Fusion of Complementary 2D and 3D Mesostructural Datasets Using Generative Adversarial Networks (Adv. Energy Mater. 2/2023). Issue 2 (13th January 2023)

• Record Type: Journal Article
• Authors: Dahari, Amir; Kench, Steve; Squires, Isaac; Cooper, Samuel J.
• Is Part Of: Advanced energy materials. Volume 13:Issue 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-01-13
• Subjects: electrodes -- imaging -- machine learning -- microstructures -- super‐resolution; Energy harvesting -- Materials -- Periodicals; Energy conversion -- Materials -- Periodicals; Energy storage -- Materials -- Periodicals; Photovoltaics -- Periodicals; Fuel cells -- Periodicals; Thermoelectric materials -- Periodicals; 621.31
• DOI: 10.1002/aenm.202370009
• Languages: English
• ISSNs: 1614-6832

Abstract

Abstract : Imaging It is hard to obtain mesostructural image data with sufficient contrast, resolution, and field‐of‐view from a single imaging technique. In article number 2202407, Amir Dahari, Samuel J. Cooper and co‐workers present a method for combining information from pairs of complementary 2D and 3D imaging techniques in order to accurately reconstruct the desired volumes. The method uses generative adversarial networks to perform super‐resolution, style‐transfer, and dimensionality expansion.