SOURCE-LINKED INTELLIGENCE
Embedded Nanoscale Ferroelectric Dynamics: Characterisation and Control of Domain Wall Motion for Reconfigurable Functional Materials
al sensitivity to structure, polarisation, strain, and electronic states, and allows in situ application of electric fields to drive domain wall dynamics. By coupling these measurements with advanced machine learning approaches, ENFOLD will overcome bottlenecks in disentangling polar, elastic, and magnetic signatures from complex datasets, and enable closed-loop, systematic control of domain wall motion to tune and optimise functional properties. By moving beyond static characterisation, conventional analyses, and manual control approaches, ENFOLD will establish a mechanistic nanoscale understanding of how electric fields drive domain wall motion and the emergence of novel embedded phases. This will provide the foundation for the systematic, on-demand design of reconfigurable ferroelectric domain wall devices, addressing a critical gap in the field. Scanning transmission electron microscopy, ferroelectrics, multiferroics, domain walls
Read original source ↗ Open in workspace
- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 260347.92
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T04:21:15.460Z. This is not the publication date.