Clustering cross-domain simulation, measurement and process data to derive data-model requirements for vitrimer qualification

Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed

Contributors

Abstract

Vitrimers are promising materials for sustainable lightweight structures, e.g. in battery electric vehicles. Their current research spans molecular simulation, testing and manufacturing, generating heterogeneous multiscale data that currently reside in isolated files, limiting reuse and cross-domain analysis. Graph-based data management can capture this data efficiently. We record domain workflows via structured questionnaires and code them using the Gioia methodology. This results in seven aggregate dimensions. These are translated into competency questions specifying the entities and relationships a labelled property graph data model must represent. On this basis, we extend an existing Vitrimer Base Schema towards an extensible model for cross-domain vitrimer qualification.

Details

Original languageEnglish
Title of host publicationProceedings of the 37th Symposium Design for X (DFX2026)
EditorsKristin Paetzold-Byhain, Dieter Krause, Sandro Wartzack, Alexander Koch
PublisherThe Design Society
Pages100-109
Number of pages10
Publication statusPublished - Oct 2026
Peer-reviewedNo

Publication series

SeriesProceedings of the Design Society
VolumeDS151
ISSN2732-527X

Symposium

Title37th Symposium Design for X
Abbreviated titleDFX 2026
Conference number37
Duration7 - 8 October 2026
Website
Degree of recognitionNational event
LocationTagungszentrum der sächsischen Wirtschaft (TSW)
CityRadebeul
CountryGermany

External IDs

ORCID /0000-0002-8504-2095/work/231454523
ORCID /0000-0003-1370-064X/work/231455673
ORCID /0000-0002-0406-5800/work/231456888
ORCID /0000-0003-3624-3242/work/231457950
ORCID /0000-0001-9789-2823/work/231458052
ORCID /0000-0002-8537-4591/work/231458065

Keywords

Keywords

  • Vitrimers, Data Management, Labelled Property Graph, Material Qualification, Gioia Methodology