Organic photovoltaic, OPVs, are promising energy-harvesting devices because of their low cost, short energy-payback time, and suitability for mass production. They have, however, lower power conversion efficiency—11 % at highest [1]—than silicon-based ones, and optimization scheme is required. An active layer of an OPV is composed of organic donor and acceptor, which are respectively a π-conjugated polymer, and a fullerene-derivative or a “non-fullerene” π-conjugated small molecule.

Performance is determined by material properties of the organic semiconductors: HOMO and LUMO levels, charge mobility, absorbance, exciton lifetime, etc [2]. A number of experimental and theoretical studies have been devoted to developing new materials. It is however challenging to optimize the properties simultaneously, and tune of properties does not necessarily improve performance due to trade-off. For example, narrowing of bandgap enhances short-circuit current density but reduces open-circuit voltage.

Another key factor is morphology—degree of phase separation (~nm) of organic materials—because it strongly affects exciton dissociation and charge collection [3]. Morphology depends on manufacturing conditions, e.g., drying rate, and annealing temperature and duration, but optimization scheme is not established. There are many experimental techniques to observe morphologies: optical microscopy, X-ray scattering, and scanning and transmission electron microscopies. Especially, conductive atomic force microscopy, C-AFM, offers high-resolution (from a few to dozens of nanometers) information on probed components [4]. It is, however, challenging to experimentally obtain three-dimensional high-resolution information about morphologies. On the other hand, theorist have generated morphologies by means of molecular dynamics, Ising model, Cahn–Hilliard equation, reptation, etc. Device-scale (~100 nm) morphologies are necessary for evaluation of performance by simulation of photo-current, but few combinations of material properties and morphologies have been examined.

Finally, dependence of performance on morphology and properties is not well examined, and a new scheme is required.

To address this, we implemented device-scale (150³ nm³) OPV simulators to examine temperature-, morphology-, and property-dependence of performance: Metropolis Monte Carlo simulator of reptation, a coarsened model of polymer, to generate morphologies under annealing; dynamic Monte Carlo, DMC, simulator to evaluate performance of morphologies and properties.  The DMC is able to simulate photo and dark current, transient absorption spectroscopy, and C-AFM. Reptation reproduced domain growth of morphologies under annealing, and DMC showed existence of optimal annealing temperature [5]. The program was improved to afford high-throughput computations and to create database of morphologies, material properties, and performances, which will enable to predict three-dimensional morphologies from experimental C-AFM images, and to provide design guideline.