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Comtet J.,CNRS ENS Statistical Physics Laboratory
Nature Materials | Year: 2017

Room-temperature ionic liquids (RTILs) are new materials with fundamental importance for energy storage and active lubrication. They are unusual liquids, which challenge the classical frameworks of electrolytes, whose behaviour at electrified interfaces remains elusive, with exotic responses relevant to their electrochemical activity. Using tuning-fork-based atomic force microscope nanorheological measurements, we explore here the properties of confined RTILs, unveiling a dramatic change of the RTIL towards a solid-like phase below a threshold thickness, pointing to capillary freezing in confinement. This threshold is related to the metallic nature of the confining materials, with more metallic surfaces facilitating freezing. This behaviour is interpreted in terms of the shift of the freezing transition, taking into account the influence of the electronic screening on RTIL wetting of the confining surfaces. Our findings provide fresh views on the properties of confined RTIL with implications for their properties inside nanoporous metallic structures, and suggests applications to tune nanoscale lubrication with phase-changing RTILs, by varying the nature and patterning of the substrate, and application of active polarization. © 2017 Nature Publishing Group


Cocco S.,CNRS ENS Statistical Physics Laboratory | Monasson R.,CNRS Physics Laboratory | Weigt M.,University Pierre and Marie Curie | Weigt M.,Human Genetics Foundation
PLoS Computational Biology | Year: 2013

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant 'patterns' of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. © 2013 Cocco et al.


Mora T.,Princeton University | Mora T.,CNRS ENS Statistical Physics Laboratory | Bialek W.,Princeton University
Journal of Statistical Physics | Year: 2011

Many of life's most fascinating phenomena emerge from interactions among many elements-many amino acids determine the structure of a single protein, many genes determine the fate of a cell, many neurons are involved in shaping our thoughts and memories. Physicists have long hoped that these collective behaviors could be described using the ideas and methods of statistical mechanics. In the past few years, new, larger scale experiments have made it possible to construct statistical mechanics models of biological systems directly from real data. We review the surprising successes of this "inverse" approach, using examples from families of proteins, networks of neurons, and flocks of birds. Remarkably, in all these cases the models that emerge from the data are poised near a very special point in their parameter space-a critical point. This suggests there may be some deeper theoretical principle behind the behavior of these diverse systems. © 2011 Springer Science+Business Media, LLC.


Ciarletta P.,CNRS Jean Le Rond d'Alembert Institute | Ben Amar M.,CNRS ENS Statistical Physics Laboratory
Mechanics Research Communications | Year: 2012

Complex networks of finger-like protrusions characterize the dermal-epidermal junction of human skin. Although formed during the foetal development, such dermal papillae evolve in adulthood, often in response to a pathological condition. The aim of this work is to investigate the emergence of biaxial papillary networks in skin from a mechanical perspective. For this purpose, we define a biomechanical model taking into account the volumetric growth and the microstructural properties of the dermis and the epidermis. A scalar stream function is introduced to generate incompressible transformations, and used to define a variational formulation of the boundary value elastic problem. We demonstrate that incompatible growth of the layers can induce a bifurcation of the elastic stability driving the formation of dermal papillae. Such an interfacial instability is found to depend both on the geometrical constraints and on the mechanical properties of the skin components. The results provide a mechanical interpretation of skin morphogenesis, with possible applications for micropattern fabrication in soft layered materials. © 2012 Elsevier Ltd. All rights reserved.


Maimbourg T.,Ecole Normale Superieure de Paris | Kurchan J.,CNRS ENS Statistical Physics Laboratory | Zamponi F.,Ecole Normale Superieure de Paris
Physical Review Letters | Year: 2016

We obtain analytic expressions for the time correlation functions of a liquid of spherical particles, exact in the limit of high dimensions d. The derivation is long but straightforward: a dynamic virial expansion for which only the first two terms survive, followed by a change to generalized spherical coordinates in the dynamic variables leading to saddle-point evaluation of integrals for large d. The problem is, thus, mapped onto a one-dimensional diffusion in a perturbed harmonic potential with colored noise. At high density, an ergodicity-breaking glass transition is found. In this regime, our results agree with thermodynamics, consistently with the general random first order transition scenario. The glass transition density is higher than the best known lower bound for hard sphere packings in large d. Because our calculation is, if not rigorous, elementary, an improvement in the bound for sphere packings in large dimensions is at hand. © 2016 American Physical Society.


Charbonneau P.,Duke University | Charbonneau P.,Ecole Normale Superieure de Paris | Kurchan J.,CNRS ENS Statistical Physics Laboratory | Parisi G.,University of Rome La Sapienza | And 3 more authors.
Nature Communications | Year: 2014

Glasses are amorphous solids whose constituent particles are caged by their neighbours and thus cannot flow. This sluggishness is often ascribed to the free energy landscape containing multiple minima (basins) separated by high barriers. Here we show, using theory and numerical simulation, that the landscape is much rougher than is classically assumed. Deep in the glass, it undergoes a â roughness transitionâ €™ to fractal basins, which brings about isostaticity and marginal stability on approaching jamming. Critical exponents for the basin width, the weak force distribution and the spatial spread of quasi-contacts near jamming can be analytically determined. Their value is found to be compatible with numerical observations. This advance incorporates the jamming transition of granular materials into the framework of glass theory. Because temperature and pressure control what features of the landscape are experienced, glass mechanics and transport are expected to reflect the features of the topology we discuss here. © 2014 Macmillan Publishers Limited. All rights reserved.


Alexakis A.,CNRS ENS Statistical Physics Laboratory
Physical Review Letters | Year: 2013

High Reynolds number magnetohydrodynamic turbulence in the presence of zero-flux large-scale magnetic fields is investigated as a function of the magnetic field strength. For a variety of flow configurations, the energy dissipation rate Ïμ follows the scaling Urms3/ℓ even when the large-scale magnetic field energy is twenty times larger than the kinetic energy. A further increase of the magnetic energy showed a transition to the Urms2Brms/ℓ scaling implying that magnetic shear becomes more efficient at this point at cascading the energy than the velocity fluctuations. Strongly helical configurations form nonturbulent helicity condensates that deviate from these scalings. Weak turbulence scaling was absent from the investigation. Finally, the magnetic energy spectra support the Kolmogorov spectrum k-5/3 while kinetic energy spectra are closer to the Iroshnikov-Kraichnan spectrum k-3/2 as observed in the solar wind. © 2013 American Physical Society.


Dervaux J.,CNRS ENS Statistical Physics Laboratory | Amar M.B.,CNRS ENS Statistical Physics Laboratory
Annual Review of Condensed Matter Physics | Year: 2012

Although the study of gels undoubtedly takes its roots within the field of physicochemistry, the interest in gels has flourished and they have progressively become an important object in the study of the mechanics of polymeric materials and volumetric growth, raising some fascinating problems, some of them remaining unsolved. Because gels are multiphase objects, their study represents an important step in the understanding of the mechanics of complex soft matter as well as for the process of shape generation in biological bodies. The scope of this article is to review the understanding we have of the mechanical behavior of gels, with a strong focus on the development of instabilities in swelling gels. Copyright © 2012 by Annual Reviews. All rights reserved.


Alexakis A.,CNRS ENS Statistical Physics Laboratory
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2011

The magnetohydrodynamic (MHD) equations in the presence of a guiding magnetic field are investigated by means of direct numerical simulations. The basis of the investigation consists of nine runs forced at the small scales. The results demonstrate that for a large enough uniform magnetic field the large scale flow behaves as a two-dimensional (2D) (non-MHD) fluid exhibiting an inverse cascade of energy in the direction perpendicular to the magnetic field, while the small scales behave like a three-dimensional (3D) MHD fluid cascading the energy forwards. The amplitude of the inverse cascade is sensitive to the magnetic field amplitude, the domain size, the forcing mechanism, and the forcing scale. All these dependences are demonstrated by the varying parameters of the simulations. Furthermore, in the case that the system is forced anisotropically in the small parallel scales an inverse cascade in the parallel direction is observed that is feeding the 2D modes k=0. © 2011 American Physical Society.


Alexakis A.,CNRS ENS Statistical Physics Laboratory
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2011

The growth rate of the dynamo instability as a function of the magnetic Reynolds number RM is investigated by means of numerical simulations for the family of the Arnold-Beltrami-Childress (ABC) flows and for two different forcing scales. For the ABC flows that are driven at the largest available length scale, it is found that, as the magnetic Reynolds number is increased: (a) The flow that results first in a dynamo is the 212-dimensional flow for which A=B and C=0 (and all permutations). (b) The second type of flow that results in a dynamo is the one for which A=B 2C/5 (and permutations). (c) The most symmetric flow, A=B=C, is the third type of flow that results in a dynamo. (d) As RM is increased, the A=B=C flow stops being a dynamo and transitions from a local maximum to a third-order saddle point. (e) At larger RM, the A=B=C flow reestablishes itself as a dynamo but remains a saddle point. (f) At the largest examined R M, the growth rate of the 212-dimensional flows starts to decay, the A=B=C flow comes close to a local maximum again, and the flow A=B 2C/5 (and permutations) results in the fastest dynamo with growth rate γ 0.12 at the largest examined RM. For the ABC flows that are driven at the second largest available length scale, it is found that (a) the 212-dimensional flows A=B,C=0 (and permutations) are again the first flows that result in a dynamo with a decreased onset. (b) The most symmetric flow, A=B=C, is the second type of flow that results in a dynamo. It is, and it remains, a local maximum. (c) At larger RM, the flow A=B 2C/5 (and permutations) appears as the third type of flow that results in a dynamo. As RM is increased, it becomes the flow with the largest growth rate. The growth rates appear to have some correlation with the Lyapunov exponents, but constructive refolding of the field lines appears equally important in determining the fastest dynamo flow. © 2011 American Physical Society.

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