Hydrodynamics of soft active matter
By M. Cristina Marchetti, J. Joanny, S. Ramaswamy, T. Liverpool, J. Prost, M. Rao, R. Simha. 2013
3,304 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Cell Biology, Condensed Matter Physics
View Paper: https://www.semanticscholar.org/paper/e4fd390b19b2b7c30cf09af0657c051527cc1dbb
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- M. Cristina Marchetti
- 'Etienne Fodor
- Gerhard Gompper
- Roland G. Winkler
- J. Elgeti
- Y. Fily
- M. E. Cates
- David Yllanes
In Cell Biology
- C. Broedersz
- Ulrich S. Schwarz
- Shmuel Safran
- M. Cristina Marchetti
- S. Ramaswamy
- L. Giomi
- F. MacKintosh
- 'Etienne Fodor
In Condensed Matter Physics
- M. Cristina Marchetti
- Roland G. Winkler
- Gerhard Gompper
- M. E. Cates
- J. Elgeti
- Hartmut Löwen
- Charles Reichhardt
- 'Etienne Fodor
Citations in the corpus
- Minimal model of active colloids highlights the role of mechanical interactions in controlling the emergent behavior of active matter (2015, background): “and therefore suppressing the self-trapping responsible for cluster formation [58, 59]. On the other hand, strong clustering is often observed in active systems even in the presence of aligning rules [3], indicating that more work needs to be done to understand the eect of aligning torques on the MI”
- Modeling semiflexible polymer networks (2014, background): “V.C.1, but we would point the interested reader to 22 recent reviews on the subject (Brangwynne et al., 2008; MacKintosh and Schmidt, 2010; Marchetti et al., 2013).”
- Flow interactions lead to orderly formations of flapping wings in forward flight (2016, background): “From a physics perspective, collectively locomoting ensembles have been viewed as states of active matter [11], and to date efforts have focused on low-Reynolds-number systems in which the dynamics of microscopic constituents are coupled through viscous flows [12].”
- Irreversibility in Active Matter Systems: Fluctuation Theorem and Mutual Information (2018, background): “Active particle systems consist of individual entities (“particles”) which have the ability to perform motion by consuming energy from the environment and converting it into a self-propulsion drive [1–7].”
- Physics of adherent cells (2013, background): “This indeed is the time regime in which the CSK is modeled (Julicher et al., 2007; Kruse et al., 2004; Liverpool and Marchetti, 2003; Marchetti et al., 2013) as an active gel that flows in response to internal forces generated by cell activity which is fueled by energy consumption.”
- Liquid-liquid phase separation in biology. (2014, background): “(For more information on active liquids, we refer the reader to Kruse et al. 2004, 2005; Marchetti et al. 2013; Ramaswamy 2010, and references therein.)”
- Pressure is not a state function for generic active fluids (2014, background): “This applies even to oriented fluids (without positional order), such as nematic liquid crystals [37], but breaks down for active nematics [3].”
- The statistical physics of active matter: From self-catalytic colloids to living cells (2017, background): “A large number of studies were dedicated to understand the nature of the flocking transition and how it is controlled by the density and noise in such systems [1,2].”
- Assembly and phase transitions of colloidal crystals (2016, background): “‘Active matter’ contains self-driven units by converting stored or ambient energy into systematic movement, and includes animal groups, energy-consuming polymers and active colloids [64].”
- Temperature in and out of equilibrium: A review of concepts, tools and attempts (2017, background): “This ‘‘middle world’’ includes several interesting topics, such as macromolecules (DNA, proteins and molecular motors) [59], colloidal suspensions [60], granular media [61] and active matter [62], just to name a few.”
- Nonequilibrium physics in biology (2019, methodology): “Another example lies in the spatial organization of the neurons in the brain, where the relevant dynamic quantities depend on space (Bray, 2001; Dayan and Abbott, 2001; Getling, 1998; Jaeger et al., 2004; Marchetti et al., 2013a).”