arXiv subjects

Fabien Brieuc

Publications and source records attributed to Fabien Brieuc.

11 recordsLinked to original sources

arXiv2025

Probing laser-driven surface and subsurface dynamics via grazing-incidence XFEL scattering and diffraction

We demonstrate a grazing-incidence x-ray platform that simultaneously records time-resolved grazing-incidence small-angle x-ray scattering (GISAXS) and grazing-incidence x-ray diffraction (GID) from a femtosecond laser-irradiated gold film above the melting threshold, with picosecond resolution at an x-ray free-electron laser (XFEL). By tuning the x-ray incidence angle, the probe depth is set to tens of nanometers, enabling depth-selective sensitivity to near-surface dynamics. GISAXS resolves ultrafast changes in surface nanomorphology (correlation length, roughness), while GID quantifies subsurface lattice compression, grain orientation, melting, and recrystallization. The approach overcomes photon-flux limitations of synchrotron grazing-incidence geometries and provides stringent, time-resolved benchmarks for complex theoretical models of ultrafast laser-matter interaction and warm dense matter. Looking ahead, the same depth-selective methodology is well suited to inertial confinement fusion (ICF): it can visualize buried-interface perturbations and interfacial thermal resistance on micron to sub-micron scales that affect instability seeding and burn propagation.

physics.optics↗

arXiv2025

Abinit 2025: New Capabilities for the Predictive Modeling of Solids and Nanomaterials

Abinit is a widely used scientific software package implementing density functional theory and many related functionalities for excited states and response properties. This paper presents the novel features and capabilities, both technical and scientific, which have been implemented over the past 5 years. This evolution occurred in the context of evolving hardware platforms, high-throughput calculation campaigns, and the growing use of machine learning to predict properties based on databases of first principles results. We present new methodologies for ground states with constrained charge, spin or temperature; for density functional perturbation theory extensions to flexoelectricity and polarons; and for excited states in many-body frameworks including GW, dynamical mean field theory, and coupled cluster. Technical advances have extended abinit high-performance execution to graphical processing units and intensive parallelism. Second principles methods build effective models on top of first principles results to scale up in length and time scales. Finally, workflows have been developed in different community frameworks to automate \abinit calculations and enable users to simulate hundreds or thousands of materials in controlled and reproducible conditions.

cond-mat.mtrl-sci↗

arXiv2025

Unveiling temperature and phase boundaries in laser-driven shocked and released copper: insights from ultra-fast X-ray Absorption Spectroscopy up to 300 GPa

Cu is an ubiquitous material used in industry for its great thermal and electrical properties. Studying the high-pressure high temperature properties of copper (Cu) is relevant for nuclear fusion research as projectiles and flyers used in hypervelocity impacts are generally made of copper, where it is used also in the design of the nuclear fusion targets. Recently, a solid (fcc)-solid (bcc) phase transition has been detected in shock compressed Cu with X-Ray Diffraction. Here, we present a study on shock compressed copper up to 300 GPa and 7100 K probed by single pulse (100 ps FWHM) X-ray Absorption Spectroscopy (XAS). Based on the analysis of the XAS spectra, we provide structural identification and bulk temperature measurements along the Hugoniot up to the melting. The collection of XAS spectra under release conditions, i.e. at later times than the breakout time of the shock wave, helped constraining the experimental fcc-bcc and solid-liquid phase boundaries. In particular, we report the first bulk temperature measurement in shock compressed copper on the melting plateau located between 237(40) GPa and 5750(1130) K and 261 (27) GPa and 6240 (1155) K and on liquid copper at 300 GPa and 7100 K.

cond-mat.mtrl-sci↗

arXiv2023

Manifestations of Local Supersolidity of $^{4}$He around a Charged Molecular Impurity

A frozen, solid helium core, dubbed snowball, is typically observed around cations in liquid helium. Here we discover, using path integral simulations, that around a cationic molecular impurity, protonated methane, the $^4$He atoms are indeed strongly localized akin to snowballs but still participate in vivid bosonic exchange induced by the ro-vibrational motion of the impurity. Such combination of solid-like order with pronounced superfluid response in the first helium shell indicates that manifestations of local supersolid behavior of $^4$He can be induced -- and probed experimentally -- by charged molecules.

physics.chem-ph↗

arXiv2022

State-resolved infrared spectrum of the protonated water dimer: Revisiting the characteristic proton transfer doublet peak

The infrared (IR) spectra of protonated water clusters encode precise information on the dynamics and structure of the hydrated proton. However, the strong anharmonic coupling and quantum effects of these elusive species remain puzzling up to the present day. Here, we report unequivocal evidence that the interplay between the proton transfer and the water wagging motions in the protonated water dimer (Zundel ion) giving rise to the characteristic doublet peak is both more complex and more sensitive to subtle energetic changes than previously thought. In particular, hitherto overlooked low-intensity satellite peaks in the experimental spectrum are now unveiled and mechanistically assigned. Our findings rely on the comparison of IR spectra obtained using two highly accurate potential energy surfaces in conjunction with highly accurate state-resolved quantum simulations. We demonstrate that these high-accuracy simulations are important for providing definite assignments of the complex IR signals of fluxional molecules.

physics.chem-ph↗

arXiv2022

Infrared spectra at coupled cluster accuracy from neural network representations

Infrared spectroscopy is key to elucidate molecular structures, monitor reactions and observe conformational changes, while providing information on both structural and dynamical properties. This makes the accurate prediction of infrared spectra based on first-principle theories a highly desirable pursuit. Molecular dynamics simulations have proven to be a particularly powerful approach for this task, albeit requiring the computation of energies, forces and dipole moments for a large number of molecular configurations as a function of time. This explains why highly accurate first principles methods, such as coupled cluster theory, have so far been inapplicable for the prediction of fully anharmonic vibrational spectra of large systems at finite temperatures. Here, we push cutting-edge machine learning techniques forward by using neural network representations of energies, forces and in particular dipoles to predict such infrared spectra fully at "gold standard" coupled cluster accuracy as demonstrated for protonated water clusters as large as the protonated water hexamer, in its extended Zundel configuration. Furthermore, we show that this methodology can be used beyond the scope of the data considered during the development of the neural network models, allowing for the computation of finite-temperature infrared spectra of large systems inaccessible to explicit coupled cluster calculations. This substantially expands the hitherto existing limits of accuracy, speed and system size for theoretical spectroscopy and opens up a multitude of avenues for the prediction of vibrational spectra and the understanding of complex intra- and intermolecular couplings.

physics.chem-ph↗

arXiv2022

Neural Network Interaction Potentials for para-Hydrogen with Flexible Molecules

The study of molecular impurities in $para$-hydrogen ($p$H$\rm_2$) clusters is key to push forward our understanding of intra- and intermolecular interactions including their impact on the superfluid response of this bosonic quantum solvent. This includes tagging with one or very few $p$H$\rm_2$, the microsolvation regime, and matrix isolation. However, the fundamental coupling between the bosonic $p$H$\rm_2$ environment and the (ro-)vibrational motion of molecular impurities remains poorly understood. Quantum simulations can in provide the necessary atomistic insight, but very accurate descriptions of the involved interactions are required. Here, we present a data-driven approach for the generation of $impurity\cdots p$H$\rm_2$ interaction potentials based on machine learning techniques which retain the full flexibility of the impurity. We employ the well-established adiabatic hindered rotor (AHR) averaging technique to include the impact of the nuclear spin statistics on the symmetry-allowed rotational quantum numbers of $p$H$\rm_2$. Embedding this averaging procedure within the high-dimensional neural network potential (NNP) framework enables the generation of highly-accurate AHR-averaged NNPs at coupled cluster accuracy, namely CCSD(T$^*$)-F12a/aVTZcp in an automated manner. We apply this methodology to the water and protonated water molecules, as representative cases for quasi-rigid and highly-flexible molecules respectively, and obtain AHR-averaged NNPs that reliably describe the H$\rm _2$O$\cdots p$H$\rm_2$ and H$\rm _3$O$^+\cdots p$H$\rm_2$ interactions. Using path integral simulations we show for the hydronium cation that umbrella-like tunneling inversion has a strong impact on the first and second $p$H$\rm_2$ microsolvation shells. The data-driven nature of our protocol opens the door to the study of bosonic $p$H$\rm_2$ quantum solvation for a wide range of embedded impurities.

physics.chem-ph↗

arXiv2021

Converged Colored Noise Path Integral Molecular Dynamics Study of the Zundel Cation down to Ultra-low Temperatures at Coupled Cluster Accuracy

For a long time, performing converged path integral simulations at ultra-low, but finite temperatures of a few Kelvin has been a nearly impossible task. However, recent developments in advanced colored noise thermostatting schemes for path integral simulations, namely the Path Integral Generalized Langevin Equation Thermostat (PIGLET) and the Path Integral Quantum Thermal Bath (PIQTB), have been able to greatly reduce the computational cost of these simulations, thus making the ultra-low temperature regime accessible in practice. In this work, we investigate the influence of these two thermostatting schemes on the description of hydrogen-bonded systems at temperatures down to a few Kelvin as encountered, for example, in helium nanodroplet isolation or tagging photodissociation spectroscopy experiments. For this purpose, we analyze the prototypical hydrogen bond in the Zundel cation (H$_5$O$_{2}^{+}$) as a function of both, oxygen-oxygen distance and temperature in order to elucidate how the anisotropic quantum delocalization and, thus, the shape of the shared proton adapts depending on the donor-acceptor distance. The underlying electronic structure of the Zundel cation is described in terms of Behler's Neural Network Potentials of essentially converged Coupled Cluster accuracy, CCSD(T*)-F12a/AVTZ. In addition, the performances of the PIQTB and PIGLET methods for energetic, structural, and quantum delocalization properties are assessed and directly compared. Overall, our results emphasize the validity and practical usefulness of these two modern thermostatting approaches for path integral simulations of hydrogen-bonded systems even at ultra-low temperatures.

physics.chem-ph↗

arXiv2021

Transferability of machine learning potentials: Protonated water neural network potential applied to the protonated water hexamer

A previously published neural network potential for the description of protonated water clusters up to the protonated water tetramer, H$^+$(H$_2$O)$_4$, at essentially converged coupled cluster accuracy (J. Chem. Theory Comput. 16, 88 (2020)) is applied to the protonated water hexamer, H$^+$(H$_2$O)$_6$ -- a system that the neural network has never seen before. Although being in the extrapolation regime, it is shown that the potential not only allows for quantum simulations from ultra-low temperatures $\sim$ 1 K up to 300 K, but that it is able to describe the new system very accurately compared to explicit coupled cluster calculations. This transferability of the model is rationalized by the similarity of the atomic environments encountered for the larger cluster compared to the environments in the training set of the model. Compared to the interpolation regime the quality of the model is reduced by roughly one order of magnitude, but most of the difference to the coupled cluster reference comes from global shifts of the potential energy surface, while local energy fluctuations are well recovered. These results suggest that the application of neural network potentials in extrapolation regimes can provide useful results and might be more general than usually thought.

physics.chem-ph↗

arXiv2020

Deciphering High-order Structural Correlations within Fluxional Molecules from Classical and Quantum Configurational Entropy

We employ the k-th nearest-neighbor estimator of configurational entropy in order to decode within a parameter-free numerical approach the complex high-order structural correlations in fluxional molecules going beyond the usual linear, bivariate correlations. This generic entropy-based scheme for determining many-body correlations is applied to the complex configurational ensemble of protonated acetylene, a prototype for fluxional molecules featuring large-amplitude motion. After revealing the importance of high-order correlations beyond the simple two-coordinate picture for this molecule, we analyze in detail the evolution of the relevant correlations with temperature as well as the impact of nuclear quantum effects down to the ultra-low temperature regime of 1 K. We find that quantum delocalization and zero-point vibrations significantly reduce all correlations in protonated acetylene in the deep quantum regime. At intermediate temperatures of approximately 100 to 800 K, a quantum-to-classical cross-over regime is found where classical mechanics starts to correctly describe trends in the correlations whereas it even qualitatively fails below 100 K. Finally, a classical description of the nuclei provides correlations that are in quantitative agreement with the quantum ones only at temperatures exceeding 1000 K. This data-intensive analysis has been made possible due to recent developments of machine learning techniques based on neural network potentials in full dimensionality that allow us to exhaustively sample both, the classical and quantum ensemble of protonated acetylene at essentially converged coupled cluster accuracy. The presented non-parametric analysis of correlations is expected to complement and guide the analysis of experimental measurements, in particular multi-dimensional vibrational spectroscopy, by revealing the complex coupling between various degrees of freedom.

physics.chem-ph↗

arXiv2016

Zero-Point Energy Leakage in Quantum Thermal Bath Molecular Dynamics Simulations

The quantum thermal bath (QTB) has been presented as analternative to path-integral-based methods to introduce nuclear quantumeffects in molecular dynamics simulations. The method has proved to beefficient, yielding accurate results for various systems. However, the QTBmethod is prone to zero-point energy leakage (ZPEL) in highly anharmonicsystems. This is a well-known problem in methods based on classicaltrajectories where part of the energy of the high-frequency modes istransferred to the low-frequency modes leading to a wrong energydistribution. In some cases, the ZPEL can have dramatic consequences onthe properties of the system. Thus, we investigate the ZPEL by testing theQTB method on selected systems with increasing complexity in order to studythe conditions and the parameters that influence the leakage. We also analyze the consequences of the ZPEL on the structuraland vibrational properties of the system. We find that the leakage is particularly dependent on the damping coefficient and thatincreasing its value can reduce and, in some cases, completely remove the ZPEL. When using sufficiently high values for thedamping coefficient, the expected energy distribution among the vibrational modes is ensured. In this case, the QTB methodgives very encouraging results. In particular, the structural properties are well-reproduced. The dynamical properties should beregarded with caution although valuable information can still be extracted from the vibrational spectrum, even for large values ofthe damping term.

cond-mat.stat-mech↗