One of the hallmarks of living systems is self-replication. Mimicking nature’s ability to self-replicate would not only give more insight into biological mechanisms of self-replication but also could potentially revolutionize material science and nanotechnology. Over the past 60 y, much research, both theoretical and experimental, has been focused on understanding and realizing self-replicating systems. However, artificial systems that efficiently self-replicate remained elusive. In this paper, we construct schemes for self-replication of small clusters of isotropic particles. By manipulating the energy landscape of the process, we show how exponential replication can be achieved. As a proof of principle, we show exponential self-replication of an octahedral cluster using finite-temperature computer simulations.

Abstract

We construct schemes for self-replicating clusters of spherical particles, validated with computer simulations in a finite-temperature heat bath. Each particle has stickers uniformly distributed over its surface, and the rules for self-replication are encoded into the specificity and strength of interactions. Geometrical constraints imply that a compact cluster can copy itself only with help of a catalyst, a smaller cluster that increases the surface area to form a template. Replication efficiency requires optimizing interaction energies to destabilize all kinetic traps along the reaction pathway, as well as initiating a trigger event that specifies when the new cluster disassociates from its parent. Although there is a reasonably wide parameter range for self-replication, there is a subtle balance between the speed of the reaction, and the error rate. As a proof of principle, we construct interactions that self-replicate an octahedron, requiring a two-particle dimer for a catalyst. The resulting self-replication scheme is a hypercycle, and computer simulations confirm the exponential growth of both octahedron and catalyst replicas.