Solvent-based thin-film deposition constitutes a popular class of fabrication strategies for manufacturing organic electronic devices like organic solar cells. All such solvent-based techniques usually involve preparing dilute blends of electron-donor and electron-acceptor materials dissolved in a volatile solvent. After some form of coating onto a substrate to form a thin film, the solvent evaporates. An initially homogeneous mixture separates into electron-acceptor rich and electron-donor rich regions as the solvent evaporates. Depending on the specifics of the blend, processing conditions, and substrate characteristics different morphologies are typically formed. Experimental evidence consistently confirms that the resultant morphology critically affects device performance. A computational framework that can predict morphology evolution can significantly augment experimental analysis. Such a framework will also allow high throughput analysis of the large phase space of processing parameters, thus yielding considerable insight into the process-structure-property relationships governing organic solar cell behavior.In this paper, we formulate a computational framework to predict evolution of morphology during solvent-based fabrication of organic thin films. This is accomplished by developing a phase field-based model of evaporation-induced and substrate-induced phase-separation in ternary systems. This formulation allows most of the important physical phenomena affecting morphology evolution during fabrication to be naturally incorporated. We discuss the various numerical and computational challenges associated with a three dimensional, finite-element based, massively parallel implementation of this framework. This formulation allows, for the first time, to model three-dimensional nanomorphology evolution over large time spans on device scale domains. We illustrate this framework by investigating and quantifying the effect of various process and system variables on morphology evolution. We explore ways to control the morphology evolution by investigating different evaporation rates, blend ratios and interaction parameters between components.

a b s t r a c tWe present an efficient numerical framework for analyzing spinodal decomposition described by the Cahn-Hilliard equation. We focus on the analysis of various implicit time schemes for two and three dimensional problems. We demonstrate that significant computational gains can be obtained by applying embedded, higher order Runge-Kutta methods in a time adaptive setting. This allows accessing time-scales that vary by five orders of magnitude. In addition, we also formulate a set of test problems that isolate each of the sub-processes involved in spinodal decomposition: interface creation and bulky phase coarsening. We analyze the error fluctuations using these test problems on the split form of the Cahn-Hilliard equation solved using the finite element method with basis functions of different orders. Any scheme that ensures at least four elements per interface satisfactorily captures both sub-processes. Our findings show that linear basis functions have superior error-to-cost properties.This strategy -coupled with a domain decomposition based parallel implementationlet us notably augment the efficiency of a numerical Cahn-Hillard solver, and open new venues for its practical applications, especially when three dimensional problems are considered. We use this framework to address the isoperimetric problem of identifying local solutions in the periodic cube in three dimensions. The framework is able to generate all five hypothesized candidates for the local solution of periodic isoperimetric problem in 3D -sphere, cylinder, lamella, doubly periodic surface with genus two (Lawson surface) and triply periodic minimal surface (P Schwarz surface).

Abstract:Blending of small-molecule organic semiconductors (OSCs) with amorphous polymers is known to yield high performance organic thin film transistors (OTFTs). Vertical stratification of the OSC and polymer binder into well-defined layers is crucial in such systems and their vertical order determines whether the coating is compatible with a top and/or a bottom gate OTFT configuration. Here, we investigate the formation of such blends prepared via spincoating in conditions which yield bilayer and trilayer stratifications, and use a combination of experimental and computational tools to study the competing effects of formulation thermodynamics and process kinetics in mediating the final vertical stratification. We show that trilayer stratification (OSC/polymer/OSC) is the thermodynamically favored configuration and that formation of the buried OSC layer can be kinetically inhibited in certain conditions of spincoating, resulting in a bilayer stack instead. Our analysis reveals that preferential loss of the Zhao et al., Adv. Func. Mater. 2016 2 OSC, combined with early aggregation of the polymer phase due to rapid drying, inhibit the formation of the buried OSC layer. We then moderate the fluid dynamics and drying kinetics during spin-coating to promote trilayer stratification with a high quality buried OSC layer which yields unusually high mobility >2 cm 2 V -1 s -1 in the bottom-gate top-contact configuration.

Organic solar cells (OSC) have the potential for widespread usage, due to their promise of low cost, roll-to-roll manufacturability, and mechanical flexibility. However, ubiquitous deployment is impeded by their relatively low power conversion efficiencies (PCE). The last decade has seen significant progress in enhancing the PCE of these devices through various strategies. One such approach is based on morphology control. This is because morphology affects all phenomena involved in solar conversion: (1) light absorption and electron-hole pair (exciton) generation; (2) exciton diffusion and dissociation into free charges; and (3) transport of charges to the electrodes.Progress in experimental characterization and computational modeling now allow reconstruction and imaging of thin film morphology. This opens up the possibility of rationally linking fabrication processes with morphology, as well as morphology with performance. In this context, a comprehensive set of computational tools to rapidly quantify and classify the 2D/3D heterogeneous internal structure of thin films will be invaluable in linking process, structure, and property.We present a novel graph-based framework to efficiently compute a broad suite of physically meaningful morphology descriptors. These morphology descriptors are further classified according to the physical subprocesses within OSCs -photon absorption, exciton diffusion, charge separation, and charge transport. This approach is motivated by the equivalence between a discretized 2D/3D morphology and a labeled, weighted, undirected graph. We utilize this approach to pose six key questions related to structure characterization. We subsequently construct estimates and rigorous upper bounds of various efficiencies. The approach is showcased by characterizing the effect of thermal annealing on time-evolution of a thin film morphology. We conclude by formulating natural extensions of our framework to characterize crystallinity and anisotropy of the morphology using the framework.