Multivariate temperature-series analysis of stress-induced ferroelectricity in SrTiO3: a machine learning approach with K-shape clustering and hierarchical Bayesian estimation
A new machine learning approach that transforms time-series analysis into temperature-series analysis is introduced to analyze stress-induced ferroelectricity in SrTiO3 at 231 MPa using birefringence images observed at successive temperatures. The spatial distribution of the temperature-series data...
Saved in:
| Main Authors: | Hirotaka Manaka, Kensei Toyoda, Yoko Miura |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Science and Technology of Advanced Materials: Methods |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/27660400.2024.2342234 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improvements of birefringence imaging techniques to observe stress-induced ferroelectricity in SrTiO3 based on K-means clustering with circular statistics
by: Kensei Toyoda, et al.
Published: (2023-12-01) -
Strontium Titanate (SrTiO3) for Adsorption of Cd(II) Ions and Photodegradation of Methylene Blue Dye in Aqueous Solutions
by: Amanda das Graças Barbosa, et al.
Published: (2025-05-01) -
Efficient Photocatalytic Hydrogen Evolution via Cocatalyst Loaded Al-doped SrTiO3
by: Zh. Kuspanov, et al.
Published: (2024-10-01) -
Effect of spin coating speeds on electrical and optical characteristic of perovskite SrTiO3 thin films prepared by sol-gel method
by: M.M. Osman, et al.
Published: (2024-12-01) -
Structural and Optical Properties of SrTiO3-Based Ceramics for Energy and Electronics Applications
by: Donghoon Kim, et al.
Published: (2024-10-01)