This research paper presents a chemical compiler developed to find optimal configurations of a platform for synthesizing specific branched oligomers in an artificial chemistry, along with exemplary compiler output and benchmarks where the platform configuration suggested by the compiler is compared to other configurations in simulation. The compiler operates as a pipeline with two stages: labelling and optimization. The report explains the structure of the compiler target and its interpretation, followed by a code walk-through of the compiler stages with code snippets and examples. The compiler can be used as a code generator for reactions in a chemical simulator and to derive loading schemes for multilevel droplets. The results obtained in simulations suggest that the container system can efficiently optimize the yield of coupled reaction networks and that multi-level droplets can lead to significant improvements.

We simulate the movement and agglomeration of oil droplets in water under constraints, like confinement, using a simplified stochastic-hydrodynamic model. In the analysis of the network created by the droplets in the agglomeration, we focus on the paths between pairs of droplets and compare the computational results for various system sizes.

Within the context of the European Horizon 2020 project ACDC , we intend to develop a probabilistic chemical compiler, to aid the construction of three-dimensional agglomerations of artificial hierarchical cellular constructs. These programmable discrete units offer a wide variety of technical innovations, like a portable biochemical laboratory that e.g. produces macromolecular medicine on demand. For this purpose, we have to investigate the agglomeration process of droplets and vesicles under proposed constraints, like confinement. This paper focuses on the influence of the geometry of the initialization and of the container on the agglomeration.

In this work, we propose a framework that derives the configuration of an artificial, compartmentalized, cell-like structure in order to maximize the yield of a desired output reactant given a formal description of the chemistry. The configuration of the structure is then used to compile G-code for 3D printing of a microfluidic platform able to manufacture the aforementioned structure. Furthermore, the compiler output includes a set of pressure profiles to actuate the valves at the input of the microfluidic platform. The work includes an outline of the steps involved in the compilation process and a discussion of the algorithms needed for each step. Finally, we provide formal, declarative languages for the input and output interfaces of each of these steps.