A molecular computing approach to solving optimization problems via programmable microdroplet arrays

The search for novel forms of computing to the dominant von Neumann model-based approach is important as it will enable different classes of problems to be solved. Molecular computers are a promising alternative to semiconductor-based computers given their potential biocompatibility and cost advantages. The vast space of chemical reactions makes molecules a tunable, scalable, and energy-efficient computational vehicle. In molecular computers, memory and processing units can be combined into a single, inherently parallelized device. Here, we present a microdroplet array molecular computer to solve combinatorial optimization problems by employing an Ising Hamiltonian to map problems heuristically to droplet-droplet interactions. The droplets represent binary digits and problems are encoded in intra- and inter-droplet reactions. We propose two implementations: first, a hybrid classical-molecular computer that enforces inter-droplet constraints in a classical computer and, second, a purely molecular computer where the problem is entirely pre-programmed in the nearest-neighbor droplet reactions.