There is a critical need to develop a method to pattern semiconducting polymers for device applications on the sub-micrometer scale.

Knowledge of the full phonon spectrum is essential to accurately calculate the dynamic disorder (σ) and hole mobility (μ h ) in organic semiconductors (OSCs). However, most vibrational spectroscopy techniques under-measure the phonons, thus limiting the phonon validation. Here, we measure and model the full phonon spectrum using multiple spectroscopic techniques and predict μ h using σ from only the Γ-point and the full Brillouin zone (FBZ). We find that only inelastic neutron scattering (INS) provides validation of all phonon modes, and that σ in a set of small molecule semiconductors can be miscalculated by up to 28% when comparing Γ-point against FBZ calculations. A subsequent mode analysis shows that many modes contribute to σ and that no single mode dominates. Our results demonstrate the importance of a thoroughly validated phonon calculation, and a need to develop design rules considering the full spectrum of phonon modes.

Atomic vibrations can inform about materials properties from hole transport in organic semiconductors to correlated disorder in metal−organic frameworks. Currently, there are several methods for predicting these vibrations using simulations, but the accuracy−efficiency tradeoffs have not been examined in depth. In this study, rubrene is used as a model system to predict atomic vibrational properties using six different simulation methods: density functional theory, density functional tight binding, density functional tight binding with a Chebyshev polynomial-based correction, a trained machine learning model, a pretrained machine learning model called ANI-1, and a classical forcefield model. The accuracy of each method is evaluated by comparison to the experimental inelastic neutron scattering spectrum. All methods discussed here show some accuracy across a wide energy region, though the Chebyshev-corrected tight-binding method showed the optimal combination of high accuracy with low expense. We then offer broad simulation guidelines to yield efficient, accurate results for inelastic neutron scattering spectrum prediction.