Precise determination of structural organization of semi-conducting polymers is of paramount importance for the further development of these materials in organic electronic technologies. Yet, prior characterization of some of the best-performing materials for transistor and photovoltaic applications, which are based on polymers with rigid backbones, often resulted in conundrums in which X-ray scattering and microscopy yielded seemingly contradicting results. Here we solve the paradox by introducing a new structural model, i.e. , semi-paracrystalline organization. The model establishes that the microstructure of these materials relies on a dense array of small paracrystalline domains embedded in a more disordered matrix. Thus, the overall structural order relies on two parameters: the novel concept of degree of paracrystallinity ( i.e. , paracrystalline volume/mass fraction, introduced here for the first time) and the lattice distortion parameter of paracrystalline domains ( g -parameter from X-ray scattering). Structural parameters of the model are correlated with long-range charge carrier transport, revealing that charge transport in semi-paracrystalline materials is particularly sensitive to the interconnection of paracrystalline domains. 
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                            Semi-Path: An interactive semi-supervised learning framework for gigapixel pathology image analysis
                        
                    - Award ID(s):
- 1934568
- PAR ID:
- 10555947
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Smart Health
- Volume:
- 32
- Issue:
- C
- ISSN:
- 2352-6483
- Page Range / eLocation ID:
- 100474
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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