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Data-driven quantitative modeling of bacterial active nematics
- Source :
- Proceedings of the National Academy of Sciences. 116:777-785
- Publication Year :
- 2018
- Publisher :
- Proceedings of the National Academy of Sciences, 2018.
-
Abstract
- Active matter comprises individual units that convert energy into mechanical motion. In many examples, such as bacterial systems and biofilament assays, constituent units are elongated and can give rise to local nematic orientational order. Such `active nematics' systems have attracted much attention from both theorists and experimentalists. However, despite intense research efforts, data-driven quantitative modeling has not been achieved, a situation mainly due to the lack of systematic experimental data and to the large number of parameters of current models. Here we introduce a new active nematics system made of swarming filamentous bacteria. We simultaneously measure orientation and velocity fields and show that the complex spatiotemporal dynamics of our system can be quantitatively reproduced by a new type of microscopic model for active suspensions whose important parameters are all estimated from comprehensive experimental data. This provides unprecedented access to key effective parameters and mechanisms governing active nematics. Our approach is applicable to different types of dense suspensions and shows a path towards more quantitative active matter research.<br />Comment: 9 pages, 7 figures
- Subjects :
- Physics
Multidisciplinary
Statistical Mechanics (cond-mat.stat-mech)
FOS: Physical sciences
Experimental data
02 engineering and technology
Models, Theoretical
Condensed Matter - Soft Condensed Matter
021001 nanoscience & nanotechnology
01 natural sciences
Active matter
Topological defect
Data-driven
PNAS Plus
Liquid crystal
0103 physical sciences
Hydrodynamics
Soft Condensed Matter (cond-mat.soft)
010306 general physics
0210 nano-technology
Biological system
Serratia marcescens
Condensed Matter - Statistical Mechanics
Subjects
Details
- ISSN :
- 10916490 and 00278424
- Volume :
- 116
- Database :
- OpenAIRE
- Journal :
- Proceedings of the National Academy of Sciences
- Accession number :
- edsair.doi.dedup.....2430e384bc7f01aaaf23b2f15772a1dd