Elucidating Morphology‐Mobility Relationships of Organic Thin Films Through Transfer Learning‐Assisted Multiscale Simulation (Adv. Funct. Mater. 22/2024)
Source abstract
Abstract
Machine Learning-Assisted Simulations In article number 2313085, Dong Wang, Tianhao Tan, and Lian Duan utilize machine learning-assisted multiscale simulations to elucidate morphology–mobility relationships of solution processed organic thin films. The results indicate that moderate shearing speeds, together with a suitable solvent, promote the development of extended transport networks, ultimately enhancing the mobility of the films.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Machine Learning in Materials Science · Block Copolymer Self-Assembly · Electron and X-Ray Spectroscopy Techniques
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Affiliations
Laboratory of Flexible Electronics Technology Tsinghua University Beijing 100084 P. R. China
MOE Key Laboratory of Organic OptoElectronics and Molecular Engineering Department of Chemistry Tsinghua University Beijing 100084 P. R. China
References
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