arXiv subjects

Rodrigo Freitas

Publications and source records attributed to Rodrigo Freitas.

28 records · Page 2Linked to original sources

arXiv2022

A data-centric framework for crystal structure identification in atomistic simulations using machine learning

Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. It is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods -- especially at high temperatures when lattices are the most distorted -- while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.

cond-mat.mtrl-sci↗

arXiv2022

Nonequilibrium free-energy calculation of solids using LAMMPS

This article describes nonequilibrium techniques for the calculation of free energies of solids using molecular dynamics (MD) simulations. These methods provide an alternative to standard equilibrium thermodynamic integration methods and often present superior efficiency. Here we describe the implementation in the LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) code of two specific nonequilibrium processes that allow the calculation of the free-energy difference between two different system Hamiltonians as well as the free-energy temperature dependence of a given Hamiltonian, respectively. The theory behind the methods is summarized, and we describe (including fragments of LAMMPS scripts) how the process parameters should be selected to obtain the best-possible efficiency in the calculations of free energies using nonequilibrium MD simulations. As an example of the application of the methods we present results related to polymorphic transitions for a classical potential model of iron.

cond-mat.mtrl-sci↗

arXiv2021

Dual phase patterning during a congruent grain boundary phase transition in elemental copper

The phase behavior of grain boundaries can have a strong influence on interfacial properties. Little is known about the emergence of grain boundary phases in elemental metal systems and how they transform. Here, we observe the nanoscale patterning of a grain boundary by two alternating grain boundary phases with distinct atomic structures in elemental copper by atomic resolution imaging. The same grain boundary phases are found by grain boundary structure search indicating a first-order transformation. Finite temperature atomistic simulations reveal a congruent, diffusionless transition between these phases under ambient pressure. The patterning of the grain boundary at room temperature is dominated by the grain boundary phase junctions separating the phase segments. Our analysis suggests that the reduced mobility of the phase junctions at low temperatures kinetically limits the transformation, but repulsive elastic interactions between them and disconnections could additionally stabilize the pattern formation.

cond-mat.mtrl-sci↗

arXiv2021

Atomic-Level Features for Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or other processes and accelerate the prediction of the chemical evolution by up to four order of magnitude. Such models go beyond the commonly employed potential energy surface fitting methods in that they are aimed purely at describing kinetic effects. So far, such kinetic models utilize molecular descriptions of reactions and have been constrained to only reproduce molecules previously observed in MD simulations. Therefore, these descriptions fail to predict the reactivity of unobserved molecules, for example in the case of large molecules or solids. Here we propose a new approach for the extraction of reaction mechanisms and reaction rates from MD simulations, namely the use of atomic-level features. Using the complex chemical network of hydrocarbon pyrolysis as example, it is demonstrated that kinetic models built using atomic features are able to explore chemical reaction pathways never observed in the MD simulations used to parametrize them. Atomic-level features are shown to construct reaction mechanisms and estimate reaction rates of unknown molecular species from elementary atomic events. Through comparisons of the model ability to extrapolate to longer simulation timescales and different chemical compositions than the ones used for parameterization, it is demonstrated that kinetic models employing atomic features retain the same level of accuracy and transferability as the use of features based on molecular species, while being more compact and parametrized with less data. We also find that atomic features can better describe the formation of large molecules enabling the simultaneous description of small molecules and condensed phases.

physics.comp-ph↗

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

Uncovering the effects of interface-induced ordering of liquid on crystal growth using machine learning

The process of crystallization is often understood in terms of the fundamental microstructural elements of the crystallite being formed, such as surface orientation or the presence of defects. Considerably less is known about the role of the liquid structure on the kinetics of crystal growth. Here atomistic simulations and machine learning methods are employed together to demonstrate that the liquid adjacent to solid-liquid interfaces presents significant structural ordering, which effectively reduces the mobility of atoms and slows down the crystallization kinetics. Through detailed studies of silicon and copper we discover that the extent to which liquid mobility is affected by interface-induced ordering (IIO) varies greatly with the degree of ordering and nature of the adjacent interface. Physical mechanisms behind the IIO anisotropy are explained and it is demonstrated that incorporation of this effect on a physically-motivated crystal growth model enables the quantitative prediction of the growth rate temperature dependence.

cond-mat.mtrl-sci↗

arXiv2018

Quantum effects on dislocation motion from Ring-Polymer Molecular Dynamics

Quantum motion of atoms known as zero-point vibrations is recognized to be important at low temperatures in condensed matter systems comprised of light atoms or ions, affecting such properties and behaviors as proton-transfer reactions, vibrational spectra of water and ice, and mechanical properties of low temperature helium. Recently, quantum motion of atoms was proposed to explain a long-standing discrepancy between theoretically computed and experimentally measured low-temperature resistance (Peierls stress) to dislocation motion in iron and possibly other metals with high atomic masses. Here we report the first direct simulations of quantum motion of screw dislocations in iron within the exact formalism of Ring-Polymer Molecular Dynamics (RPMD) that rigorously accounts for quantum effects on the statistics of condensed-phase systems. Our quantum RPMD simulations predict only a modest ($\approx\!13\%$) reduction in the Peierls stress in iron compared to its fully classical prediction. Our simulations confirm that reduction in the Peierls stress solely due to the zero-point energy is close to $50\%$ predicted earlier, but its effect is substantially offset by an increase in the effective atom size with decreasing temperature, an effect known as quantum dispersion. Thus, quantum motion of atoms does not resolve the notorious discrepancy between theoretical and experimental values of the Peierls stress in iron.

cond-mat.mtrl-sci↗

arXiv2018

Free energy of grain boundary phases: Atomistic calculations for $Σ$5(310)[001] grain boundary in Cu

Atomistic simulations are employed to demonstrate the existence of a well-defined thermodynamic phase transformation between grain boundary (GB) phases with different atomic structures. The free energy of different interface structures for an embedded-atom-method model of the $Σ5 (310) [001]$ symmetric tilt boundary in elemental Cu is computed using the nonequilibrium Frenkel-Ladd thermodynamic integration method through molecular dynamics simulations. It is shown that the free-energy curves predict a temperature-induced first-order interfacial phase transition in the GB structure in agreement with computational studies of the same model system. Moreover, the role of vibrational entropy in the stabilization of the high-temperature GB phase is clarified. The calculated results are able to determine the GB phase stability at homologous temperatures less than $0.5$, a temperature range particularly important given the limitation of the methods available hitherto in modeling GB phase transitions at low temperatures. The calculation of GB free energies complements currently available $0\,\mathrm{K}$ GB structure search methods, making feasible the characterization of GB phase diagrams.

cond-mat.mtrl-sci↗

arXiv2017

Capillary fluctuations of surface steps: An atomistic simulation study for the model Cu(111) system

Molecular dynamics (MD) simulations are employed to investigate the capillary fluctuations of steps on the surface of a model metal system. The fluctuation spectrum, characterized by the wave number ($k$) dependence of the mean squared capillary-wave amplitudes and associated relaxation times, is calculated for $\left<110\right>$ and $\left<112\right>$ steps on the $\{111\}$ surface of elemental copper near the melting temperature of the classical potential model considered. Step stiffnesses are derived from the MD results, yielding values from the largest system sizes of $(37\pm1) \, \mathrm{meV}/\mathring{\mathrm{A}}$ for the different line orientations, implying that the stiffness is isotropic within the statistical precision of the calculations. The fluctuation lifetimes are found to vary by approximately four orders of magnitude over the range of wave numbers investigated, displaying a $k$ dependence consistent with kinetics governed by step-edge mediated diffusion. The values for step stiffness derived from these simulations are compared to step free energies for the same system and temperature obtained in a recent MD-based thermodynamic-integration (TI) study [Freitas, Frolov, and Asta, Phys. Rev. B 95, 155444 (2017)]. Results from the capillary-fluctuation analysis and TI calculations yield statistically significant differences that are discussed within the framework of statistical-mechanical theories for configurational contributions to step free energies.

cond-mat.mtrl-sci↗

arXiv2017

Step free energies at faceted solid surfaces: Theory and atomistic calculations for steps on the Cu(111) surface

A theory for the thermodynamic properties of steps on faceted crystalline surfaces is presented. The formalism leads to the definition of step excess quantities, including an excess step stress that is the step analogy of surface stress. The approach is used to develop a relationship between the temperature dependence of the step free energy ($γ^\mathrm{st}$) and step excess quantities for energy and stress that can be readily calculated by atomistic simulations. We demonstrate the application of this formalism in thermodynamic-integration (TI) calculations of the step free energy, based on molecular-dynamics simulations, considering $\left< 110 \right>$ steps on the $\{111\}$ surface of a classical potential model for elemental Cu. In this application we employ the Frenkel-Ladd approach to compute the reference value of $γ^\mathrm{st}$ for the TI calculations. Calculated results for excess energy and stress show relatively weak temperature dependencies up to a homologous temperature of approximately 0.6, above which these quantities increase strongly and the step stress becomes more isotropic. From the calculated excess quantities we compute $γ^\mathrm{st}$ over the temperature range from zero up to the melting point ($T_\mathrm{m}$). We find that $γ^\mathrm{st}$ remains finite up to $T_\mathrm{m}$, indicating the absence of a roughening temperature for this $\{111\}$ surface facet, but decreases by roughly fifty percent from the zero-temperature value. The strongest temperature dependence occurs above homologous temperatures of approximately 0.6, where the step becomes configurationally disordered due to the formation of point defects and appreciable capillary fluctuations.

cond-mat.mtrl-sci↗