most citedMachine-learning Based Extraction of the Short-Range Part of the Interaction in Non-contact Atomic Force Microscopy

4 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

cond-mat.mtrl-sci2025

High-throughput, Non-Destructive, Three-Dimensional Imaging of GaN Threading Dislocations with in-Plane Burgers Vector Component via Phase-Contrast Microscopy

Yukari Ishiakwa, Ryo Hattori, Yongzhao Yao +2

We demonstrate a nondestructive, high-throughput method for observing dislocations in GaN (0001) using phase-contrast microscopy (PCM). The PCM images (359x300 m) analyzed i…

cond-mat.mtrl-sci2025

High-speed, High-Resolution, Three-Dimensional Imaging of Threading Dislocations in beta- via Phase-Contrast Microscopy

Yukari Ishiakwa, Daiki Katsube, Yongzhao Yao +2

This study presents a nondestructive, high-resolution method for three-dimensional imaging of threading dislocations in beta- (010) using phase-contrast microscopy (PC…

cond-mat.mes-hall2020★ 4 cited

Machine-learning Based Extraction of the Short-Range Part of the Interaction in Non-contact Atomic Force Microscopy

Zhuo Diao, Daiki Katsube, Hayato Yamashita +3

A machine-learning method for extracting the short-range part of the probe-surface interaction from force spectroscopy curves is presented. Our machine-learning algorithm consists…