Abstract
Living organisms and cells possess functionalities that go beyond the capabilities of traditional synthetic chemical systems, including precise spatial and temporal positioning, collective motion, and exchange of (chemical) signals, which ultimately allows for conscious thought. Underlying these functions is a process known as self-organization, through which order can emerge from disordered parts under out-of-equilibrium conditions. A better understanding of this process would not only help us comprehend the inner workings of complex biological systems, but also opens up opportunities to implement their functions in smart synthetic systems with life-like properties.
As the study of self-organization in biological systems is complicated by the sheer amount of processes that occur at the same time, a simplified, synthetic self-organizing model system may provide a more practical approach. In my PhD research, I have contributed to the development of such a system. Inspired by neurons in the brain, I set out to construct a synthetic network that is composed of simple elements (i) with direct and specific connections between them (ii) which are able to degrade and reform over time (iii).
