In combinatorial research, one seeks to mimic a natural evolution process, such that a diverse collection of materials improves over time, in response to an external challenge. Modeling such experiments is important for validation and rational design challenges. We present a new hybrid modeling method, which allows more efficient simulation of mesoscale (10 À9 -10 À6 m) phenomena, and is a prototype for a broader approach, which we intend to encompass molecular interactions, nanoscale, and microfluidics. As an example and proof of principle, we examined partition and self-assembly of surfactant from aqueous solution onto the surface of an oil droplet, and the phase separation of a block copolymer to an oil/water interface by using a hybrid self-consistent field/dissipative particle dynamics (SCF-DPD) model.