Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: To advance the development of high-strength polycrystalline metallic materials towards achieving carbon neutrality, it is essential to design materials in which the atomic level control of general grain boundaries (GGBs), which govern the material properties, is achieved. However, owing to the complex and diverse structures of GGBs, there have been no reports on interatomic potentials capable of reproducing them. This accuracy is essential for conducting molecular dynamics analyses to derive material design guidelines. In this study, we constructed a machine learning interatomic potential (MLIP) with density functional theory (DFT) accuracy to model the energy, atomic structure, and dynamics of arbitrary grain boundaries (GBs), including GGBs, in α-Fe. Specifically, we employed a training dataset comprising diverse atomic structures generated based on crystal space groups. The GGB accuracy was evaluated by directly comparing with DFT calculations performed on cells cut near GBs from nano-polycrystals, and extrapolation grades of the local atomic environment based on active learning methods for the entire nano-polycrystal. Furthermore, we analyzed the GB energy and atomic structure in α-Fe polycrystals through large-scale molecular dynamics analysis using the constructed MLIP. The average GB energy of α-Fe polycrystals calculated by the constructed MLIP is 1.57 J/m², exhibiting good agreement with experimental predictions. Our findings demonstrate the methodology for constructing an MLIP capable of representing GGBs with high accuracy, thereby paving the way for materials design based on computational materials science for polycrystalline materials.

Abstract: To advance the development of high-strength polycrystalline metallic materials towards achieving carbon neutrality, it is essential to design materials in which the atomic level control of general grain boundaries (GGBs), which govern the material properties, is achieved. However, owing to the complex and diverse structures of GGBs, there have been no reports on interatomic potentials capable of reproducing them. This accuracy is essential for conducting molecular dynamics analyses to derive material design guidelines. In this study, we constructed a machine learning interatomic potential (MLIP) with density functional theory (DFT) accuracy to model the energy, atomic structure, and dynamics of arbitrary grain boundaries (GBs), including GGBs, in α-Fe. Specifically, we employed a training dataset comprising diverse atomic structures generated based on crystal space groups. The GGB accuracy was evaluated by directly comparing with DFT calculations performed on cells cut near GBs from nano-polycrystals, and extrapolation grades of the local atomic environment based on active learning methods for the entire nano-polycrystal. Furthermore, we analyzed the GB energy and atomic structure in α-Fe polycrystals through large-scale molecular dynamics analysis using the constructed MLIP. The average GB energy of α-Fe polycrystals calculated by the constructed MLIP is 1.57 J/m², exhibiting good agreement with experimental predictions. Our findings demonstrate the methodology for constructing an MLIP capable of representing GGBs with high accuracy, thereby paving the way for materials design based on computational materials science for polycrystalline materials.

Abstract: To advance the development of high-strength polycrystalline metallic materials towards achieving carbon neutrality, it is essential to design materials in which the atomic level control of general grain boundaries (GGBs), which govern the material properties, is achieved. However, owing to the complex and diverse structures of GGBs, there have been no reports on interatomic potentials capable of reproducing them. This accuracy is essential for conducting molecular dynamics analyses to derive material design guidelines. In this study, we constructed a machine learning interatomic potential (MLIP) with density functional theory (DFT) accuracy to model the energy, atomic structure, and dynamics of arbitrary grain boundaries (GBs), including GGBs, in α-Fe. Specifically, we employed a training dataset comprising diverse atomic structures generated based on crystal space groups. The GGB accuracy was evaluated by directly comparing with DFT calculations performed on cells cut near GBs from nano-polycrystals, and extrapolation grades of the local atomic environment based on active learning methods for the entire nano-polycrystal. Furthermore, we analyzed the GB energy and atomic structure in α-Fe polycrystals through large-scale molecular dynamics analysis using the constructed MLIP. The average GB energy of α-Fe polycrystals calculated by the constructed MLIP is 1.57 J/m², exhibiting good agreement with experimental predictions. Our findings demonstrate the methodology for constructing an MLIP capable of representing GGBs with high accuracy, thereby paving the way for materials design based on computational materials science for polycrystalline materials.

Abstract: To advance the development of high-strength polycrystalline metallic materials towards achieving carbon neutrality, it is essential to design materials in which the atomic level control of general grain boundaries (GGBs), which govern the material properties, is achieved. However, owing to the complex and diverse structures of GGBs, there have been no reports on interatomic potentials capable of reproducing them. This accuracy is essential for conducting molecular dynamics analyses to derive material design guidelines. In this study, we constructed a machine learning interatomic potential (MLIP) with density functional theory (DFT) accuracy to model the energy, atomic structure, and dynamics of arbitrary grain boundaries (GBs), including GGBs, in α-Fe. Specifically, we employed a training dataset comprising diverse atomic structures generated based on crystal space groups. The GGB accuracy was evaluated by directly comparing with DFT calculations performed on cells cut near GBs from nano-polycrystals, and extrapolation grades of the local atomic environment based on active learning methods for the entire nano-polycrystal. Furthermore, we analyzed the GB energy and atomic structure in α-Fe polycrystals through large-scale molecular dynamics analysis using the constructed MLIP. The average GB energy of α-Fe polycrystals calculated by the constructed MLIP is 1.57 J/m², exhibiting good agreement with experimental predictions. Our findings demonstrate the methodology for constructing an MLIP capable of representing GGBs with high accuracy, thereby paving the way for materials design based on computational materials science for polycrystalline materials.

Abstract: To improve the mechanical properties of polycrystalline metallic materials, understanding the elementary processes involved in their deformation at the atomic level is crucial. In this study, firstly, we evaluate the transferability of the recently proposed α-Fe machine-learning interatomic potential (MLIP), constructed from mechanically generated training data based on crystal space groups, to the tensile deformation process of nanopolycrystals. The transferability was evaluated by comparing the physical properties and lattice defect formation energies, which are important in the deformation behavior of nanopolycrystals, with those obtained from density functional theory (DFT) and by comprehensively calculating extrapolation grades based on active learning methods for the local atomic environment in the nanopolycrystal during tensile deformation. These evaluations demonstrate the superior transferability of the MLIP to the tensile deformation of the nanopolycrystals. Furthermore, large-scale molecular dynamics calculations were performed using the MLIP and the most commonly used embedded atom method (EAM) potential to investigate the effect of grain size on the deformation behavior of α-Fe polycrystals and the effect of interatomic potentials on them. The uniaxial tensile deformation behavior of the nanopolycrystals obtained from EAM was qualitatively consistent with that obtained from MLIP. This result supports the results of many studies conducted using EAM and is an important conclusion considering the high computational cost of the MLIP. Furthermore, the construction method for the MLIP used in this study is applicable to other metals. Therefore, this study considerably contributes to the understanding and material design of various metallic materials through the construction of highly accurate MLIPs.

Abstract: We present a general-purpose machine learning Gaussian approximation potential (GAP) for iron that is applicable to all bulk crystal structures found experimentally under diverse thermodynamic conditions, as well as surfaces and nanoparticles (NPs). By studying its phase diagram, we show that our GAP remains stable at extreme conditions, including those found in the Earth's core. The new GAP is particularly accurate for the description of NPs. We use it to identify new low-energy NPs, whose stability is verified by performing density functional theory calculations on the GAP structures. Many of these NPs are lower in energy than those previously available in the literature up to N_atoms = 100. We further extend the convex hull of available stable structures to N_atoms = 200. For these NPs, we study characteristic surface atomic motifs using data clustering and low-dimensional embedding techniques. With a few exceptions, e.g., at magic numbers N_atoms = 59, 65, 76, and 78, we find that iron tends to form irregularly shaped NPs without a dominant surface character or characteristic atomic motif, and no reminiscence of crystalline features. We hypothesize that the observed disorder stems from an intricate balance and competition between the stable bulk motif formation, with bcc structure, and the stable surface motif formation, with fcc structure. We expect these results to improve our understanding of the fundamental properties and structure of low-dimensional forms of iron and to facilitate future work in the field of iron-based catalysis.

Abstract: The Earth's inner core started forming when molten iron cooled below the melting point. However, the nucleation mechanism, which is a necessary step of crystallization, has not been well understood. Recent studies have found that it requires an unrealistic degree of undercooling to nucleate the stable, hexagonal, close-packed (hcp) phase of iron that is unlikely to be reached under core conditions and age. This contradiction is referred to as the inner core nucleation paradox. Using a persistent embryo method and molecular dynamics simulations, we demonstrate that the metastable, body-centered, cubic (bcc) phase of iron has a much higher nucleation rate than does the hcp phase under inner core conditions. Thus, the bcc nucleation is likely to be the first step of inner core formation, instead of direct nucleation of the hcp phase. This mechanism reduces the required undercooling of iron nucleation, which provides a key factor in solving the inner core nucleation paradox. The two-step nucleation scenario of the inner core also opens an avenue for understanding the structure and anisotropy of the present inner core.

Abstract: The development of classical interatomic potential for iron is a quite demanding task with a long history background. A new interatomic potential for simulation of iron was created with a focus on description of crystal defects properties. In contrast with previous studies, here the potential development was based on force-matching method that requires only ab initio data as reference values. To verify our model, we studied various features of body-centered-cubic iron including the properties of point defects (vacancy and self-interstitial atom), the Peierls energy barrier for dislocations (screw and mix types), and the formation energies of planar defects (surfaces, grain boundaries, and stacking fault). The verification also implies thorough comparison of a potential with 11 other interatomic potentials reported in literature. This potential correctly reproduces the largest number of iron characteristics which ensures its advantage and wider applicability range compared to the other considered classical potentials. Here application of the model is illustrated by estimation of self-diffusion coefficients and the calculation of fcc lattice properties at high temperature.

Abstract: Density functional theory predicts clusters in the form of the C15 Laves phase to be the most stable cluster of self-interstitials in iron at small sizes. The C15 clusters can form as a result of irradiation, but their prevalence and survival in harsh irradiation conditions have not been thoroughly studied. Using a new bond-order potential optimised for molecular dynamics simulations of radiation damage, we explore the dynamical stability of the C15 clusters in iron under irradiation conditions. We find that small C15 clusters make up 5–20% of the interstitial clusters formed directly in cascades. In continuous irradiation, C15 clusters are frequently formed, after which they remain highly stable and grow by absorbing nearby single interstitial atoms. Growth of C15 clusters ultimately leads to collapse into dislocation loops, most frequently into 1/2 <111> loops and only rarely collapsing into <100> loops at low temperatures. The population, size, and collapse of C15 clusters during continuous irradiation correlates well with their formation energies relative to dislocation loops calculated at zero Kelvin.

Abstract: To design the mechanical strength of body-centered-cubic (bcc) iron, clarifying the dislocation dynamics is very important. Using systematically constructed reference data based on density functional theory (DFT) calculations, we construct an atomic artificial neural network (ANN) potential to investigate the dislocation dynamics in bcc iron with the accuracy of DFT calculations. The bulk properties and defect formation energies predicted by the constructed ANN potential are in good agreement with the reference DFT calculations. The a₀/2⟨111⟩110 screw dislocation core structure predicted by the ANN potential is compact and nondegenerate. The Peierls barrier predicted by the ANN potential is 35.3 meV per length of the Burgers vector. These results are consistent with the DFT results. Furthermore, not only the Peierls barrier, but also the two-dimensional energy profile of the screw dislocation core position predicted by the ANN potential are in excellent agreement with the DFT results. These results clearly demonstrate the reproducibility and transferability of the constructed ANN potential for investigating dislocation dynamics with the accuracy of the DFT. Combined with advanced atomistic techniques, the ANN potential will be highly useful for investigating the dislocation dynamics in bcc iron at finite temperatures.

Abstract: Availability of a reliable interatomic potential is one of the major challenges in utilizing molecular dynamics (MD) for simulations of metals at near the melting temperatures and melting point (MP). Here, we propose a novel approach to address this challenge in the concept of modified-embedded-atom (MEAM) interatomic potential; also, we apply the approach on iron, nickel, copper, and aluminum as case studies. We propose adding experimentally available high temperature elastic constants and MP of the element to the list of typical low temperature properties used for the development of MD interatomic potential parameters. We show that the proposed approach results in a reasonable agreement between the MD calculations of melting properties such as latent heat, expansion in melting, liquid structure factor, and solid-liquid interface stiffness and their experimental/computational counterparts. Then, we present the physical properties of mentioned elements near melting temperatures using the new MEAM parameters. We observe that the behavior of elastic constants, heat capacity and thermal linear expansion coefficient at room temperature compared to MP follows an empirical linear relation (α±β × MP) for transition metals. Furthermore, a linear relation between the tetragonal shear modulus and the enthalpy change from room temperature to MP is observed for face-centered cubic materials.

Abstract: In this paper, molecular dynamics (MD) simulations based on the modified-embedded atom method (MEAM) and a phase-field crystal (PFC) model are utilized to quantitatively investigate the solid-liquid properties of Fe. A set of second nearest-neighbor MEAM parameters for high-temperature applications are developed for Fe, and the solid-liquid coexisting approach is utilized in MD simulations to accurately calculate the melting point, expansion in melting, latent heat, and solid-liquid interface free energy, and surface anisotropy. The required input properties to determine the PFC model parameters, such as liquid structure factor and fluctuations of atoms in the solid, are also calculated from MD simulations. The PFC parameters are calculated utilizing an iterative procedure from the inputs of MD simulations. The solid-liquid interface free energy and surface anisotropy are calculated using the PFC simulations. Very good agreement is observed between the results of our calculations from MEAM-MD and PFC simulations and the available modeling and experimental results in the literature. As an application of the developed model, the grain boundary free energy of Fe is calculated using the PFC model and the results are compared against experiments.

Abstract: Crystal plasticity involves the motion of dislocations under stress. So far, atomistic simulations of this process have predicted Peierls stresses, the stress needed to overcome the crystal resistance in the absence of thermal fluctuations, of more than twice the experimental values, a discrepancy best-known in body-centred cubic crystals. Here we show that a large contribution arises from the crystal zero-point vibrations, which ease dislocation motion below typically half the Debye temperature. Using Wigner’s quantum transition state theory in atomistic models of crystals, we found a large decrease of the kink-pair formation enthalpy due to the quantization of the crystal vibrational modes. Consequently, the flow stress predicted by Orowan’s law is strongly reduced when compared with its classical approximation and in much closer agreement with experiments. This work advocates that quantum mechanics should be accounted for in simulations of materials and not only at very low temperatures or in light-atom systems.

Abstract: A second generation of empirical potentials is produced for α-Fe within the framework of the magnetic potential formalism (Dudarev and Derlet 2005 J. Phys.: Condens. Matter 17 7097). A materials database that, in addition to ab initio-derived point defect formation energies, now includes third-order elastic constant and ab initio-derived string potential data controlling, respectively, the thermal expansion properties and the core structure of the 1/2<111> screw dislocation. Three parameterizations are presented in detail, all of which exhibit positive thermal expansion and produce a non-degenerate configuration for the relaxed 1/2<111> screw dislocation easy core structure. These potentials, along with two other published potentials, are investigated in terms of defect formation volume, early stage dislocation loop clustering energetics, <110> dumbbell interstitial diffusion, and the zero-stress 1/2<111> screw dislocation Peierls barrier and its corresponding kink formation energies.

Abstract: The performance of four recent semi-empirical interatomic potentials for iron, developed or used within the FP6 Perfect Project, is evaluated by comparing them between themselves and with available experimental or, more often, density functional theory data. The quantities chosen for the comparison are of specific interest for radiation damage studies, i.e. they concern mainly properties of point-defects and their clusters, as well as dislocations. For completeness, an earlier, widely used (also within the Project) iron potential is included in the comparison exercise as well. This exercise allows conclusions to be drawn about the reliability of the available potentials, while providing a snapshot of the state-of-the-art concerning fundamental properties of iron, thereby being also useful as a kind of handbook and as a framework for the validation of future semi-empirical interatomic potentials for iron. It is found that Mendelev-type potentials are currently the best choice in order to "extend density functional theory" to larger scales and this justifies their widespread use, also for the development of iron alloy potentials. However, a fully reliable description of self-interstitial atom clusters and dislocations with interatomic potentials remains largely an elusive objective, that calls for further effort within the concerned scientific community.

Abstract: A three-dimensional periodic structure is proposed for self-interstitial clusters in body-centered-cubic metals, as opposed to the conventional two-dimensional loop morphology. The underlying crystal structure corresponds to the C15 Laves phase. Using density functional theory and interatomic potential calculations, we demonstrate that in α-iron these C15 aggregates are highly stable and immobile and that they exhibit large antiferromagnetic moments. They form directly in displacement cascades, and they can grow by capturing self-interstitials. They thus constitute an important new element to account for when predicting the microstructural evolution of iron base materials under irradiation.

Abstract: We have constructed a set of embedded atom method (EAM) potentials for Fe, Ta, W and V and used them in order to study point defect properties. The parametrizations of the potentials ensure that the third order elastic constants are continuous and they have been fitted to the cohesive energies, the lattice constants, the unrelaxed vacancy formation energies and the second order elastic constants. Formation energies for different self-interstitials reveal that the <1 1 0> split dumbbell is the most stable configuration for Fe while for Ta, W and V we find that the <1 1 1> split dumbbell is preferred. Self-interstitial migration energies are simulated using the nudged elastic band method and for Fe and W the migration energies are found to be in good agreement with experimental and ab initio data. Migration energies for Ta and V self-interstitials are found to be quite low. The calculated formation, activation and migration energies for monovacancies are in good agreement with experimental data. Formation energies for divacancies reveal that the second nearest neighbor divacancy is more energetically favorable than nearest neighbor divacancies and the migration energies indicate that nearest neighbor migration paths are more likely to occur than second nearest neighbor migration jumps. For Fe, we have also studied the influence of the pair potential behavior between the second and third nearest neighbor on the stability of the <1 1 0> split dumbbell, which revealed that the higher the energy level of the pair potential is in that region, the more stable the <1 1 0> split dumbbell becomes.

Abstract: In this work, we generalize a many-body extension of pairwise interatomic potentials originally proposed by Baskes [Phys. Rev. Lett. 83, 2592 (1991)], in particular, showing how a pair potential interacting with multiple near neighbor shells may be extended to an embedded atom form without changing the cohesive energy or lattice constant. This is important for parametric studies of interatomic potentials, particularly how elastic constants affect other properties. Specifically, we apply this to the modified Johnson potential, a pair potential for Fe that has been used extensively for understanding liquid and amorphous metals.

Abstract: A new analytic bond-order potential for iron is presented that has been fitted to experimental data and results from first-principles calculations. The angular-dependent functional form allows a proper description of a large variety of bulk, surface and defect properties, including the Bain path, phonon dispersions, defect diffusivities and defect formation energies. By calculating Gibbs free energies of body-centred cubic (bcc) and face-centred cubic (fcc) iron as a function of temperature, we show that this potential is able to reproduce the transitions from α-iron to γ-iron and δ-iron before the melting point. The results are compared to four widely used embedded-atom-method potentials for iron.

Abstract: We have constructed an embedded-atom potential for Fe by fitting to both experimental and first-principles results. The potential reproduces with satisfactory accuracy the lattice properties, surface energies and point defect energies for both BCC and the high temperature FCC phases of the metal. The potential was used in tandem with molecular-dynamics simulations to calculate the thermal expansion of both BCC-Fe and FCC-Fe, the phonon dispersion curves, mean-square displacements and surface relaxations of the element. In addition, we have studied self-diffusion of single adatoms on the BCC-Fe(1 0 0) surface at several temperatures. The migration energies and pre-exponential factors for three main diffusion mechanisms were determined and compared with available experimental data. We have found that the diagonal exchange diffusion process is energetically favored over the direct hopping mechanism and that its migration energy is close to the experimental value. Furthermore, the diffusion coefficient associated with the diagonal exchange diffusion process is about an order of magnitude higher than those of the hopping and the non-diagonal exchange mechanisms.

Abstract: We develop a semi-empirical many-body interatomic potential suitable for large scale molecular dynamics simulations of magnetic α-iron. The functional form of the embedding part of the potential is derived using a combination of the Stoner and the Ginzburg–Landau models. We show that it is the symmetry broken solutions of the Ginzburg–Landau model describing spontaneous magnetization of atoms that provide the link between magnetism and interatomic forces. We discuss a range of potential applications of the new method.

Abstract: Recent molecular dynamics simulations of the growth of [Ni0.8Fe0.2/Au] multilayers have revealed the formation of misfit-strain-reducing dislocation structures very similar to those observed experimentally. Here we report similar simulations showing the formation of edge dislocations near the interfaces of vapor-deposited (111) [NiFe/CoFe/Cu] multilayers. Unlike misfit dislocations that accommodate lattice mismatch, the dislocation structures observed here increase the mismatch strain energy. Stop-action observations of the dynamically evolving atomic structures indicate that during deposition on the (111) surface of a fcc lattice, adatoms may occupy either fcc sites or hcp sites. This results in the random formation of fcc and hcp domains, with dislocations at the domain boundaries. These dislocations enable atoms to undergo a shift from fcc to hcp sites, or vice versa. These shifts lead to missing atoms, and therefore a later deposited layer can have missing planes compared to a previously deposited layer. This dislocation formation mechanism can create tensile stress in fcc films. The probability that such dislocations are formed was found to quickly diminish under energetic deposition conditions.

Abstract: Two procedures were developed to fit interatomic potentials of the embedded-atom method (EAM) form and applied to determine a potential which describes crystalline and liquid iron. While both procedures use perfect crystal and crystal defect data, the first procedure also employs the first-principles forces in a model liquid and the second procedure uses experimental liquid structure factor data. These additional types of information were incorporated to ensure more reasonable descriptions of atomic interactions at small separations than is provided using standard approaches, such as fitting to the universal binding energy relation. The new potentials (provided herein) are, on average, in better agreement with the experimental or first-principles lattice parameter, elastic constants, point-defect energies, bcc–fcc transformation energy, liquid density, liquid structure factor, melting temperature and other properties than other existing EAM iron potentials.

Abstract: Two procedures were developed to fit interatomic potentials of the embedded-atom method (EAM) form and applied to determine a potential which describes crystalline and liquid iron. While both procedures use perfect crystal and crystal defect data, the first procedure also employs the first-principles forces in a model liquid and the second procedure uses experimental liquid structure factor data. These additional types of information were incorporated to ensure more reasonable descriptions of atomic interactions at small separations than is provided using standard approaches, such as fitting to the universal binding energy relation. The new potentials (provided herein) are, on average, in better agreement with the experimental or first-principles lattice parameter, elastic constants, point-defect energies, bcc–fcc transformation energy, liquid density, liquid structure factor, melting temperature and other properties than other existing EAM iron potentials.

Abstract: The second nearest-neighbor modified embedded atom method (MEAM) [Phys. Rev. B 62, 8564 (2000)], developed in order to solve problems of the original first nearest-neighbor MEAM on bcc metals, has now been applied to all bcc transition metals, Fe, Cr, Mo, W, V, Nb, and Ta. The potential parameters could be determined empirically by fitting to (∂B/∂P), elastic constants, structural energy differences among bcc, fcc and hcp structures, vacancy-formation energy, and surface energy. Various physical properties of individual elements, including elastic constants, structural properties, point-defect properties, surface properties, and thermal properties were calculated and compared with experiments or high level calculations so that the reliability of the present empirical atomic-potential formalism can be evaluated. It is shown that the present potentials reasonably reproduce nonfitted properties of the bcc transition metals, as well as the fitted properties. The effect of the size of radial cutoff distance on the calculation and the compatibility with the original first nearest-neighbor MEAM that has been successful for fcc, hcp, and other structures are also discussed.

Abstract: We have done molecular-dynamics simulations of Fe_1−xNi_x employing a semiempirical model. We present a phase diagram of the martensite-austenite transition temperatures as a function of the Ni concentration which is in good agreement with experimental observations. In addition to this we have calculated the phonon dispersion curves of Fe and Ni from the model. Results show that the vibrational properties of the metals are well reproduced by the embedded-atom-method potentials. Finally, we have derived the phonon dispersion relations of bcc Fe₈₀Ni₂₀. We find rather low energies of the [110]−TA₁ phonons with a strong temperature dependence which we attribute to instabilities of Ni in the bcc phase. We do not find any indications of a soft mode at the martensite-austenite transition in Fe_1−xNi_x.

Abstract: The behaviour of copper atoms in dilute solution in α-iron is important for the microstructural changes that occur in ferritic pressure vessel steels under fastneutron irradiation. To investigate the properties of atomic defects that control this behaviour, a set of many-body interatomic potentials has been developed for the Fe—Cu system. The procedures employed, including modifications to ensure suitability for simulating atomic collisions at high energy, are described. The effect of copper on the lattice parameter of iron in the new model is in good agreement with experiment. The phonon properties of the pure crystals and, in particular, the influence of the instability of the metastable, bcc phase of copper that precipitates during irradiation are discussed. The properties of point defects have been investigated. It is found that the vacancy has lower formation and migration energy in bcc copper than in α-iron, and the self-interstitial atom has very low formation energy in this phase of copper. The threshold displacement energy in iron has been computed as a function of recoil orientation for both iron-and copper-atom recoils. The differences between the energy for the two species are small.

Abstract: The Morse parameters were calculated using experimental values for the energy of vaporization, the lattice constant, and the compressibility. The equation of state and the elastic constants which were computed using the Morse parameters, agreed with experiment for both face-centered and body-centered cubic metals. All stability conditions were also satisfied for both the face-centered and the body-centered metals. This shows that the Morse function can be applied validly to problems involving any type of deformation of the cubic metals.

Abstract: Recent molecular dynamics simulations of the growth of [Ni0.8Fe0.2/Au] multilayers have revealed the formation of misfit-strain-reducing dislocation structures very similar to those observed experimentally. Here we report similar simulations showing the formation of edge dislocations near the interfaces of vapor-deposited (111) [NiFe/CoFe/Cu] multilayers. Unlike misfit dislocations that accommodate lattice mismatch, the dislocation structures observed here increase the mismatch strain energy. Stop-action observations of the dynamically evolving atomic structures indicate that during deposition on the (111) surface of a fcc lattice, adatoms may occupy either fcc sites or hcp sites. This results in the random formation of fcc and hcp domains, with dislocations at the domain boundaries. These dislocations enable atoms to undergo a shift from fcc to hcp sites, or vice versa. These shifts lead to missing atoms, and therefore a later deposited layer can have missing planes compared to a previously deposited layer. This dislocation formation mechanism can create tensile stress in fcc films. The probability that such dislocations are formed was found to quickly diminish under energetic deposition conditions.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: A set of embedded atom model (EAM) interatomic potentials was developed to represent highly idealized face-centered cubic (FCC) mixtures of Fe–Ni–Cr–Co–Al at near-equiatomic compositions. Potential functions for the transition metals and their crossed interactions are taken from our previous work for Fe–Ni–Cr–Co–Cu [D. Farkas and A. Caro: J. Mater. Res. 33 (19), 3218–3225, 2018], while cross-pair interactions involving Al were developed using a mix of the component pair functions fitted to known intermetallic properties. The resulting heats of mixing of all binary equiatomic random FCC mixtures not containing Al is low, but significant short-range ordering appears in those containing Al, driven by a large atomic size difference. The potentials are utilized to predict the relative stability of FCC quinary mixtures, as well as ordered L1₂ and B2 phases as a function of Al content. These predictions are in qualitative agreement with experiments. This interatomic potential set is developed to resemble but not model precisely the properties of this complex system, aiming at providing a tool to explore the consequences of the addition of a large size-misfit component into a high entropy mixture that develops multiphase microstructures.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: A set of modified embedded-atom method (MEAM) potentials for the interactions between Al, Si, Mg, Cu, and Fe was developed from a combination of each element's MEAM potential in order to study metal alloying. Previously published MEAM parameters of single elements have been improved for better agreement to the generalized stacking fault energy (GSFE) curves when compared with ab initio generated GSFE curves. The MEAM parameters for element pairs were constructed based on the structural and elastic properties of element pairs in the NaCl reference structure garnered from ab initio calculations, with adjustment to reproduce the ab initio heat of formation of the most stable binary compounds. The new MEAM potentials were validated by comparing the formation energies of defects, equilibrium volumes, elastic moduli, and heat of formation for several binary compounds with ab initio simulations and experiments. Single elements in their ground-state crystal structure were subjected to heating to test the potentials at elevated temperatures. An Al potential was modified to avoid formation of an unphysical solid structure at high temperatures. The thermal expansion coefficient of a compound with the composition of AA 6061 alloy was evaluated and compared with experimental values. MEAM potential tests performed in this work, utilizing the universal atomistic simulation environment (ASE), are distributed to facilitate reproducibility of the results.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: Second nearest neighbor modified embedded-atom method (2NN-MEAM) interatomic potentials are developed for binary aluminum (Al) alloys applicable from room temperature to the melting point. The binary alloys studied in this work are Al-Cu, Al-Fe and Al-Ni. Sensitivity and uncertainty analyses are performed on potential parameters based on the perturbation approach. The outcome of the sensitivity analysis shows that some of the MEAM parameters interdependently influence all MEAM model outputs, allowing for the definition of an ordered calibration procedure to target specific MEAM outputs. Using these 2NN-MEAM interatomic potentials, molecular dynamics (MD) simulations are performed to calculate low and high-temperature properties, such as the formation energies of stable phases and unstable intermetallics, lattice parameters, elastic constants, thermal expansion coefficients, enthalpy of formation of solids, liquid mixing enthalpy, and liquidus temperatures at a wide range of compositions. The computed data are compared with the available first principle calculations and experimental data, showing high accuracy of the 2NN-MEAM interatomic potentials. In addition, the liquidus temperature of the Al binary alloys is compared to the phase diagrams determined by the CALPHAD method.

Abstract: An interatomic potential for the Fe–Al binary system has been developed based on the modified embedded-atom method (MEAM) potential formalism. The potential can describe various fundamental physical properties of Fe–Al binary alloys—structural, elastic and thermodynamic properties, defect formation behavior and interactions between defects—in reasonable agreement with experimental data or higher-level calculations. The applicability of the potential to atomistic investigations of various defect formation behaviors and their effects on the mechanical properties of high aluminum steels as well as Fe–Al binary alloys is demonstrated.

Abstract: We present an analysis, based upon atomistic simulation data, of the effect of Fe impurities on grain boundary migration in Al. The first step is the development of a new interatomic potential for Fe in Al. This potential provides an accurate description of Al–Fe liquid diffraction data and the bulk diffusivity of Fe in Al. We use this potential to determine the physical parameters in the Cahn–Lücke–Stüwe (CLS) model for the effect of impurities on grain boundary mobility. These include the heat of segregation of Fe to grain boundaries in Al and the diffusivity of Fe in Al. Using the simulation-parameterized CLS model, we predict the grain boundary mobility in Al in the presence of Fe as a function of temperature and Fe concentration. The order of magnitude and the trends in the mobility from the simulations are in agreement with existing experimental results.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: In this work we study the effects of C and Cr enrichment of <1 0 0> dislocation loops (DL) on their absorption and obstacle strength when interacting with an edge dislocation. To do so, we have i) developed a C-Cr cross potential based on density functional theory data as part of a ternary FeCrC interatomic potential; ii) performed exchange Monte Carlo simulations employing the developed interatomic potential to obtain the distribution of the solutes enriching the DL in the energetically optimum configurations; iii) performed large scale molecular dynamics simulations employing the interatomic potential to characterize the interaction between an edge dislocation line and the decorated DL. We found that the obstacle stress scales to the same obstacle strength regardless the DL density. On the other hand, we found that C, the level of Cr enrichment, loop size and interaction temperature have a significant impact on the obstacle strength and level of absorption of the loops. The presented results can be used to help parameterize and validate discrete dislocation dynamics codes and therein integrated constitutive laws to enable accounting for irradiation-induced chemical segregation effects.

Abstract: Machine learning interatomic potentials (MLIPs) for α-iron and carbon binary system have been constructed aiming for understanding the mechanical behavior of Fe–C steel and carbides. The MLIPs were trained using an extensive reference database produced by spin polarized density functional theory (DFT) calculations. The MLIPs reach the DFT accuracies in many important properties which are frequently engaged in Fe and Fe–C studies, including kinetics and thermodynamics of C in α-Fe with vacancy, grain boundary, and screw dislocation, and basic properties of cementite and cementite–ferrite interfaces. In conjunction with these MLIPs, the impact of C atoms on the mobility of screw dislocation at finite temperature, and the C-decorated core configuration of screw dislocation were investigated, and a uniaxial tensile test on a model with multiple types of defects was conducted.

Abstract: Machine learning interatomic potentials (MLIPs) for α-iron and carbon binary system have been constructed aiming for understanding the mechanical behavior of Fe–C steel and carbides. The MLIPs were trained using an extensive reference database produced by spin polarized density functional theory (DFT) calculations. The MLIPs reach the DFT accuracies in many important properties which are frequently engaged in Fe and Fe–C studies, including kinetics and thermodynamics of C in α-Fe with vacancy, grain boundary, and screw dislocation, and basic properties of cementite and cementite–ferrite interfaces. In conjunction with these MLIPs, the impact of C atoms on the mobility of screw dislocation at finite temperature, and the C-decorated core configuration of screw dislocation were investigated, and a uniaxial tensile test on a model with multiple types of defects was conducted.

Abstract: In steels, the interaction between screw dislocations and carbon solutes has a great influence on the yield strength. Fe-C potentials used in molecular dynamics (MD) simulations yield a poor description of screw dislocation properties-their core structure and Peierls barrier-compared to ab initio calculations. Here we combine two EAM potentials from the literature, which greatly improves dislocation property accuracy in FeC alloys. Using this hybrid potential, MD simulations of dislocation glide in random solid solutions confirm a powerful solute strengthening, caused by complex interaction processes. We analyze these processes in a model geometry, where a row of carbon atoms is inserted in the dislocation core with varying separations. We use a combination of MD simulations, minimum-energy path calculations, and a statistical model based on the harmonic transition state theory to explain the strengthening induced by carbon. We unveil that carbon disrupts the glide process, as unpinning requires the successive nucleation of two kink pairs. When solute separation is below about 100 Burgers vectors, the activation enthalpy of both kink pairs are markedly increased compared to pure iron, resulting in a strong dependence of the unpinning stress on solute spacing. Our simulations also suggest an effect of carbon spacing on the kink-pair activation entropy. This work provides elementary processes and parameters that will be useful for larger-scale models and, in particular, kinetic Monte Carlo simulations.

Abstract: Structural, elastic, and thermal properties of cementite (Fe3C) were studied using a modified embedded atom method (MEAM) potential for iron-carbon (Fe-C) alloys. Previously developed Fe and C single-element potentials were used to develop a Fe-C alloy MEAM potential, using a statistics-based optimization scheme to reproduce structural and elastic properties of cementite, the interstitial energies of C in bcc Fe, and heat of formation of Fe-C alloys in L12 and B1 structures. The stability of cementite was investigated by molecular dynamics simulations at high temperatures. The nine single-crystal elastic constants for cementite were obtained by computing total energies for strained cells. Polycrystalline elastic moduli for cementite were calculated from the single-crystal elastic constants of cementite. The formation energies of (001), (010), and (100) surfaces of cementite were also calculated. The melting temperature and the variation of specific heat and volume with respect to temperature were investigated by performing a two-phase (solid/liquid) molecular dynamics simulation of cementite. The predictions of the potential are in good agreement with first-principles calculations and experiments.

Abstract: The iron–carbon EAM potential that we have developed [Comput. Mater. Sci. 40 (2007) 119] was found to predict a saddle point slightly off the tetrahedral position. This problem was fixed by adding a Gaussian function to the Fe–C pairwise function, which does not change neither the position corresponding to the local energy minimum, i.e. the octahedral site, nor the energy of the saddle point. The potential energy landscape around the saddle point is now more realistic, without changing the dynamics properties of the former potential.

Abstract: Stainless steels found in real-world applications usually have some C content in the base Fe–Cr alloy, resulting in hard and dislocation-pinning carbides—Fe3C (cementite) and Cr23C6—being present in the finished steel product. The higher complexity of the steel microstructure has implications, for example, for the elastic properties and the evolution of defects such as Frenkel pairs and dislocations. This makes it necessary to re-evaluate the effects of basic radiation phenomena and not simply to rely on results obtained from purely metallic Fe–Cr alloys. In this report, an analytical interatomic potential parameterization in the Abell–Brenner–Tersoff form for the entire Fe–Cr–C system is presented to enable such calculations. The potential reproduces, for example, the lattice parameter(s), formation energies and elastic properties of the principal Fe and Cr carbides (Fe3C, Fe5C2, Fe7C3, Cr3C2, Cr7C3, Cr23C6), the Fe–Cr mixing energy curve, formation energies of simple C point defects in Fe and Cr, and the martensite lattice anisotropy, with fair to excellent agreement with empirical results. Tests of the predictive power of the potential show, for example, that Fe–Cr nanowires and bulk samples become elastically stiffer with increasing Cr and C concentrations. High-concentration nanowires also fracture at shorter relative elongations than wires made of pure Fe. Also, tests with Fe3C inclusions show that these act as obstacles for edge dislocations moving through otherwise pure Fe.

Abstract: Existing interatomic potentials for the iron-carbon system suffer from qualitative flaws in describing even the simplest of defects. In contrast to more accurate first-principles calculations, all previous potentials show strong bonding of carbon to overcoordinated defects (e.g., self-interstitials, dislocation cores) and a failure to accurately reproduce the energetics of carbon-vacancy complexes. Thus any results from their application in molecular dynamics to more complex environments are unreliable. The problem arises from a fundamental error in potential design—the failure to describe short-ranged covalent bonding of the carbon p electrons. We describe a resolution to the problem and present an empirical potential based on insights from density-functional theory, showing covalent-type bonding for carbon. The potential correctly describes the interaction of carbon and iron across a wide range of defect environments. It has the embedded atom method form and hence appropriate for billion atom molecular-dynamics simulations.

Abstract: A modified embedded-atom method (MEAM) interatomic potential for the Fe–C binary system has been developed using previous MEAM potentials of Fe and C. The potential parameters were determined by fitting to experimental information on the dilute heat of solution of carbon, the vacancy–carbon binding energy and its configuration, the location of interstitial carbon atoms and the migration energy of carbon atoms in body-centered cubic (bcc) Fe, and to a first-principles calculation result for the cohesive energy of a hypothetical NaCl-type FeC. The potential reproduces the known physical properties of carbon as an interstitial solute element in bcc Fe and face-centered cubic Fe very well. The applicability of this potential to atomistic approaches for investigating interactions between carbon interstitial solute atoms and other defects such as vacancies, dislocations and grain boundaries, and also for investigating the effects of carbon on various deformation and mechanical behaviors of iron is demonstrated.

Abstract: A quaternary element Modified Embedded Atom Method (MEAM) potential comprising Fe, Mn, Si, and C is developed by employing a hierarchical multiscale modeling paradigm to simulate low-alloy steels. Experimental information alongside first-principles calculations based on Density Functional Theory served as calibration data to upscale and develop the MEAM potential. For calibrating the single element potentials, the cohesive energy, lattice parameters, elastic constants, and vacancy and interstitial formation energies are used as target data. The heat of formation and elastic constants of binary compounds along with substitutional and interstitial formation energies serve as binary potential calibration data, while substitutional and interstitial pair binding energies aid in developing the ternary potential. Molecular dynamics simulations employing the developed potentials predict the thermal expansion coefficient, heat capacity, self-diffusion coefficients, and stacking fault energy for steel alloys comparable to those reported in the literature.

Abstract: Modified embedded-atom method (MEAM) interatomic potentials for Nb-C, Nb-N, Fe-Nb-C, and Fe-Nb-N systems have been developed based on the previously developed MEAM potentials for lower order systems. The potentials reproduce various fundamental physical properties (structural properties, elastic properties, thermal properties, and surface properties) of NbC and NbN, and interfacial energy between bcc Fe and NbC or NbN, in generally good agreement with higher-level calculations or experimental information. The applicability of the present potentials to atomic-level investigations to the precipitation behavior of complex-carbonitrides (Nb,Ti)(C,N) as well as NbC and NbN, and their effects on the mechanical properties of steels are also discussed.

Abstract: Modified embedded-atom method (MEAM) interatomic potentials for the Fe-Ti-C and Fe-Ti-N ternary systems have been developed based on the previously developed MEAM potentials for sub-unary and binary systems. An attempt was made to find a way to determine ternary potential parameters using the corresponding binary parameters. The calculated coherent interface properties, interfacial energy, work of separation and misfit strain energy between body-centered cubic Fe and NaCl-type TiC or TiN were reasonable when compared with relevant first-principles calculations under the same condition. The applicability of the present potentials for atomistic simulations to investigate nucleation kinetics of TiC or TiN precipitates and their effects on mechanical properties in steels is also demonstrated.

Abstract: High Entropy Alloys (HEA) attract attention as possible radiation resistant materials, a feature observed in some experiments that has been attributed to several unique properties of HEA, in particular to the disorder-induced reduced thermal conductivity and to the peculiar defect properties originating from the chemical complexity. To explore the origin of such behavior we study the early stages (less than 0.1 ns), of radiation damage response of a HEA using molecular dynamics simulations of collision cascades induced by primary knock-on atoms (PKA) with 10, 20 and 40 keV, at room temperature, on an idealized model equiatomic quinary fcc FeNiCrCoCu alloy, the corresponding "Average Atom" (AA) material, and on pure Ni. We include accurate corrections to describe short-range atomic interactions during the cascade. In all cases the average number of defects in the HEA is lower than for pure Ni, which has been previously used to help claiming that HEA is radiation resistant. However, simulated defect evolution during primary damage, including the number of surviving Frenkel Pairs, and the defect cluster size distributions are nearly the same in all cases, within our statistical uncertainty. The number of surviving FP in the alloy is predicted fairly well by analytical models of defect production in pure materials. All of this indicates that the origin of radiation resistance in HEAs as observed in experiments may not be related to a reduction in primary damage due to chemical disorder, but is probably caused by longer-time defect evolution.

Abstract: A set of embedded atom method model interatomic potentials is presented to represent a high-entropy alloy with five components. The set is developed to resemble but not model precisely face-centered cubic (fcc) near-equiatomic mixtures of Fe–Ni–Cr–Co–Cu. The individual components have atomic sizes deviating up to 3%. With the heats of mixing of all binary equiatomic random fcc mixtures being less than 0.7 kJ/mol and the corresponding value for the quinary being −0.0002 kJ/mol, the potentials predict the random equiatomic fcc quinary mixture to be stable with respect to phase separation or ordering and with respect to bcc and hcp random mixtures. The details of lattice distortion, strain, and stress states in this phase are reported. The standard deviation in the individual nearest neighbor bond lengths was found to be in the range of 2%. Most importantly, individual atoms in the alloy were found to be under atomic strains up to 0.5%, corresponding to individual atomic stresses up to several GPa.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: The single-phase equiatomic CoCrFeMnNi alloy is a random solid solution of five elements on the face-centered cubic lattice, whose pure constituents crystallize in very different structures and exhibit diverse magnetic properties. Due to the randomness of the alloy, 80% of nearest neighbor bonds are between unlike elements and thus the details of bonding in pure structures are less important. The elastic moduli of this alloy give rise to small Cauchy pressure C₁₂ − C₄₄, which suggests that the dominant part of bonding may be described by a simple pair potential. We test this hypothesis by developing a long-range Lennard-Jones potential in which the equilibrium crystal structures of pure constituents are taken as reference. The standard mixing rules for regular solutions are then adopted to obtain parameters for bonds between unlike elements in the quinary system. The transferability of this potential to quaternary CoCrFeNi, ternary CoCrNi, and binary FeNi alloys is investigated and the predictions compared with experiments and density functional theory calculations. By sampling over a large number of random configurations, we investigate the effect of compositional randomness on misfit volumes, energies of point defects and stacking faults, and the dislocation friction stresses experienced by moving edge and screw dislocations.

Abstract: Although high-entropy alloys (HEAs) are attracting interest, the physical metallurgical mechanisms related to their properties have mostly not been clarified, and this limits wider industrial applications, in addition to the high alloy costs. We clarify the physical metallurgical reasons for the materials phenomena (sluggish diffusion and micro-twining at cryogenic temperatures) and investigate the effect of individual elements on solid solution hardening for the equiatomic CoCrFeMnNi HEA based on atomistic simulations (Monte Carlo, molecular dynamics and molecular statics). A significant number of stable vacant lattice sites with high migration energy barriers exists and is thought to cause the sluggish diffusion. We predict that the hexagonal close-packed (hcp) structure is more stable than the face-centered cubic (fcc) structure at 0 K, which we propose as the fundamental reason for the micro-twinning at cryogenic temperatures. The alloying effect on the critical resolved shear stress (CRSS) is well predicted by the atomistic simulation, used for a design of non-equiatomic fcc HEAs with improved strength, and is experimentally verified. This study demonstrates the applicability of the proposed atomistic approach combined with a thermodynamic calculation technique to a computational design of advanced HEAs.

Abstract: High entropy alloys (HEA) composition-structure relationships are crucial for guiding their design and applications. Here, we use a combined experimental and molecular dynamics (MD) approach to investigate phase formation during physical vapor deposition (PVD) of CoFeNiTi_x and CrFeNiTi_x HEA thin films. We vary titanium molar ratio from 0 to 1 to understand the role of a larger element in the alloy mixture. The experiments show that a high titanium content favors amorphous phase formation in the samples produced by magnetron co-sputtering. In contrast, a low titanium content results in the formation of a face-centered cubic (FCC) structure in both HEA families. This effect of titanium content on the stability of the amorphous and FCC phases is reproduced in PVD MD simulations. The threshold titanium molar ratio is identified to be ~0.53 and ~0.16 for the CoFeNiTi_x and CrFeNiTi_x films in the experiments, and ~0.53 and ~0.53 in the MD simulations. In addition, the atomistic modeling allows for energy versus volume calculations with increasing titanium content, which demonstrate the stabilization of the amorphous phase with respect to crystalline structures. To isolate the effect of atomic sizes, additional simulations are performed using an average-atom model, which disregards differences in atomic radii while preserving the average properties of the alloy. In these simulations, the energetic stability of the amorphous phase disappears. The combined experimental and simulation results demonstrate that the formation of the amorphous phase in HEA thin films generated by PVD is directly caused by the atomic size difference.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.

Abstract: Complex concentrated alloys (CCAs) are a new generation of metallic alloys composed of three or more principal elements with physical and mechanical properties that can be tuned by adjusting their compositions. The extensive compositional workspace of CCAs makes it impractical to perform a comprehensive search for a specific material property using experimental measurements. The use of computational methods can rapidly narrow down the search span, improving the efficiency of the design process. We carried out a high-throughput parameterization of modified embedded atom method (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics.