Needle in a Haystack: Information Recovery in Low Signal‐to‐Noise Piezoresponse Force Microscopy Data (Small Methods 2/2026)

Small Methods 2026 Open access

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Authors: Kerisha N. Williams, Henry Shaowu Yuchi, Gardy Kevin Ligonde, Mathew Repasky, Yao Xie, Nazanin Bassiri‐Gharb
DOI: 10.1002/smtd.70385
Cited by: 1

Abstract

Inside Back Cover Clear signals emerge from a curtain of noise as this work reveals the true electromechanical behavior of ferroelectric materials. By identifying and reconstructing unreliable signals through Bayesian matrix completion, the framework restores physically meaningful responses and hence transforms low signal-to-noise data into coherent insight on nanoscale switching dynamics and material functionality via piezoresponse force microscopy. More in article number 2500318, Bassiri-Gharb and co-workers. Image design by Nicholas Preston.

Fields of Study & Subjects

Force Microscopy Techniques and Applications Innovative Energy Harvesting Technologies Ferroelectric and Piezoelectric Materials

Publication details

Journal / source
Small Methods
Publisher
Wiley
Volume
10
Issue
2
Publication date
1 January 2026
Language
EN