Unknown

Dataset Information

0

Active matter logic for autonomous microfluidics.


ABSTRACT: Chemically or optically powered active matter plays an increasingly important role in materials design, but its computational potential has yet to be explored systematically. The competition between energy consumption and dissipation imposes stringent physical constraints on the information transport in active flow networks, facilitating global optimization strategies that are not well understood. Here, we combine insights from recent microbial experiments with concepts from lattice-field theory and non-equilibrium statistical mechanics to introduce a generic theoretical framework for active matter logic. Highlighting conceptual differences with classical and quantum computation, we demonstrate how the inherent non-locality of incompressible active flow networks can be utilized to construct universal logical operations, Fredkin gates and memory storage in set-reset latches through the synchronized self-organization of many individual network components. Our work lays the conceptual foundation for developing autonomous microfluidic transport devices driven by bacterial fluids, active liquid crystals or chemically engineered motile colloids.

SUBMITTER: Woodhouse FG 

PROVIDER: S-EPMC5414041 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Active matter logic for autonomous microfluidics.

Woodhouse Francis G FG   Dunkel Jörn J  

Nature communications 20170425


Chemically or optically powered active matter plays an increasingly important role in materials design, but its computational potential has yet to be explored systematically. The competition between energy consumption and dissipation imposes stringent physical constraints on the information transport in active flow networks, facilitating global optimization strategies that are not well understood. Here, we combine insights from recent microbial experiments with concepts from lattice-field theory  ...[more]

Similar Datasets

| S-EPMC7283233 | biostudies-literature
| S-EPMC6328580 | biostudies-literature
| S-EPMC3935767 | biostudies-literature
| S-EPMC8865799 | biostudies-literature
| S-EPMC4942321 | biostudies-literature
| S-EPMC5565432 | biostudies-other
| S-EPMC11003918 | biostudies-literature
| S-EPMC6646586 | biostudies-literature
| S-EPMC9700843 | biostudies-literature
| S-EPMC6924514 | biostudies-literature