Experimental test of the Gallavotti-Cohen fluctuation theorem in turbulent flows

We test the fluctuation theorem from measurements in turbulent flows. We study the time fluctuations of the force acting on an obstacle, and we consider two experimental situations: the case of a von K\'arm\'an swirling flow between counter-rotating disks (VK) and the case of a wind tunnel jet. We first study the symmetries implied by the Gallavotti-Cohen fluctuation theorem (FT) on the probability density distributions of the force fluctuations; we then test the Sinai scaling. We observe that in both experiments the symmetries implied by the FT are well verified, whereas the Sinai scaling is established, as expected, only for long times

Work and heat fluctuations in two-state systems: a trajectory thermodynamics formalism

Two-state models provide phenomenological descriptions of many different systems, ranging from physics to chemistry and biology. We investigate work fluctuations in an ensemble of two-state systems driven out of equilibrium under the action of an external perturbation. We calculate the probability density P(W) that a work equal to W is exerted upon the system along a given non-equilibrium trajectory and introduce a trajectory thermodynamics formalism to quantify work fluctuations in the large-size limit. We then define a trajectory entropy S(W) that counts the number of non-equilibrium trajectories P(W)=exp(S(W)/kT) with work equal to W. A trajectory free-energy F(W) can also be defined, which has a minimum at a value of the work that has to be efficiently sampled to quantitatively test the Jarzynski equality. Within this formalism a Lagrange multiplier is also introduced, the inverse of which plays the role of a trajectory temperature. Our solution for P(W) exactly satisfies the fluctuation theorem by Crooks and allows us to investigate heat-fluctuations for a protocol that is invariant under time reversal. The heat distribution is then characterized by a Gaussian component (describing small and frequent heat exchange events) and exponential tails (describing the statistics of large deviations and rare events). For the latter, the width of the exponential tails is related to the aforementioned trajectory temperature. Finite-size effects to the large-N theory and the recovery of work distributions for finite N are also discussed. Finally, we pay particular attention to the case of magnetic nanoparticle systems under the action of a magnetic field H where work and heat fluctuations are predicted to be observable in ramping experiments in micro-SQUIDs.Comment: 28 pages, 14 figures (Latex

Characterization of Fluorinated Polymers by Atmospheric-Solid-Analysis-Probe High-Resolution Mass Spectrometry (ASAP/HRMS) Combined with Kendrick-Mass-Defect Analysis

Fluorinated polymers are a diverse and important class of polymers with unique applications. However, characterization of fluorinated polymers by conventional mass spectrometric methods is challenging because (i) their high fluorine contents make them insoluble or only sparingly soluble in most common solvents and (ii) commonly used matrices employed for MALDI do not desorb or ionize them efficiently. In this work, atmospheric-solid-analysis-probe (ASAP) high-resolution orbitrap mass spectrometry (HRMS) was used as a new tool for the molecular characterization of various fluorinated polymers, including polyvinylidene fluoride (PVDF) and fluorinated copolymers containing PVDF and chlorotrifluoroethylene (KEL-F 800) or PVDF and hexafluoropropylene (Viton A and Tecnoflon). The major peaks of the observed distributions were assigned compositions, but the high number of species required the use of an alternative method to treat such complex data. Kendrick-mass defects (KMD) were calculated on the basis of the “common-to-all” vinylidene difluoride repeating unit. By plotting the KMD as a function of the nominal Kendrick masses (NKM), specific patterns based on homologous series emerged. Kendrick maps were therefore drawn to simplify the mass spectra and provide confident peak assignments through homologous-series recognition. A specific fingerprint for each polymer has been identified, and the ability to discern the four species present in a blend through KMD analysis was demonstrated