arXiv subjects

Nicolas Bertin

Publications and source records attributed to Nicolas Bertin.

17 recordsLinked to original sources

arXiv2026

Precipitation strengthening: a collective multi-dislocation phenomenon

Precipitation strengthening is a cornerstone of physical metallurgy, delivering otherwise unattainable combinations of strength and ductility. The approach relies on nanoscale precipitates that impede the motion of dislocations, the primary carriers of plastic deformation. Historically, precipitation strengthening has been rationalized via two idealized, limiting mechanisms: dislocations either cut through or bow around precipitates. However, in situ experiments cannot yet resolve the coupled, real-time evolution of dislocation networks and nanoprecipitates, leaving these atomic-scale dynamics inaccessible to direct observation. Here, using large-scale atomistic simulations that fully capture these dynamics, we demonstrate that the classical cutting-versus-bowing dichotomy is incomplete. Instead, strengthening arises as an emergent collective phenomenon driven by concurrent, multi-dislocation interactions. These interactions simultaneously induce dislocation accumulation at interfaces, storage within precipitates, and precipitate-mediated multiplication inside the matrix. These findings establish a mechanistic framework that transcends traditional models and provides a new foundation for predicting strengthening behavior.

cond-mat.mtrl-sci↗

arXiv2026

Ductility and Brittle Fracture of Tungsten by Disconnection Pile-up on Twin Boundaries

Refractory body-centered cubic (BCC) metals and alloys are of extraordinary importance in modern technological and structural applications. However, their wider adoption in science and technology is severely restricted by low-temperature brittleness, quantified by an unacceptably high value of the brittle-to ductile transition temperature (DBTT). The DBTT of these alloys is known to depend strongly on the particular microstructure of the material following mechanisms that are not well understood. Here we apply cross-scale molecular dynamics (MD), a simulation approach that preserves full atomic resolution while capturing the collective evolution of dislocations, twins, and cracks in near-micron-scale volumes, to investigate ductility and fracture in single-crystal tungsten pillars as a function of initial defect microstructure, deformation conditions, and temperature. The simulations reveal a sequence of microscopic processes conducive to failure: dislocation starvation, nucleation and growth of twins, pinning of the twin boundaries at surface asperities, resulting in disconnection pile-ups that trigger crack nucleation and propagation at low macroscopic stresses along incoherent boundary segments. By resolving these processes within a single atomistic framework, our simulations connect defect-level dynamics to macroscopic fracture behavior and identify microstructural pathways capable of shifting the DBTT through targeted promotion or suppression of the underlying deformation mechanisms.

cond-mat.mtrl-sci↗

arXiv2025

Link Statistics of Dislocation Network during Strain Hardening

Dislocations are line defects in crystals that multiply and self-organize into a complex network during strain hardening. The length of dislocation links, connecting neighboring nodes within this network, contains crucial information about the evolving dislocation microstructure. By analyzing data from Discrete Dislocation Dynamics (DDD) simulations in face-centered cubic (fcc) Cu, we characterize the statistical distribution of link lengths of dislocation networks during strain hardening on individual slip systems. Our analysis reveals that link lengths on active slip systems follow a double-exponential distribution, while those on inactive slip systems conform to a single-exponential distribution. The distinctive long tail observed in the double-exponential distribution is attributed to the stress-induced bowing out of long links on active slip systems, a feature that disappears upon removal of the applied stress. We further demonstrate that both observed link length distributions can be explained by extending a one-dimensional Poisson process to include different growth functions. Specifically, the double-exponential distribution emerges when the growth rate for links exceeding a critical length becomes super-linear, which aligns with the physical phenomenon of long links bowing out under stress. This work advances our understanding of dislocation microstructure evolution during strain hardening and elucidates the underlying physical mechanisms governing its formation.

cond-mat.mtrl-sci↗

arXiv2025

Atomistic insights into solid solution strengthening: size misfit versus stiffness misfit

Used for centuries to enhance mechanical properties of materials, solid solution strengthening (SSS) is a classical metallurgical method in which small amounts of impurity elements are added to a base metal. Developed for dilute alloys, classical theories of SSS are presently challenged by the ongoing explosive development of complex concentrated alloys (CCA) in which all component elements are present in nearly equal fractions. Here we develop a method of computational alchemy in which interatomic interactions are modified to continuously and systematically vary two key parameters defining SSS, atomic size misfit and elastic stiffness misfit, over a maximally wide range of misfit values. The resulting model alloys are subjected to massive Molecular Dynamics simulations reproducing full complexity of plastic strength response in concentrated single-phase body-centered cubic solid solutions. At variance with views prevailing in the literature, our computational experiments show that stiffness misfit can contribute to SSS on par if not more than size misfit. Furthermore, depending on exactly how they are combined, the two misfits can result in synergistic or antagonistic effect on alloy strengthening. In contrast to real CCAs in which every constituent element comes with its specific combination of atomic size and elastic stiffness, our alchemical model alloys sample the space of misfit parameters continuously thus augmenting the much more constrained and inevitably spotty experimental exploration of the CCA design space. Taking advantage of unique to our approach ability to define alloy misfit parameters, our computational study demonstrates how useful insights can be gained from intentionally unrealistic alchemical models. Rather than practical recommendation for alloy design, our computational experiments should be regarded as a proving ground for further SSS theory development.

cond-mat.mtrl-sci↗

arXiv2024

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray Microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high dislocation density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation (DD) structures obtained from atomistic simulations. Our new DD-DFXM model integrates a non-singular formulation for calculating the local strain from the DD structures and an efficient geometrical optics algorithm for computing the DFXM image from the strain. We apply the model to complex DD structures obtained from a large-scale molecular dynamics (MD) simulation of compressive loading on a single-crystal silicon. Simulated DFXM images exhibit prominent feature contrast for dislocations between the multiple slip systems, demonstrating the DFXM's potential to resolve features from dislocation multiplication. The integrated DD-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for the breadth of measurements across shock plasticity and the broader materials science community.

cond-mat.mtrl-sci↗

arXiv2024

Enhanced mobility of dislocation network nodes and its effect on dislocation multiplication and strain hardening

Understanding plastic deformation of crystals in terms of the fundamental physics of dislocations has remained a grand challenge in materials science for decades. To overcome this, the Discrete Dislocation Dynamics (DDD) method has been developed, but its lack of atomistic resolution leaves open the possibility that certain key mechanisms may be overlooked. By comparing large-scale Molecular Dynamics (MD) with DDD simulations performed under identical conditions we uncover significant discrepancies in the predicted strength and microstructure evolution in BCC crytals under high-strain rate conditions. These are traced to unexpected behaviors of dislocation network nodes forming at dislocation intersections, that can move in ways not previously anticipated as revealed by MD. Once these newfound freedoms of nodal motion are incorporated, DDD simulations begin to closely match plastic evolution observed in MD. This additional mechanism of motion whereby non-screw dislocations can change their glide plane profoundly affects fundamental processes of dislocation multiplication, recovery and storage that define strength of metals.

cond-mat.mtrl-sci↗

arXiv2023

Learning dislocation dynamics mobility laws from large-scale MD simulations

The computational method of discrete dislocation dynamics (DDD), used as a coarse-grained model of true atomistic dynamics of lattice dislocations, has become of powerful tool to study metal plasticity arising from the collective behavior of dislocations. As a mesoscale approach, motion of dislocations in the DDD model is prescribed via the mobility law; a function which specifies how dislocation lines should respond to the driving force. However, the development of traditional hand-crafted mobility laws can be a cumbersome task and may involve detrimental simplifications. Here we introduce a machine-learning (ML) framework to streamline the development of data-driven mobility laws which are modeled as graph neural networks (GNN) trained on large-scale Molecular Dynamics (MD) simulations of crystal plasticity. We illustrate our approach on BCC tungsten and demonstrate that our GNN mobility implemented in large-scale DDD simulations accurately reproduces the challenging tension/compression asymmetry observed in ground-truth MD simulations while correctly predicting the flow stress at lower straining rate conditions unseen during training, thereby demonstrating the ability of our method to learn relevant dislocation physics. Our DDD+ML approach opens new promising avenues to improve fidelity of the DDD model and to incorporate more complex dislocation motion behaviors in an automated way, providing a faithful proxy for dislocation dynamics several orders of magnitude faster than ground-truth MD simulations.

cond-mat.mtrl-sci↗

arXiv2023

Score-based denoising for atomic structure identification

We propose an effective method for removing thermal vibrations that complicate the task of analyzing complex dynamics in atomistic simulation of condensed matter. Our method iteratively subtracts thermal noises or perturbations in atomic positions using a denoising score function trained on synthetically noised but otherwise perfect crystal lattices. The resulting denoised structures clearly reveal underlying crystal order while retaining disorder associated with crystal defects. Purely geometric, agnostic to interatomic potentials, and trained without inputs from explicit simulations, our denoiser can be applied to simulation data generated from vastly different interatomic interactions. The denoiser is shown to improve existing classification methods such as common neighbor analysis and polyhedral template matching, reaching perfect classification accuracy on a recent benchmark dataset of thermally perturbed structures up to the melting point. Demonstrated here in a wide variety of atomistic simulation contexts, the denoiser is general, robust, and readily extendable to delineate order from disorder in structurally and chemically complex materials.

cond-mat.mtrl-sci↗

arXiv2023

Accelerating discrete dislocation dynamics simulations with graph neural networks

Discrete dislocation dynamics (DDD) is a widely employed computational method to study plasticity at the mesoscale that connects the motion of dislocation lines to the macroscopic response of crystalline materials. However, the computational cost of DDD simulations remains a bottleneck that limits its range of applicability. Here, we introduce a new DDD-GNN framework in which the expensive time-integration of dislocation motion is entirely substituted by a graph neural network (GNN) model trained on DDD trajectories. As a first application, we demonstrate the feasibility and potential of our method on a simple yet relevant model of a dislocation line gliding through an array of obstacles. We show that the DDD-GNN model is stable and reproduces very well unseen ground-truth DDD simulation responses for a range of straining rates and obstacle densities, without the need to explicitly compute nodal forces or dislocation mobilities during time-integration. Our approach opens new promising avenues to accelerate DDD simulations and to incorporate more complex dislocation motion behaviors.

cond-mat.mtrl-sci↗

arXiv2022

Numerical simulation of universal morphogenesis of fluid interface deformations driven by radiation pressure

We report on ab initio simulation of fluid interface deformations induced either by acoustic or optical radiation pressure. This is done by solving simultaneously the scalar wave propagation equation and the two-phase flow equations using the boundary element method. Using dimensional analysis, we show that interface deformation morphogenesis is universal, i.e. depends on the same dimensionless parameters in acoustics and electromagnetics. We numerically investigate a few selected phenomena -- in particular the shape of large deformations, the slenderness transition and its hysteresis -- and compare with existing and novel experimental observations. Qualitative agreement between the numerical simulations and experiments is found when the mutual interaction between wave propagation and wave-induced deformations is taken into account. Our results demonstrate the leading role of the radiation pressure in morphogenesis of fluid interface deformations and the importance of the propagation-deformation interplay .

physics.flu-dyn↗

arXiv2022

Energy storage under high-rate compression of single crystal tantalum

When a material is plastically deformed the majority of mechanical work is dissipated as heat, and the fraction of plastic work converted into heat is known as the Taylor-Quinney coefficient (TQC). Large-scale molecular dynamics simulations were performed of high strain rate compression of single-crystal tantalum, and the resulting integral and differential TQC values are reported up to true strains of 1.0. A phenomenological model is proposed for the energy stored in the material as a function of time with an asymptotic limit for this energy defined by the deformation conditions. The model reasonably describes the convergence of TQC values to 1.0 with increasing plastic strain, but does not directly address the physical nature of thermo-mechanical conversion. This is instead developed in a second more detailed model that accurately accounts for energy storage in two distinct contributions, one being the growing dislocation network and the other the point defect debris left behind by the moving dislocations. The contribution of the point defect debris is found to lag behind that of the dislocation network but to be substantial under the high-rate straining conditions considered here.

cond-mat.mtrl-sci↗

arXiv2020

Metal hardening in atomistic detail

Through millennia humans exploited the natural property of metals to get stronger or hardened when mechanically deformed. Ultimately rooted in the motion of dislocations, mechanisms of metal hardening remained in the crosshairs of physical metallurgists for over a century. Here, we performed atomistic simulations at the limits of supercomputing, which are sufficiently large to be statistically representative of macroscopic crystal plasticity yet fully resolved to examine the origins of metal hardening at its most fundamental level of atomic motion. We demonstrate that the notorious staged (inflection) hardening of metals is a direct consequence of crystal rotation under uniaxial straining. At variance with widely divergent and contradictory views in the literature, we observe that basic mechanisms of dislocation behavior are the same across all stages of metal hardening.

cond-mat.mtrl-sci↗

arXiv2020

Dislocation Density-Based Plasticity Model from Massive Discrete Dislocation Dynamics Database

We present a dislocation density-based strain hardening model for single crystal copper through a systematic coarse-graining analysis of more than 200 discrete dislocation dynamics (DDD) simulations of plastic deformation under uniaxial tension. The proposed constitutive model has two components: a generalized Taylor relation connecting resolved shear stresses to dislocation densities on individual slip systems, and a generalized Kocks-Mecking model for dislocation multiplication. The DDD data strongly suggests a logarithmic dependence of flow stress on the plastic shear strain rate on each slip system, and, equivalently, an exponential dependence of the plastic shear strain rate on the resolved shear stress. Hence the proposed generalized Taylor relation subsumes the Orowan relation for plastic flow. The DDD data also calls for a correction to the Kocks-Mecking model of dislocation multiplication to account for the increase of dislocation density on slip systems with negligible plastic shear strain rate. This is accomplished by allowing the multiplication rate on each slip system to include contributions from the plastic strain rates of the two coplanar slip systems. The resulting constitutive model successfully captures the strain hardening rate dependence on the loading orientation as predicted by the DDD simulations, which is also consistent with existing experiments.

cond-mat.mtrl-sci↗

arXiv2020

Topological origin of strain induced damage of multi-network elastomers by bond breaking

Elastomers that can sustain large reversible strain are essential components for stretchable electronics. The stretchability and mechanical robustness of unfilled elastomers can be enhanced by introducing easier-to-break cross-links, e.g. through the multi-network structure, which also causes stress-strain hysteresis indicating strain-induced damage. However, it remains unclear whether cross-link breakage follows a predictable pattern that can be used to understand the damage evolution with strain. Using coarse-grained molecular dynamics and topology analyses of the polymer network, we find that bond-breaking events are controlled by the evolution of the global shortest path length between well-separated cross-links, which is both anisotropic and hysteretic with strain. These findings establish an explicit connection between the molecular structure and the macroscopic mechanical behavior of elastomers, thereby providing guidelines for designing mechanically robust soft materials.

cond-mat.soft↗

arXiv2018

Connecting discrete and continuum dislocation mechanics: a non-singular spectral framework

In this paper, we present an improved framework of the spectral-based Discrete Dislocation Dynamics (DDD) approach introduced in [1,2], that establishes a direct connection with the continuum Field Dislocation Mechanics (FDM) approach. To this end, an analytical method to convert a discrete dislocation network to its continuous dislocation density tensor representation is first developed. From there, the mechanical fields are evaluated using a FDM-based spectral framework, while submesh resolution elastic interactions are accounted for via the introduction of a rigorous stress splitting procedure that leverages properties of non-singular dislocation theories. The model results in a computationally efficient approach for DDD simulations that enables the use of elastic anisotropy and heterogeneities, while being fully compatible with recently developed subcycling time-integrators. As an example, the model is used to perform a work-hardening simulation, and potential applications that take advantage of the full-field nature of the method are explored, such as informing FDM models, and efficiently calculating virtual diffraction patterns.

physics.comp-ph↗

arXiv2017

Dislocation Networks and the Microstructural Origin of Strain Hardening

When metals are plastically deformed, the total density of dislocations increases with strain as the microstructure is continuously refined, leading to the strain hardening behavior. Here we report the fundamental role played by the junction formation process in the connection between dislocation microstructure evolution and the strain hardening rate in face-centered cubic (FCC) Cu, as revealed by discrete dislocation dynamics (DDD) simulations. The dislocation network formed during [001] loading consists of line segments whose lengths closely follow an exponential distribution. This exponential distribution is a consequence of junction formation by dislocations on different slip planes, which can be modeled as a one-dimensional Poisson process. We show that, according to the exponential distribution, the dislocation microstructure evolution is governed by two non-dimensional parameters, and the hardening rate is controlled by the rate of stable junction formation. By selectively disabling specific junction types in DDD simulations, we find that among the four types of junctions in FCC crystals, glissile junctions make the dominant contribution to the strain hardening rate.

cond-mat.mtrl-sci↗

arXiv2012

Universal morphologies of fluid interfaces deformed by the radiation pressure of acoustic or electromagnetic waves

We unveil the generation of universal morphologies of fluid interfaces by radiation pressure whatever is the nature of the wave, acoustic or optical. Experimental observations reveal interface deformations endowed with step-like features that are shown to result from the interplay between the wave propagation and the shape of the interface. The results are supported by numerical simulations and a quantitative interpretation based on the waveguiding properties of the field is provided.

cond-mat.soft↗