Conducting polymers based on open-shell
radical moieties exhibit
potentially advantageous processing, stability, and optical attributes
compared with conventional doped conjugated polymers. Despite their
ascendance, reported radical conductors have been based almost exclusively
on (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO), which raises fundamental
questions regarding the ultimate limits of charge transport in these
materials and whether some of the deficiencies exhibited by contemporary
materials are due to the choice of radical chemistry. To address these
questions, we have performed a density functional theory (DFT) study
of the charge transfer characteristics of a broad range of open-shell
chemistries relevant to radical conductors, including p-type, n-type,
and ambipolar open-shell chemistries. We observe that far from being
representative, TEMPO exhibits anomalously high reorganization energies
due to strong charge localization. This, in turn, limits charge transfer
in TEMPO compared with more delocalized open-shell species. By comprehensively
mapping the dependence of charge transfer on radical–radical
orientation, we have also identified a large mismatch between the
conformations that are favored by intermolecular interactions and
the conformations that maximize charge transfer in all of the open-shell
chemistries investigated. These results suggest that significant opportunities
exist to exploit directing interactions to promote charge transport
in radical polymers.
Molecular quantum mechanical modeling, accelerated by machine learning, has opened the door to high‐throughput screening campaigns of complex properties, such as the activation energies of chemical reactions and absorption/emission spectra of materials and molecules; in silico. Here, we present an overview of the main principles, concepts, and design considerations involved in such hybrid computational quantum chemistry/machine learning screening workflows, with a special emphasis on some recent examples of their successful application. We end with a brief outlook of further advances that will benefit the field.
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