In recent years, stable organic radical functional groups have been incorporated into a variety of polymeric materials for use as electrodes within energy storage devices, for example, batteries and capacitors. With the complex nature of the charge-transfer processes in a polymer matrix, the morphologies of the polymer films can have a significant impact on the redox behavior of the organic-based radical. To elucidate possible effects of packing on electron-transport mechanisms, theoretical modeling of the well-characterized cathode material poly(2,2,6,6-tetramethylpiperidinyloxy methacrylate) (PTMA) was conducted. Polymer morphologies were modeled using classical molecular dynamics simulations, and subsequently, the electronic-coupling matrix element between each radical site was calculated. Building on a previously derived treatment of diffusion in inhomogeneous materials, an expression for an effective electron diffusion length and an effective electron diffusion rate was derived in terms of an electronic-coupling-weighted radial distribution function. Two primary distances were found to contribute to the effective electron transfer length of 5.5 Å with a majority of the electron transfer, nearly 85%, occurring between radical sites on different polymer chains. Finally, we point out that this analysis of charge transfer using an electronic-coupling-weighted radial distribution function has application beyond the specific system addressed here and that it may prove useful more generally for simulating electron-transfer processes in disordered molecular materials.

A dynamic-charge, many-body potential function is proposed for the hafnium/hafnium oxide system. It is based on an extended Tersoff potential for semiconductors and the charge-optimized many-body potential for silicon oxide. The materials fidelity of the proposed formalism is demonstrated for both hafnium metal and various hafnia polymorphs. In particular, the correct orders of the experimentally observed polymorphs of both the metal and the oxide are obtained. Satisfactory agreement is found for the structural and mechanical properties, defect energetics, and phase stability as compared to first-principles calculations and/or experimental values. The potential can be used in conjunction with the previously determined potentials for the Si and SiO 2 system. This transferability is demonstrated by comparing the structure of a hafnia/silicon interface to that previously determined from electronic-structure calculations.

Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data, machine learning approaches can enable rapid high-throughput virtual screening of large libraries of compounds. Graph-based neural network architectures have emerged in recent years as the most successful approach for predictions based on molecular structure and have consistently achieved the best performance on benchmark quantum chemical datasets. However, these models have typically required optimized 3D structural information for the molecule to achieve the highest accuracy. These 3D geometries are costly to compute for high levels of theory, limiting the applicability and practicality of machine learning methods in high-throughput screening applications. In this study, we present a new database of candidate molecules for organic photovoltaic applications, comprising approximately 91 000 unique chemical structures. Compared to existing datasets, this dataset contains substantially larger molecules (up to 200 atoms) as well as extrapolated properties for long polymer chains. We show that message-passing neural networks trained with and without 3D structural information for these molecules achieve similar accuracy, comparable to state-of-the-art methods on existing benchmark datasets. These results therefore emphasize that for larger molecules with practical applications, near-optimal prediction results can be obtained without using optimized 3D geometry as an input. We further show that learned molecular representations can be leveraged to reduce the training data required to transfer predictions to a new density functional theory functional.

The relationship between the polymer network and electronic transport properties for stable radical polymeric materials has come under investigation owing to their potential application in electronic devices. For the radical polymer poly(2,2,6,6-tetramethylpiperidine-4-yl-1-oxyl methacrylate), it is unclear whether the radical packing is optimal for charge transport partially because the relationship between radical packing and molecular structure is not well-understood. Using the paramagnetic nitroxide radical as a probe of the polymer and synthetic techniques to control the radical concentration on the methyl methacrylate backbone, we investigate the dependence of radical concentration on molecular structure. The electron paramagnetic resonance data indicate that radicals in the PTMA assume a closest approach distance to each other when more than 60% of the backbone is populated with radical pendant groups. Below 60% coverage, the polymer rearranges to accommodate larger radical-radical spacing. These findings are consistent with theoretical calculations and help explain some experimentally determined electron-transport properties.

On the basis of atomistic simulations of the stable organic radical polymer material poly(2,2,6,6-tetramethylpiperidinyloxy methacrylate) (PTMA), various material properties relating to charge transport were evaluated in terms of the Marcus charge-transfer rates between radical sites. The reorganization energy of the PTMA monomer unit was calculated using density functional theory to provide an approximate value to enter into the Marcus charge-transfer rate. The role of energetic disorder in the charge transfer between sites caused by the different local environments seen by radical sites is examined in terms of both steric and electrostatic effects. The electronic coupling between sites was examined in terms of the intersite network, morphological features, and energetic disorder. Energetic disorder was found to result in both sites that act as traps and paired sites that were highly coupled to each other and would act as a single site for transport purposes.