Machine learning-assisted profiling of a kinked ladder polymer structure using scattering
Ladder polymers consisting of fused rings in the backbone have very limited conformational freedom, which results in very different properties from traditional linear polymers.
Authors
- Chi-Huan Tung (ORCID: https://orcid.org/0000-0002-2197-2074)
- Zekun Ye (ORCID: https://orcid.org/0000-0003-4260-5860)
- Lijie Ding (ORCID: https://orcid.org/0000-0002-2745-4606)
- Changwoo Do (ORCID: https://orcid.org/0000-0001-8358-8417)
- Zhiqiang Cao (ORCID: https://orcid.org/0000-0003-0114-2249)
- Yan Xia (ORCID: https://orcid.org/0000-0002-5298-748X)
- Wei‐Ren Chen (ORCID: https://orcid.org/0000-0002-5192-0777)
- Xiaodan Gu (ORCID: https://orcid.org/0000-0002-1123-3673)
Institutions
- Oak Ridge National Laboratory (US)
- University of Southern Mississippi (US)
- Stanford University (US)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00051c
- Citations
- 5
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 2.59
Funders
- U.S. Department of Energy
- Battelle
- UT-Battelle
- Office of Science
- Oak Ridge National Laboratory