Datensatz #880998

Ph.D.

Phase map of dynamic, adaptive colloidal crystals far from equilibrium

Coordinator	BILKENT UNIVERSITESI ULUSAL NANOTEKNOLOJI ARASTIRMA MERKEZI - UNAM
Grant period	2019-11-01 - 2024-10-31
Funding body	European Union
Call number	ERC-2019-STG
Grant number	853387
Identifier	G:(EU-Grant)853387

Note: We recently reported the first observation of dynamic adaptive colloidal crystals exhibiting characteristics similar to those commonly associated with living organisms: self-replication, self-healing, adaptation, competition, motility. Here, I propose to do the first experiments to clarify precisely how dynamic adaptive behavior arises far from equilibrium and how to control it. The key to both is a fundamental question at the heart of condensed matter, statistical and nonlinear physics: When far from equilibrium, in the presence of fluctuations and faced with multiple steady states with small energy differences, how does a system evolve? Specifically, my objectives are (1) to form crystals with periodic and aperiodic patterns, e.g. 2D Bravais lattices, quasicrystals, using passive identical particles, (2) to quantify their formation energies through the effective temperature of Brownian particles, (3) to identify the conditions for emergence and control of adaptive behavior. Then, I will draw a complete phase map of these dynamic adaptive colloidal crystals using fitness landscapes to characterize each pattern. I will further ask to what extent this control is extendable down to the few-nm scale, where fluctuations are even stronger and if and how these findings change when using nonidentical, in size or shape, but still passive particles. My system comprises quasi-2D-confined pure-polystyrene 500-nm spheres suspended in water. An energy flux to drive the system far from equilibrium and sustain it there is supplied by an ultrafast laser. My method exploits only three physical tenets, nonlinearity, fluctuations and positive/negative feedback mechanisms acting on identical passive particles, yet generates extremely rich emergent dynamics. A full understanding of how such dynamics arise from so few basic ingredients will advance our understanding of complex systems in addition to numerous practical applications to self-assembly, microfluidics, nanoscience and biology.

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Datensatz erzeugt am 2020-09-04, letzte Änderung am 2023-02-07

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