most citedTo switch or not to switch -- a machine learning approach for ferroelectricity

16 citations · 17 across the 3 of their papers we have counts for

collaborators

5 papers

cond-mat.mes-hall202016 cited

To switch or not to switch -- a machine learning approach for ferroelectricity

Sabine M. Neumayer, Stephen Jesse, Gabriel Velarde +5

With the advent of increasingly elaborate experimental techniques in physics, chemistry and materials sciences, measured data are becoming bigger and more complex. The observables…

physics.app-ph2020

Super-resolution and signal separation in contact Kelvin probe force microscopy of electrochemically active ferroelectric materials

Maxim Ziatdinov, Dohyung Kim, Sabine Neumayer +7

Imaging mechanisms in contact Kelvin Probe Force Microscopy (cKPFM) are explored via information theory-based methods. Gaussian Processes are used to achieve super-resolution in th…

physics.app-ph2019

Piezoresponse phase as variable in electromechanical characterization

Sabine M. Neumayer, Sahar Saremi, Lane W. Martin +5

Piezoresponse force microscopy (PFM) is a powerful characterization technique to readily image and manipulate ferroelectrics domains. PFM gives insight into the strength of local p…

physics.comp-ph20191 cited

Imaging Mechanism for Hyperspectral Scanning Probe Microscopy via Gaussian Process Modelling

Maxim Ziatdinov, Dohyung Kim, Sabine Neumayer +5

We investigate the ability to reconstruct and derive spatial structure from sparsely sampled 3D piezoresponse force microcopy data, captured using the band-excitation (BE) techniqu…

cond-mat.mtrl-sci2019

Room Temperature Electrocaloric Effect in Layered Ferroelectric CuInP2S6 for Solid State Refrigeration

Mengwei Si, Atanu K. Saha, Pai-Ying Liao +10

A material with reversible temperature change capability under an external electric field, known as the electrocaloric effect (ECE), has long been considered as a promising solid-s…