Macromolecules that exhibit both electron transport and ionic mass transport (i.e., mixed conducting polymers) are ascendant with respect to both emerging application spaces and the elucidation of their fundamental physical principles. The unique coupling between the two modes of conduction puts these materials at the center of many next-generation organic electronic applications. The molecular details of this coupling are also at the epicenter of outstanding questions about how these materials function; how monomer and macromolecular chemistry dictates observable properties; and ultimately, how these macromolecular materials can be rationally designed, processed, and implemented into high-performance devices. Here, we focus on what is currently known about coupled ionic-electronic transport in these polymers and where there are open opportunities in the field. These opportunities include the syntheses of designer macromolecules, the need for significant simulation efforts that provide molecular-level insights into the mixed conduction mechanism, and the need for advanced characterization techniques for real-time monitoring of polymer morphology, as this is critical to coupled ion-charge transport processes. Considering the early stage of this important subfield of polymer science, we also present our view of how the development of mixed conductors can benefit from the lessons learned from previous polymerbased electronic devices.
Developing accurate coarse-grained (CG) models is critical for addressing long time and length scale phenomena with molecular simulations. Here, we distinguish and quantify two sources of error that are relevant to CG models in order to guide further methods development: “representability” errors, which result from the finite basis associated with the chosen functional form of the CG model and mapping operator, and “information” errors, which result from the limited kind and quantity of data supplied to the CG parameterization algorithm. We have performed a systematic investigation of these errors by generating all possible CG models of three liquids (butane, 1-butanol, and 1,3-propanediol) that conserve a set of chemically motivated locality and topology relationships. In turn, standard algorithms (iterative Boltzmann inversion, IBI, and multiscale coarse-graining, MSCG) were used to parameterize the models and the CG predictions were compared with atomistic results. For off-target properties, we observe a strong correlation between the accuracy and the resolution of the CG model, which suggests that the approximations represented by MSCG and IBI deteriorate with decreasing resolution. Conversely, on-target properties exhibit an extremely weak resolution dependence that suggests a limited role of representability errors in model accuracy. Taken together, these results suggest that simple CG models are capable of utilizing more information than is provided by standard parameterization algorithms, and that model accuracy can be improved by algorithm development rather than resorting to more complicated CG models.
Organic polymers that exhibit both ionic and electronic conduction are of interest for energy storage devices and emerging bioelectronic applications. Nevertheless, organic mixed conductors are at an early stage of development with nascent design rules and relatively few material chemistries having been experimentally characterized. Here we report a coarse-grained modeling framework that is sufficiently flexible to represent a range of mixed conducting chemistries while retaining the molecular physics necessary to interrogate structure-function relationships. A detailed overview of the framework is presented, accompanied by an applied study of the effect of hydration and oxidation levels on a representative mixed conductor. The model recapitulates experimental trends related to the macroscopic ionic and electronic conductivities, including the non-linear suppression of the electronic mobility with respect to oxidation level and the direct relationship between ionic mobility and hydration level, while revealing the complex interplay of polymer morphology, ionic-electronic coupling, and electrolyte distribution that govern these relationships. These results provide a validation of this framework for future applications in establishing structure-function relationships in this important materials class, and suggests several near-term opportunities for tailoring mixed conduction via side-chain design. File list (2) download file view on ChemRxiv main.pdf (34.25 MiB) download file view on ChemRxiv SI.pdf (1.79 MiB)
Organic mixed ionic-electronic conductors (OMIECs) are a developing class of organic electronic materials distinguished by their dual modes of conduction.The side-chains of OMIEC polymers are responsible for forming a percolating electrolyte phase that mediates doping and ionic conduction. Despite this critical role, design rules for OMIEC side-chains are still nascent and their effects on OMIEC morphology and charge transport have yet to be systematically studied. Here we perform the first dedicated coarse-grained molecular dynamics study of OMIECs where the side-chain identity and distribution are systematically varied using a random copolymer architecture. The simulations recapitulate the nonlinear progression of the morphology from an interfacially gated electrolyte when large fractions of hydrophobic side-chains are incorporated, to an electrolyte swelled morphology after crossing a threshold of approximately 40% polar side-chains. Kinetic Monte Carlo simulations were used to characterize the charge transport behaviors in these systems, revealing two interesting maxima in the mobility at 40% and 100% polar side-chain fractions, respectively. With respect to maximizing the charge mobility and conductivity, these simulations suggest that a uniform hydrophilic side-chain distribution is optimal and that there are few advantages to using mixed side-chains in a random copolymer architecture. These results also suggest several alternative side-chain engineering strategies for optimizing OMIEC performance.
Swimming at low Reynolds number in Newtonian fluids is only possible through non-reciprocal body deformations due to the kinematic reversibility of the Stokes equations. We consider here a model swimmer consisting of two linked spheres, wherein one sphere is rigid and the other an incompressible neo-Hookean solid. The two spheres are connected by a rod which changes its length periodically. We show that the deformations of the body are non-reciprocal despite the reversible actuation and hence, the elastic two-sphere swimmer propels forward. Our results indicate that even weak elastic deformations of a body can affect locomotion and may be exploited in designing artificial microswimmers.
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