arXiv subjects

François Sicard

Publications and source records attributed to François Sicard.

13 recordsLinked to original sources

arXiv2026

Is Bitcoin A Hedge Against Central Banking? Evidence from AI-Driven Monetary Policy Expectations

This study investigates the transmission of monetary policy narratives to Bitcoin prices, distinguishing policy expectations from realized policy implementation. We introduce a weekly Monetary Policy Expectations (MPE) index derived from the Large Language Model (LLM)-based classification of 118,000+ market messages, providing a granular measure of hawkish and dovish monetary policy discourse. We demonstrate that changes in the MPE index provide evidence of significant linear predictive information for Bitcoin returns at short-to-medium horizons, with significant Granger causality at multiple lags. A Long Short-Term Memory (LSTM) framework combined with SHapley Additive exPlanations (SHAP) further identifies nonlinear and regime-dependent relationships between monetary-policy expectations and Bitcoin returns, indicating that Bitcoin functions as a sensitive barometer of central bank signaling. In particular, hawkish monetary-policy narratives are associated with negative price responses that are not accounted for by contemporaneous Federal Funds Rate adjustments. These findings highlight Bitcoin's structural sensitivity to global monetary discourse, establishing LLM-derived monetary-policy sentiment as a high-frequency measure of central-bank communication and as an informative leading macroeconomic indicator for the digital asset landscape.

econ.GN↗

arXiv2021

Computational design of armored nanodroplets as nanocarriers for encapsulation and release under flow conditions

Nanocarriers are nanosized materials commonly used for targeted-oriented delivery of active compounds, including antimicrobials and small-molecular drugs. They equally represent fundamental and engineering challenges since sophisticated nanocarriers must show adequate structure, stability, and function in complex ambients. Here, we report on the computational design of a distinctive class of nanocarriers, built from buckled armored nanodroplets, able to selectively encapsulate or release a probe load under specific flow conditions. Mesoscopic simulations offer detailed insight into the interplay between the characteristics of laden surface coverage and evolution of the droplet morphology. First, we describe in detail the formation of \textit{pocket-like} structures in Pickering emulsion nanodroplets and their stability under external flow. Then we use that knowledge to test the capacity of these emulsion-based pockets to yield flow-assisted encapsulation or expulsion of a probe load. Finally, the rheological properties of our model carrier are put into perspective with those of delivery systems employed in pharmaceutical and cosmetic technology.

cond-mat.soft↗

arXiv2020

Role of Structural Rigidity and Collective Behaviour in the Molecular Design of Gas Hydrates Anti-Agglomerants

Antiagglomerants (AAs) are surface active molecules widely used in the rubber and petroleum industry, among others. In the petroleum industry, it is believed that AAs strongly adsorb to the surface of hydrate particles to prevent the growth of clathrate hydrate within oil pipelines. Small changes in their molecular structures can strongly affect the thermodynamic and kinetic stability of the system as a whole. Here we employ molecular dynamics simulations to study the interplay between the modification of the molecular structure, rigidity and collective effects of AAs designed to prevent hydrate agglomeration in the conditions encountered in rocking cell experiments. The AAs are surface-active compounds with a complex hydrophilic head and three hydrophobic tails whose structural rigidity is enhanced with the attachement of a simple aromatic group. We observe that the aromatic group can positively or negatively affect the performance of the AAs, depending on its location along the hydrophobic tail. Our approach is based on first quantifying the molecular mechanisms responsible for the macroscopic performance. Although the mechanisms at play depend on the application, the methodology implemented could be applicable to other high-tech industries, where the agglomeration of small particles must be controlled.

cond-mat.soft↗

arXiv2019

Nanoparticles actively fragment armored droplets

Understanding the complexity of fragmentation processes is essential for regulating intercellular communication in mechanistic biology and developing novel bottom-up approaches in a large range of multiphase flow processes. In this context, self-fragmentation proceeds without any external mechanical energy input allowing one to create efficiently micro- and nanodroplets. Here we examine self-fragmentation in emulsion nanodroplets stabilized by solid particles with different surface features. Mesoscopic modelling and accelerated dynamics simulations allow us to overcome the limitations of atomistic simulations and offer detailed insight into the interplay between the evolution of the droplet shape and the particle finite-sized effects at the interface. We show that finite-sized nanoparticles play an active role in the necking breakup, behaving like nano-scale razors, and affect strongly the thermodynamic properties of the system. The role played by the particles during self-fragmentation might be of relevance to multifunctional biomaterial design and tuning of signaling pathways in mechanistic biology.

cond-mat.mes-hall↗

arXiv2018

Control of DNA denaturation bubble nucleation to advance nano-biosensing

In the demanding biosensing environment, improving selection efficiency strategies has become an issue of great significance. DNA minicircles containing between 200 and 400 base-pairs, also named microDNA, are representative of the supercoiled DNA loops found in nature. Their short size makes them extremely susceptible to writhe and twist, which is known to play a central role in DNA denaturation. We investigate minicircle lengths and superhelical densities that induce DNA denaturation bubbles of nanometer size and control well-defined long-life. Mesoscopic modeling and accelerated dynamics simulations allow us to study accurately the thermodynamic and dynamical properties associated with the nucleation and closure mechanisms of long-lived denaturation bubbles. Our results pave the way for new types of DNA biosensors with enhanced selectivity for specific DNA binding proteins.

physics.bio-ph↗

arXiv2018

Emergent Properties of Antiagglomerant Films Control Methane Transport: Implications for Hydrate Management

The relation between collective properties and performance of antiagglomerants (AAs) used in hydrate management is handled using molecular dynamics simulations and enhanced sampling techniques. A thin film of AAs adsorbed at the interface between one flat sII methane hydrate substrate and a fluid hydrocarbon mixture containing methane and n-dodecane is studied. The AA considered is a surface-active compound with a complex hydrophilic head that contains both amide and tertiary ammonium cation groups and hydrophobic tails. At sufficiently high AA density, the interplay between the surfactant layer and the liquid hydrocarbon excludes methane from the interfacial region. In this scenario, we combine metadynamics and umbrella sampling frameworks to study accurately the free-energy landscape and the equilibrium rates associated with the transport of one methane molecule across the AA film. We observe that local configurational changes of the liquid hydrocarbon packed within the AA film are associated with high free-energy barriers for methane transport. The time scales estimated for the transport of methane across the AA film can be, in some cases, comparable to those reported in the literature for the growth of the hydrates, suggesting that one possible mechanism by which AAs delay the formation of hydrate plugs could be providing a barrier to methane transport. Considering the interplay between structural design and collective properties of AAs might be of relevance to improve their performance in flow assurance.

cond-mat.soft↗

arXiv2018

Computing Transition Rates for Rare Event: When Kramers Theory meets Free Energy Landscape

Computing reactive trajectories and free energy (FE) landscapes associated to rare event kinetics is key to understanding the dynamics of complex systems. The analysis of the FE surface on which the underlying dynamics takes place has become central to compute transition rates. In the overdamped limit, most often encountered in biophysics and soft condensed matter, the Kramers' Theory (KT) has proved to be quite successful in recovering correct kinetics. However, the additional calculation to obtain rate constants in complex systems where configurational entropy is competing with energy is still challenging conceptually and computationally. Building on KT and the metadynamics framework, the rate is expressed in terms of the height of the FE barrier measured along the minimum FE path and an auxiliary measure of the configurational entropy. We apply the formalism to two different problems where our approach shows good agreement with simulations and experiments and can present significant improvement over the standard KT.

cond-mat.stat-mech↗

arXiv2017

Buckling in Armored Droplets

The issue of the buckling mechanism in droplets stabilized by solid particles (armored droplets) is tackled at a mesoscopic level using dissipative particle dynamics simulations. We consider spherical water droplet in a decane solvent coated with nanoparticle monolayers of two different types: Janus and homogeneous. The chosen particles yield comparable initial three-phase contact angles, chosen to maximize the adsorption energy at the interface. We study the interplay between the evolution of droplet shape, layering of the particles, and their distribution at the interface when the volume of the droplets is reduced. We show that Janus particles affect strongly the shape of the droplet with the formation of a crater-like depression. This evolution is actively controlled by a close-packed particle monolayer at the curved interface. On the contrary, homogeneous particles follow passively the volume reduction of the droplet, whose shape does not deviate too much from spherical, even when a nanoparticle monolayer/bilayer transition is detected at the interface. We discuss how these buckled armored droplets might be of relevance in various applications including potential drug delivery systems and biomimetic design of functional surfaces.

cond-mat.soft↗

arXiv2016

Numerical analysis of Pickering emulsion stability: insights from ABMD simulations

The issue of the stability of Pickering emulsions is tackled at a mesoscopic level using dissipative particle dynamics simulations within the Adiabatic Biased Molecular Dynamics framework. We consider the early stage of the coalescence process between two spherical water droplets in decane solvent. The droplets are stabilized by Janus nanoparticles of different shapes (spherical and ellipsoidal) with different three-phase contact angles. Given a sufficiently dense layer of particles on the droplets, we show that the stabilization mechanism strongly depends on the collision speed. This is consistent with a coalescence mechanism governed by the rheology of the interfacial region. When the system is forced to coalesce sufficiently slowly, we investigate at a mesoscopic level how the ability of the nanoparticles to stabilize Pickering emulsions is discriminated by nanoparticle mobility and the associated caging effect. These properties are both related to the interparticle interaction and the hydrodynamic resistance in the liquid film between the approaching interfaces.

cond-mat.soft↗

arXiv2015

DNA denaturation bubbles: free-energy landscape and nucleation/closure rates

The issue of the nucleation and slow closure mechanisms of non superhelical stress-induced denaturation bubbles in DNA is tackled using coarse-grained MetaDynamics and Brownian simulations. A minimal mesoscopic model is used where the double helix is made of two interacting bead-spring rotating strands with a prescribed torsional modulus in the duplex state. We demonstrate that timescales for the nucleation (resp. closure) of an approximately 10 base-pair bubble, in agreement with experiments, are associated with the crossing of a free-energy barrier of $22~k_{\rm B}T$ (resp. $13~k_{\rm B}T$) at room temperature $T$. MetaDynamics allows us to reconstruct accurately the free-energy landscape, to show that the free-energy barriers come from the difference in torsional energy between the bubble and duplex states, and thus to highlight the limiting step, a collective twisting, that controls the nucleation/closure mechanism, and to access opening time scales on the millisecond range. Contrary to small breathing bubbles, these more than 4~base-pair bubbles are of biological relevance, for example when a preexisting state of denaturation is required by specific DNA-binding proteins.

cond-mat.soft↗

arXiv2014

Scaling quasi-stationary states in long range systems with dissipation

Hamiltonian systems with long-range interactions give rise to long lived out of equilibrium macroscopic states, so-called quasi-stationary states. We show here that, in a suitably generalized form, this result remains valid for many such systems in the presence of dissipation. Using an appropriate mean-field kinetic description, we show that models with dissipation due to a viscous damping or due to inelastic collisions admit "scaling quasi-stationary states", i.e., states which are quasi-stationary in rescaled variables. A numerical study of one dimensional self-gravitating systems confirms both the relevance of these solutions, and gives indications of their regime of validity in line with theoretical predictions. We underline that the velocity distributions never show any tendency to evolve towards a Maxwell-Boltzmann form.

cond-mat.stat-mech↗

arXiv2013

Exponents of non-linear clustering in scale-free one dimensional cosmological simulations

One dimensional versions of cosmological N-body simulations have been shown to share many qualitative behaviours of the three dimensional problem. They can resolve a large range of time and length scales, and admit exact numerical integration. We use such models to study how non-linear clustering depends on initial conditions and cosmology. More specifically, we consider a family of models which, like the 3D EdS model, lead for power-law initial conditions to self-similar clustering characterized in the strongly non-linear regime by power-law behaviour of the two point correlation function. We study how the corresponding exponent γdepends on the initial conditions, characterized by the exponent n of the power spectrum of initial fluctuations, and on a single parameter κcontrolling the rate of expansion. The space of initial conditions/cosmology divides very clearly into two parts: (1) a region in which γdepends strongly on both n and κand where it agrees very well with a simple generalisation of the so-called stable clustering hypothesis in three dimensions, and (2) a region in which γis more or less independent of both the spectrum and the expansion of the universe. We explain the observed location of the boundary in (n, κ) space dividing the "stable clustering" region from the "universal" region. We compare and contrast our findings to results in three dimensions, and discuss in particular the light they may throw on the question of "universality" of non-linear clustering in this context.

astro-ph.CO↗

arXiv2011

Non-linear gravitational clustering of cold matter in an expanding universe: indications from 1D toy models

Studies of a class of infinite one dimensional self-gravitating systems have highlighted that, on the one hand, the spatial clustering which develops may have scale invariant (fractal) properties, and, on the other, that they display "self-similar" properties in their temporal evolution. The relevance of these results to three dimensional cosmological simulations has remained unclear. We show here that the measured exponents characterizing the scale-invariant non-linear clustering are in excellent agreement with those derived from an appropriately generalized "stable-clustering" hypothesis. Further an analysis in terms of "halos" selected with a friend-of-friend algorithm reveals that such structures are, statistically, virialized across the range of scales corresponding to scale-invariance. Thus the strongly non-linear clustering in these models is accurately described as a virialized fractal structure, very much in line with the "clustering hierarchy" which Peebles originally envisaged qualitatively as associated with stable clustering. If transposed to three dimensions these results would imply, notably, that cold dark matter halos (or even subhalos) are 1) not well modeled as smooth objects, and 2) that the supposed "universality" of their profiles is, like apparent smoothness, an artefact of poor numerical resolution.

astro-ph.CO↗