Life’s origin and chemical evolution requires continuous and substantial selective processes at the molecular scale. However, the spontaneous emergence of selection, its mechanism and system-level influence are still insufficiently explored. To address this, an automated experimental framework has been devised to identify selection in a recursive system of oligomerizing molecules with closed-loop analytics. The approach is based on Assembly Theory, using Molecular Assembly (MA) index as an inherent complexity measure of molecules and molecular networks. A string-based MA model was developed to assist in the efficient analysis of diverse lengthy oligomers and to allow string information procedures. Coupled with smart algorithmic decision-making, the system will attempt to maximize the molecular network’s complexity in the reactor over recursive cycles. Following patterns of increasing chemical complexity in the molecular system could reveal definite traces of selection and determine the conditions and agents that promote it. This work elucidates why improbable complex states emerge, pertinent to life’s origin and its major evolutionary transitions.

In my laboratory we are interested in creating the conditions that allow an artificial life form to emerge. But how do we know when our chemical system is really on the path to life? Will bottom- up (prebiotic) and top-down (programmed) be intrinsically different types of artificial life forms? In this lecture I will describe three areas of work in my laboratory: 1) how to measure how alive an artificial life form is; 2) our attempts to emerge a bottom up life form; 3) a top down chemically embodied life form. To achieve the top-down life form we had to build a chemical computer that was able to be digitally programmed, error correcting, and ability to do computations using a chemical-logic-machine. We believe this represents the first example of chemical artificial life.

There is great interest in oil-in-water droplets as simple systems that display astonishingly complex behaviours. Recently, we reported a chemorobotic platform capable of autonomously exploring and evolving the behaviours these droplets can exhibit. The platform enabled us to undertake a large number of reproducible experiments, allowing us to probe the non-linear relationship between droplet composition and behaviour. Herein we introduce this work, and also report on the recent developments we have made to this system. These include new platforms to simultaneously evolve the droplets’ physical and chemical environments and the inclusion of selfreplicating molecules in the droplets.