High-mobility semiconducting polymers with different spin ground states

Organic semiconductors with high-spin ground states are fascinating because they could enable fundamental understanding on the spin-related phenomenon in light element and provide opportunities for organic magnetic and quantum materials. Although high-spin ground states have been observed in some quinoidal type small molecules or doped organic semiconductors, semiconducting polymers with high-spin at their neutral ground state are rarely reported. Here we report three high-mobility semiconducting polymers with different spin ground states. We show that polymer building blocks with small singlet-triplet energy gap (ΔES-T) could enable small ΔES-T gap and increase the diradical character in copolymers. We demonstrate that the electronic structure, spin density, and solid-state interchain interactions in the high-spin polymers are crucial for their ground states. Polymers with a triplet ground state (S = 1) could exhibit doublet (S = 1/2) behavior due to different spin distributions and solid-state interchain spin-spin interactions. Besides, these polymers showed outstanding charge transport properties with high hole/electron mobilities and can be both n- and p-doped with superior conductivities. Our results demonstrate a rational approach to high-mobility semiconducting polymers with different spin ground states.

Identifier
Source https://archive.materialscloud.org/record/2022.46
Metadata Access https://archive.materialscloud.org/xml?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:1300
Provenance
Creator Chen, Xiao-Xiang; Li, Jia-Tong; Fang, Yu-Hui; Deng, Xin-Yu; Wang, Xue-Qing; Liu, Guangchao; Wang, Yunfei; Gu, Xiaodan; Jiang, Shang-Da; Lei, Ting
Publisher Materials Cloud
Publication Year 2022
Rights info:eu-repo/semantics/openAccess; Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Contact archive(at)materialscloud.org
Representation
Language English
Resource Type Dataset
Discipline Materials Science and Engineering