Semantic self-assembly in a meaning-less energy landscape far from equilibrium (seminar on Zoom)
Pablo Sartori (Gulbenkian Institute for Molecular Medicine)
Due to an illness from the speaker, the seminar has been converted to a remote format – see Zoom link below. Some of us will gather in the seminar room to watch. Feel free to join us.
Like the letters in the alphabet forming words, reusing components is an efficient strategy for assembling a large number of target structures from heterogeneous mixture of components. Examples range from synthetic DNA origami to proteins self-assembling into complexes. The standard self-assembly paradigm views target structures as free-energy minima of a mixture. While this is an appealing picture, at high speed structures may be kinetically trapped in local minima, reducing self-assembly accuracy. How then can high speed, high accuracy, and combinatorial usage of components coexist? We propose to reconcile these three concepts not by avoiding kinetic traps, but by exploiting them to encode target structures. This can be achieved by sculpting the kinetic pathways of the mixture, instead of its free-energy landscape. In other words, targets structures with semantic value are not enconded in the energy landscape, but rather on the kinetics. We formalize these ideas in a minimal toy model, for which we analytically estimate the encoding capacity and kinetic characteristics, in agreement with simulations. Our results may be generalized to other soft-matter systems capable of computation, such as liquid mixtures or elastic networks, and pave the way for high-dimensional information processing far from equilibrium.
Time: May 16, 2025 11:00 AM Paris
https://cnrs.zoom.us/j/93701191981?pwd=abTkbFq72axppbR2pHUgIumGG6Ojk0.1
Meeting ID: 937 0119 1981
Passcode: Ufwf5x