activity
20232026
most citedNovel implementations for reservoir computing -- from spin to charge

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.mtrl-sci2026

Photo-induced currents and short-term memory for reservoir computing in a ferroelectric semiconductor

Yan Meng Chong, Atreya Majumdar, Manuel Zahn +3

Physical reservoir computing represents an energy efficient approach for processing temporal signals by exploiting the intrinsic nonlinear dynamics and fading memory of a physical…

cond-mat.mtrl-sci2025

Domain-wall driven suppression of thermal conductivity in a ferroelectric polycrystal

Rachid Belrhiti-Nejjar, Manuel Zahn, Patrice Limelette +8

A common strategy for reducing thermal conductivity of polycrystalline systems is to increase the number of grain boundaries. Indeed, grain boundaries enhance the probability of ph…

cond-mat.mtrl-sci2024

Strain engineering of magnetic anisotropy in the kagome magnet Fe3Sn2

D. Kong, A. Kovács, M. Charilaou +7

The ability to control magnetism with strain offers innovative pathways for the modulation of magnetic domain configurations and for the manipulation of magnetic states in material…

cond-mat.mtrl-sci2024

Reversible long-range domain wall motion in an improper ferroelectric

M. Zahn, A. M. Müller, K. P. Kelley +8

Reversible ferroelectric domain wall movements beyond the 10 nm range associated with Rayleigh behavior are usually restricted to specific defect-engineered systems. Here, we demon…

cond-mat.mtrl-sci2024★ 1 cited

Coexistence of multi-scale domains in ferroelectric polycrystals with non-uniform grain-size distributions

K. Wolk, R. S. Dragland, E. Chavez Panduro +7

Engineering of ferroelectric domain structures enables direct control over the switching dynamics and is crucial for tuning the functional properties of ferroelectrics for various…

physics.app-ph2023★ 1 cited

Novel implementations for reservoir computing -- from spin to charge

Karin Everschor-Sitte, Atreya Majumdar, Katharina Wolk +1

Topological textures in magnetic and electric materials are considered to be promising candidates for next-generation information technology and unconventional computing. Here, we…