Embedded Nanoscale Ferroelectric Dynamics: Characterisation and Control of Domain Wall Motion for Reconfigurable Functional Materials

Objective

Ferroelectric domain walls are dynamic nanoscale interfaces with functional properties distinct from the bulk, offering a potential route to next-generation nanoelectronics and platform for studying exotic topological states. They can be created, moved, and reconfigured by external stimuli including electric fields, strain, and temperature, enabling reversible control of conductivity and other local responses. Recent discoveries have suggested that complex polar topology can emerge dynamically during domain wall motion, with the prospect of realising multiferroicity in non-magnetic systems. Yet, systematic control has been limited by the difficulty of probing and directing these dynamics at the necessary length scales. ENFOLD aims to exploit the unique capabilities of scanning transmission electron microscopy (STEM) to systematically control the motion of ferroelectric domain walls and characterise the emergent behavior associated with domain wall dynamics at high spatial resolution. STEM offers multimodal 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.