Self-replication is a ubiquitous process in organisms. Understanding the key ingredients of self-replication is critical for developing self-sustaining systems in the laboratory. Moreover, finding the optimal conditions to generate accurate replicas and adequate output can accelerate industrial processes enormously. Here, we propose a scheme for self-replication where asymmetric interactions in colloids are used to find optimal self-replication conditions by controlling the input of energy. We generalize a recently developed kinetic Monte Carlo algorithm to treat both translational and rotational motions of Brownian anisotropic colloids. We report two main findings from our simulations: first, by fine tuning the particle interactions, highly accurate self-replication is achievable with a moderate sacrifice of reaction speed. Second, with the introduction of energy cycling to enable periodic assembly/disassembly of the system's components the replicator population grows exponentially. The exponential growth constant is a non-monotonic function of the period of the pulsed energy delivery.
ASJC Scopus subject areas
- Condensed Matter Physics