking this link your registration is completed.