globalchange  > 气候变化与战略
DOI: 10.1073/pnas.1812570116
论文题名:
Data-driven quantitative modeling of bacterial active nematics
作者: Li H.; Shi X.-Q.; Huang M.; Chen X.; Xiao M.; Liu C.; Chaté H.; Zhang H.P.
刊名: Proceedings of the National Academy of Sciences of the United States of America
ISSN: 0027-8424
出版年: 2019
卷: 116, 期:3
起始页码: 777
结束页码: 785
语种: 英语
英文关键词: Active nematics ; Bacteria collective motion ; Quantitative modeling ; Topological defects
Scopus关键词: article ; motion ; quantitative analysis ; suspension ; hydrodynamics ; Serratia marcescens ; theoretical model ; Hydrodynamics ; Models, Theoretical ; Serratia marcescens
英文摘要: 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 an 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 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 toward more quantitative active matter research. © 2019 National Academy of Sciences. All Rights Reserved.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/163575
Appears in Collections:气候变化与战略

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作者单位: Li, H., School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240, China, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China; Shi, X.-Q., Center for Soft Condensed Matter Physics and, Interdisciplinary Research and School of Physical Science and Technology, Soochow University, Suzhou, 215006, China, Service de Physique de l’Etat Condensé, Commissariat à l’Energie Atomique (CEA), CNRS, Université Paris-Saclay, CEA-Saclay, Gif-sur-Yvette, 91191, France; Huang, M., School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240, China, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China; Chen, X., School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240, China, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China; Xiao, M., Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Liu, C., Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Chaté, H., Service de Physique de l’Etat Condensé, Commissariat à l’Energie Atomique (CEA), CNRS, Université Paris-Saclay, CEA-Saclay, Gif-sur-Yvette, 91191, France, Computational Science Research Center, Beijing, 100094, China; Zhang, H.P., School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240, China, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, 200240, China, Collaborative Innovation Center of Advanced Microstructures, Nanjing, 210093, China

Recommended Citation:
Li H.,Shi X.-Q.,Huang M.,et al. Data-driven quantitative modeling of bacterial active nematics[J]. Proceedings of the National Academy of Sciences of the United States of America,2019-01-01,116(3)
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