Natural living systems on Earth (i) process information, (ii) metabolize, (iii) self-reproduce and (iv) evolve. These functional properties of life are traditionally associated with the presence of a boundary, metabolism and information-carrying polymers. How can (i)-(iv) be integrated in a chemical system? Our 1-pot chemical system avoids bio-chemistry and is completely artificial. We present progress in this area resulting from experiments on autonomous system boot-up generated during the chemically controlled non-equilibrium assembly of active vesicles. We follow their dynamical evolution with membrane growth and metabolism working in concert and under autonomous chemical control. This is achieved by implementing a PISA (Polymerization Induced Self-Assembly) polymerization and encapsulation scenario, which solves the concentration problem and generates an all-important free-energy gradient. As chemicals (“fuels”) are consumed in the polymerization reaction, energy is dissipated and entropy changes result in morphological changes and joint physicochemical evolution. We monitor the consequences of the copolymer synthesis going on as it proceeds and the resulting evolution of the molecular self-assembly. We find that this transient (or dissipative) self-assembly process leads to vesicles with diameters between 0.5 and 10's of microns. They exhibit several autonomous emergent, life-like, properties including periodic growth and partial collapse, system self-replication, together with homeostasis, competition and phototaxis. We also discuss the extension of the above by running the PISA process with oscillatory chemical reactions which are actually able to compute as a completely autonomous chemical Turing machine and control the generation and time evolution of their entrapping and replicating vesicles. Taken together these results offer insights into chemistry-based artificial life, as well as into prebiotic membrane formation en route to proto-cells and proto-life and the first living systems on the early Earth.

A new method is presented for quantifying viability, the likelihood of a system persisting. We then present an information-theoretical approach for evaluating the quality of viability-indicators, measurable quantities that co-vary with, and thus can be used to predict or influence a system's viability.