| Title: |
Non-destructive tomographic nanoscale imaging of ferroelectric domain walls |
| Authors: |
He, Jiali, Zahn, Manuel, Ushakov, Ivan N., Richarz, Leonie, Ludacka, Ursula, Roede, Erik D., Yan, Zewu, Bourret, Edith, Kézsmárki, István, Catalan, Gustau, Meier, Dennis |
| Publication Year: |
2023 |
| Collection: |
Condensed Matter |
| Subject Terms: |
Condensed Matter - Materials Science |
| More Details: |
Extraordinary physical properties arise at polar interfaces in oxide materials, including the emergence of two-dimensional electron gases, sheet-superconductivity, and multiferroicity. A special type of polar interface are ferroelectric domain walls, where electronic reconstruction phenomena can be driven by bound charges. Great progress has been achieved in the characterization of such domain walls and, over the last decade, their potential for next-generation nanotechnology has become clear. Established tomography techniques, however, are either destructive or offer insufficient spatial resolution, creating a pressing demand for 3D imaging compatible with future fabrication processes. Here, we demonstrate non-destructive tomographic imaging of ferroelectric domain walls using secondary electrons. Utilizing conventional scanning electron microscopy (SEM), we reconstruct the position, orientation, and charge state of hidden domain walls at distances up to several hundreds of nanometers away from the surface. A mathematical model is derived that links the SEM intensity variations at the surface to the local domain wall properties, enabling non-destructive tomography with good noise tolerance on the timescale of seconds. Our SEM-based approach facilitates high-throughput screening of materials with functional domain walls and domain-wall-based devices, which is essential for monitoring during the production of device architectures and quality control in real-time. |
| Document Type: |
Working Paper |
| Access URL: |
http://arxiv.org/abs/2311.00139 |
| Accession Number: |
edsarx.2311.00139 |
| Database: |
arXiv |
