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Selbach, Sverre M.

Publications and source records attributed to Selbach, Sverre M..

4 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Observation of Antiferroelectric Domain Walls in a Uniaxial Hyperferroelectric

Abstract Ferroelectric domain walls are a rich source of emergent electronic properties and unusual polar order. Recent studies show that the configuration of ferroelectric walls can go well beyond the conventional Ising‐type structure. Néel‐, Bloch‐, and vortex‐like polar patterns have been observed, displaying strong similarities with the spin textures at magnetic domain walls. Here, the discovery of antiferroelectric domain walls in the uniaxial ferroelectric Pb 5 Ge 3 O 11 is reported. Highly mobile domain walls with an alternating displacement of Pb atoms are resolved, resulting in a cyclic 180° flip of dipole direction within the wall. Density functional theory calculations show that Pb 5 Ge 3 O 11 is hyperferroelectric, allowing the system to overcome the depolarization fields that usually suppress the antiparallel ordering of dipoles along the longitudinal direction. Interestingly, the antiferroelectric walls observed under the electron beam are energetically more costly than basic head‐to‐head or tail‐to‐tail walls. The results suggest a new type of excited domain‐wall state, expanding previous studies on ferroelectric domain walls into the realm of antiferroic phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Confinement‐Driven Inverse Domain Scaling in Polycrystalline ErMnO 3

Abstract The research on topological phenomena in ferroelectric materials has revolutionized the way people understand polar order. Intriguing examples are polar skyrmions, vortex/anti‐vortex structures, and ferroelectric incommensurabilties, which promote emergent physical properties ranging from electric‐field‐controllable chirality to negative capacitance effects. Here, the impact of topologically protected vortices on the domain formation in improper ferroelectric ErMnO 3 polycrystals is studied, demonstrating inverted domain scaling behavior compared to classical ferroelectrics. It is observed that as the grain size increases, smaller domains are formed. Phase field simulations reveal that elastic strain fields drive the annihilation of vortex/anti‐vortex pairs within the grains and individual vortices at the grain boundaries. The inversion of the domain scaling behavior has far‐reaching implications, providing fundamentally new opportunities for topology‐based domain engineering and the tuning of the electromechanical and dielectric performance of ferroelectrics in general.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Application of a long short-term memory for deconvoluting conductance contributions at charged ferroelectric domain walls

Ferroelectric domain walls are promising quasi-2D structures that can be leveraged for miniaturization of electronics components and new mechanisms to control electronic signals at the nanoscale. Despite the significant progress in experiment and theory, however, most investigations on ferroelectric domain walls are still on a fundamental level, and reliable characterization of emergent transport phenomena remains a challenging task. Here, we apply a neural-network-based approach to regularize local I ( V )-spectroscopy measurements and improve the information extraction, using data recorded at charged domain walls in hexagonal (Er 0.99 ,Zr 0.01 )MnO 3 as an instructive example. Using a sparse long short-term memory autoencoder, we disentangle competing conductivity signals both spatially and as a function of voltage, facilitating a less biased, unconstrained and more accurate analysis compared to a standard evaluation of conductance maps. The neural-network-based analysis allows us to isolate extrinsic signals that relate to the tip-sample contact and separating them from the intrinsic transport behavior associated with the ferroelectric domain walls in (Er 0.99 ,Zr 0.01 )MnO 3 . Our work expands machine-learning-assisted scanning probe microscopy studies into the realm of local conductance measurements, improving the extraction of physical conduction mechanisms and separation of interfering current signals.

36 MATERIALS SCIENCE↗