Abstract: Plastic deformation and fracture of FCC metals involve the formation of stable or unstable stacking faults (SFs) on (111) plane. Examples include dislocation cross-slip and dislocation nucleation at interfaces and near crack tips. The stress component normal to (111) plane can strongly affect the SF energy when the stress magnitude reaches several to tens of GPa. We conduct a series of DFT calculations of SF energies in six FCC metals: Al, Ni, Cu, Ag, Au, and Pt. The results show that normal compression significantly increases the stable and unstable SF energies in all six metals, while normal tension decreases them. The SF formation is accompanied by inelastic expansion in the normal direction. The DFT calculations are compared with predictions of several representative classical and machine-learning interatomic potentials. Many potentials fail to capture the correct stress effect on the SF energy, often predicting trends opposite to the DFT calculations. Possible ways to improve the ability of potentials to represent the stress effect on SF energy are discussed.

Abstract: Plastic deformation and fracture of FCC metals involve the formation of stable or unstable stacking faults (SFs) on (111) plane. Examples include dislocation cross-slip and dislocation nucleation at interfaces and near crack tips. The stress component normal to (111) plane can strongly affect the SF energy when the stress magnitude reaches several to tens of GPa. We conduct a series of DFT calculations of SF energies in six FCC metals: Al, Ni, Cu, Ag, Au, and Pt. The results show that normal compression significantly increases the stable and unstable SF energies in all six metals, while normal tension decreases them. The SF formation is accompanied by inelastic expansion in the normal direction. The DFT calculations are compared with predictions of several representative classical and machine-learning interatomic potentials. Many potentials fail to capture the correct stress effect on the SF energy, often predicting trends opposite to the DFT calculations. Possible ways to improve the ability of potentials to represent the stress effect on SF energy are discussed.

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: We present a study on the transport and material properties of aluminum spanning from ambient to warm dense matter conditions using a machine-learned interatomic potential (ML-IAP). Prior research has utilized ML-IAPs to simulate phenomena in warm dense matter, but these potentials have often been calibrated for a narrow range of temperatures and pressures. In contrast, we train a single ML-IAP over a wide range of temperatures, using density functional theory molecular dynamics (DFT-MD) data. Our approach overcomes the computational limitations of DFT-MD simulations, enabling us to study the transport and material properties of matter at higher temperatures and longer time scales. We demonstrate the ML-IAP transferability across a wide range of temperatures using molecular dynamics by examining the ionic part of thermal conductivity, shear viscosity, self-diffusion coefficient, sound velocity, and structure factor of aluminum up to about 60000 K, where we find good agreement with previous theoretical data.

Abstract: Interatomic potentials constitute the key component of large-scale atomistic simulations of materials. The recently proposed physically informed neural network (PINN) method combines a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential applicable to both metals and nonmetals. In this paper, we present a modified version of the PINN method that accelerates the potential training process and further improves the transferability of PINN potentials to unknown atomic environments. As an application, a modified PINN potential for Al has been developed by training on a large database of electronic structure calculations. The potential reproduces the reference first-principles energies within 2.6 meV per atom and accurately predicts a wide spectrum of physical properties of Al. Such properties include, but are not limited to, lattice dynamics, thermal expansion, energies of point and extended defects, the melting temperature, the structure and dynamic properties of liquid Al, the surface tensions of the liquid surface and the solid-liquid interface, and the nucleation and growth of a grain boundary crack. Computational efficiency of PINN potentials is also discussed.

Abstract: Large-scale atomistic computer simulations of materials heavily rely on interatomic potentials predicting the energy and Newtonian forces on atoms. Traditional interatomic potentials are based on physical intuition but contain few adjustable parameters and are usually not accurate. The emerging machine-learning (ML) potentials achieve highly accurate interpolation within a large DFT database but, being purely mathematical constructions, suffer from poor transferability to unknown structures. We propose a new approach that can drastically improve the transferability of ML potentials by informing them of the physical nature of interatomic bonding. This is achieved by combining a rather general physics-based model (analytical bond-order potential) with a neural-network regression. This approach, called the physically informed neural network (PINN) potential, is demonstrated by developing a general-purpose PINN potential for Al. We suggest that the development of physics-based ML potentials is the most effective way forward in the field of atomistic simulations.

Abstract: Force fields developed with machine learning methods in tandem with quantum mechanics are beginning to find merit, given their (i) low cost, (ii) accuracy, and (iii) versatility. Recently, we proposed one such approach, wherein, the vectorial force on an atom is computed directly from its environment. Here, we discuss the multistep workflow required for their construction, which begins with generating diverse reference atomic environments and force data, choosing a numerical representation for the atomic environments, down selecting a representative training set, and lastly the learning method itself, for the case of Al. The constructed force field is then validated by simulating complex materials phenomena such as surface melting and stress–strain behavior, that truly go beyond the realm of ab initio methods, both in length and time scales. To make such force fields truly versatile an attempt to estimate the uncertainty in force predictions is put forth, allowing one to identify areas of poor performance and paving the way for their continual improvement.

Abstract: The behavior of an atom in a molecule, liquid, or solid is governed by the force it experiences. If the dependence of this vectorial force on the atomic chemical environment can be learned efficiently with high fidelity from benchmark reference results—using "big-data" techniques, i.e., without resorting to actual functional forms—then this capability can be harnessed to enormously speed up in silico materials simulations. The present contribution provides several examples of how such a force field for Al can be used to go far beyond the length-scale and time-scale regimes presently accessible using quantum-mechanical methods. It is argued that pathways are available to systematically and continuously improve the predictive capability of such a learned force field in an adaptive manner, and that this concept can be generalized to include multiple elements.

Abstract: An interatomic potential for Al is developed within the third generation of the charge optimized many-body (COMB3) formalism. The database used for the parameterization of the potential consists of experimental data and the results of first-principles and quantum chemical calculations. The potential exhibits reasonable agreement with cohesive energy, lattice parameters, elastic constants, bulk and shear modulus, surface energies, stacking fault energies, point defect formation energies, and the phase order of metallic Al from experiments and density functional theory. In addition, the predicted phonon dispersion is in good agreement with the experimental data and first-principles calculations. Importantly for the prediction of the mechanical behavior, the unstable stacking fault energetics along the <1 2 -1> direction on the (1 1 1) plane are similar to those obtained from first-principles calculations. The polycrsytal when strained shows responses that are physical and the overall behavior is consistent with experimental observations.

Abstract: Interaction for both pure Al and Al–U alloys of the MEAM type are developed. The obtained Al interatomic potential assures its compatibility with the details of the framework presently adopted. The Al–U interaction fits various properties of the Al2U, Al3U and Al4U intermetallics. The potential verifies the stability of the intermetallic structures in a temperature range compatible with that observed in the phase diagram, and also takes into account the greater stability of these structures relative to others that are competitive in energy. The intermetallics are characterized by calculating elastic and thermal properties and point defect parameters. Molecular dynamics simulations show a growth of the Al3U intermetallic in the Al/U interface in agreement with experimental evidence.

Abstract: An accurate description of the thermoelastic response of solids is central to classical simulations of compression- and deformation-induced condensed matter phenomena. To achieve the correct thermoelastic description in classical simulations, a new approach is presented for determining interatomic potentials. In this two-step approach, values of atomic volume and the second- and third-order elastic constants measured at room temperature are extrapolated to T = 0 K using classical thermo-mechanical relations that are thermodynamically consistent. Next, the interatomic potentials are fitted to these T = 0 K pseudo-values. This two-step approach avoids the low-temperature quantum regime, providing consistency with the assumptions of classical simulations and enabling the correct thermoelastic response to be recovered in simulations at room temperature and higher. As an example of our approach, an EAM potential was developed for aluminum, providing significantly better agreement with thermoelastic data compared with previous EAM potentials. The approach presented here is quite general and can be used for other potential types as well, the key restriction being the inapplicability of classical atomistic simulations when quantum effects are important.

Abstract: Fast heating of target material by femtosecond laser pulse (fsLP) with duration τL~40–100fs results in the formation of thermomechanically stressed state. Its unloading may cause frontal cavitation of subsurface layer at a depth of 50nm for Al and 100nm for Au. The compression wave propagating deep into material hits the rear-side of the target with the formation of rarefaction wave. The last may produce cracks and rear-side spallation. Results of MD simulations of ablation and spallation of Al and Au metals under action fsLP are presented. It is shown that the used EAM potentials (Mishin et al. and our new one) predict the different ablation and spallation thresholds on absorbed fluence in Al: ablation Fa=6065mJ/cm2 and spallation Fs=120190mJ/cm2, where numbers in brackets show the corresponding values for Mishin potential. The strain rate in spallation zone was 4.3×10^9 1/s at spallation threshold. Simulated spall strength of Al is 7.48.7GPa, that is noticeably less than 10.314GPa obtained from acoustic approximation with the use of velocity pullback on velocity profile of free rear surface. The ablation threshold Fa≈120mJ/cm2 and crater depth of 110nm are obtained in MD simulations of gold with the new EAM potential. They agree well with experiment.

Abstract: We investigate the application of embedded atom method (EAM) interatomic potentials in the study of crystallization kinetics from deeply undercooled melts, focusing on the fcc metals Al and Cu. For this application, it is important that the EAM potential accurately reproduces melting properties and liquid structure, in addition to the crystalline properties most commonly fit in its development. To test the accuracy of previously published EAM potentials and to guide the development of new potential in this work, first-principles calculations have been performed and new experimental measurements of the Al and Cu liquid structure factors have been undertaken by X-ray diffraction. We demonstrate that the previously published EAM potentials predict a liquid structure that is too strongly ordered relative to measured diffraction data. We develop new EAM potentials for Al and Cu to improve the agreement with the first-principles and measured liquid diffraction data. Furthermore, we calculate liquid-phase diffusivities and find that this quantity correlates well with the liquid structure. Finally, we perform molecular dynamics simulations of crystal nucleation from the melt during quenching at constant cooling rate. We find that EAM potentials, which predict the same zero-temperature crystal properties but different liquid structures, can lead to quite different crystallization kinetics. More interestingly, we find that two potentials predicting very similar equilibrium solid and liquid properties can still produce very different crystallization kinetics under far-from-equilibrium conditions characteristic of the rapid quenching simulations employed here.

Abstract: A new Al potential with improved stacking fault energy is constructed using the force-matching method. The potential is fitted to an ab initio forces database and various experimental data. By using a slightly larger cut-off, we found that the new potential gives the relaxed stacking fault energy in the experimental range without changing the excellent thermal and surface properties of the original force-matching Al potential given by Ercolessi and Adams (1994 Europhys. Lett. 26 583).

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: Modified embedded atom method (MEAM) potentials for fcc elements Cu, Ag, Au, Ni, Pd, Pt, Al, and Pb have been newly developed using the original first nearest-neighbor MEAM and the recently developed second nearest-neighbor MEAM formalisms. It was found that the original MEAM potentials for fcc elements show some critical shortcomings such as structural instability and incorrect surface reconstructions on (100), (110), and/or (111) surfaces. The newly developed MEAM potentials solve most of the problems and describe the bulk properties (elastic constants, structural energy differences), point defect properties (vacancy and interstitial formation energy and formation volume, activation energy of vacancy diffusion), planar defect properties (stacking fault energy, surface energy, surface relaxation and reconstruction), and thermal properties (thermal expansion coefficients, specific heat, melting point, heat of melting) of the fcc elements considered, in good agreement with relevant experimental information. It has been shown that in the MEAM the degree of many-body screening (C_min) is an important material property and that structural stability at finite temperatures should be included as a checkpoint during development of semiempirical potentials.

Abstract: Semiempirical interatomic potentials have been developed for Al, α−Ti, and γ−TiAl within the embedded atom method (EAM) formalism by fitting to a large database of experimental as well as ab initio data. The ab initio calculations were performed by the linearized augmented plane wave (LAPW) method within the density functional theory to obtain the equations of state for a number of crystal structures of the Ti-Al system. Some of the calculated LAPW energies were used for fitting the potentials while others for examining their quality. The potentials correctly predict the equilibrium crystal structures of the phases and accurately reproduce their basic lattice properties. The potentials are applied to calculate the energies of point defects, surfaces, and planar faults in the equilibrium structures. Unlike earlier EAM potentials for the Ti-Al system, the proposed potentials provide a reasonable description of the lattice thermal expansion, demonstrating their usefulness for molecular-dynamics and Monte Carlo simulations at high temperatures. The energy along the tetragonal deformation path (Bain transformation) in γ−TiAl calculated with the EAM potential is in fairly good agreement with LAPW calculations. Equilibrium point defect concentrations in γ−TiAl are studied using the EAM potential. It is found that antisite defects strongly dominate over vacancies at all compositions around stoichiometry, indicating that γ−TiAl is an antisite disorder compound, in agreement with experimental data.

Abstract: A combined theoretical and experimental approach has been used to study nanoscale CoFe/Cu/CoFe multilayer films grown by sputter deposition. Such films have applications in sensors that utilize the giant magnetoresistance effect, for example, read heads in high-density information storage devices. Atomistic simulations based on a molecular dynamics approach and an alloy form of the embedded atom method have been developed to accurately model the sputter deposition of the CoFe/Cu/CoFe multilayers. The simulations show that relatively flat interfaces are formed because of the energetic deposition conditions. However, significant intermixing at the CoFe-on-Cu interface, but not at the Cu-on-CoFe interface, was observed. An abnormal Fe depletion zone is also revealed at the CoFe-on-Cu interface. A three-dimensional atom probe method has been used for a nanoscale chemical analysis of the films. It provided direct verification of the simulations. The simulations have then been used to understand the mechanism responsible for the formation of the intermixing defects observed in the multilayers. A novel deposition technique is proposed which reduces both interfacial mixing and Fe depletion by controlling the incident adatom energies.

Abstract: Model interaction potentials for real materials are generally optimized with respect to only those experimental properties that are easily evaluated as mechanical averages [e.g., elastic constants (at T=0 K), static lattice energies, and liquid structure]. For such potentials, agreement with experiment for the nonmechanical properties, such as the melting point, is not guaranteed and such values can deviate significantly from experiment. We present a method for reparametrizing any model interaction potential of a real material to adjust its melting temperature to a value that is closer to its experimental melting temperature. This is done without significantly affecting the mechanical properties for which the potential was modeled. This method is an application of Gibbs-Duhem integration [D. Kofke, Mol. Phys. 78, 1331 (1993)]. As a test we apply the method to an embedded atom model of aluminum [J. Mei and J.W. Davenport, Phys. Rev. B 46, 21 (1992)] for which the melting temperature for the thermodynamic limit is 826.4±1.3 K—somewhat below the experimental value of 933 K. After reparametrization, the melting temperature of the modified potential is found to be 931.5±1.5 K.

Abstract: We demonstrate an approach to the development of many-body interatomic potentials for monoatomic metals with improved accuracy and reliability. The functional form of the potentials is that of the embedded-atom method, but the interesting features are as follows: (1) The database used for the development of a potential includes both experimental data and a large set of energies of different alternative crystalline structures of the material generated by ab initio calculations. We introduce a rescaling of interatomic distances in an attempt to improve the compatibility between experimental and ab initio data. (2) The optimum parametrization of the potential for the given database is obtained by alternating the fitting and testing steps. The testing step includes a comparison between the ab initio structural energies and those predicted by the potential. This strategy allows us to achieve the best accuracy of fitting within the intrinsic limitations of the potential model. Using this approach we develop reliable interatomic potentials for Al and Ni. The potentials accurately reproduce basic equilibrium properties of these metals, the elastic constants, the phonon-dispersion curves, the vacancy formation and migration energies, the stacking fault energies, and the surface energies. They also predict the right relative stability of different alternative structures with coordination numbers ranging from 12 to 4. The potentials are expected to be easily transferable to different local environments encountered in atomistic simulations of lattice defects.

Abstract: A detailed derivation of the simplest form of the effective medium theory for bonding in metallic systems is presented, and parameters for the fcc metals Ni, Pd, Pt, Cu, Ag and Au are given. The derivation of parameters is discussed in detail to show how new parameterizations can be made. The method and the parameterization is tested for a number of surface and bulk problems. In particular we present calculations of the energetics of metal atoms deposited on metal surfaces. The calculated energies include heats of adsorption, energies of overlayers, both pseudomorphic and relaxed, as well as energies of atoms alloyed into the first surface layer.

Abstract: We present a new scheme to extract numerically "optimal" interatomic potentials from large amounts of data produced by first-principles calculations. The method is based on fitting the potential to ab initio atomic forces of many atomic configurations, including surfaces, clusters, liquids and crystals at finite temperature. The extensive data set overcomes the difficulties encountered by traditional fitting approaches when using rich and complex analytic forms, allowing to construct potentials with a degree of accuracy comparable to that obtained by ab initio methods. A glue potential for aluminium obtained with this method is presented and discussed.

Abstract: An expression is derived for the total energy of a system of interacting atoms based on an ansatz for the total electron density of the system as a superposition of atom densities taken from calculations for the atoms embedded in a homogeneous electron gas. This leads to an expression for the interaction energy in terms of the embedding energy of the atoms in a homogeneous electron gas, and corrections accounting, for instance, for the d-d hybridization in the transition metals. The density of the homogeneous electron gas is chosen as the average of the density from the surrounding atoms. Due to the variational property of the total-energy functional, the errors in the interaction energy are second order in the deviation of the ansatz density from the true ground-state value. The applicability of the approach is illustrated by calculations of the cohesive properties of some simple metals and all the 3d transition metals. The interaction energy can be expressed in a form simple enough to allow calculations for low-symmetry systems and is very well suited for simulations of time-dependent and finite-temperature problems. Preliminary results for the phonon-dispersion relations and the surface energies and relaxations for Al are used to illustrate the versatility of the approach. The division of the total energy into a density-dependent part, an electrostatic "pair-potential" part, and a hybridization part provides a very simple way of understanding a number of these phenomena.

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: A detailed derivation of the simplest form of the effective medium theory for bonding in metallic systems is presented, and parameters for the fcc metals Ni, Pd, Pt, Cu, Ag and Au are given. The derivation of parameters is discussed in detail to show how new parameterizations can be made. The method and the parameterization is tested for a number of surface and bulk problems. In particular we present calculations of the energetics of metal atoms deposited on metal surfaces. The calculated energies include heats of adsorption, energies of overlayers, both pseudomorphic and relaxed, as well as energies of atoms alloyed into the first surface layer.

Abstract: Metal-semiconductor nanostructures are key objects for multifunctional electronics and optical design. We report a new interatomic potential for atomistic simulation of a ternary Si-Au-Al system. The development procedure was based on the force-matching method that allowed us to create the potential without use of experimental data at the fitting. Extensive validation including elastic, thermophysical and defect properties demonstrates a wide range of the potential applicability. Special attention was paid to the description of the silicon-metal alloys in liquid and amorphous states. We used the new potential for study of crystallization and glass transition in the undercooled melt. The simulation results revealed the beneficial conditions for the formation of the unique metal-semiconductor nanocrystalline structure, which is highly important for various applications in the field of nanophotonics.

Abstract: Kinking is a deformation mechanism ubiquitous to layered systems, ranging from the nanometer scale in layered crystalline solids, to the kilometer scale in geological formations. Herein, we demonstrate its origins in the former through multiscale experiments and atomistic simulations. When compressively loaded parallel to their basal planes, layered crystalline solids first buckle elastically, then nucleate atomic-scale, highly stressed ripplocation boundaries – a process driven by redistributing strain from energetically expensive in-plane bonds to cheaper out-of-plane bonds. The consequences are far reaching as the unique mechanical properties of layered crystalline solids are highly dependent upon their ability to deform by kinking. Moreover, the compressive strength of numerous natural and engineered layered systems depends upon the ease of kinking or lack there of.

Abstract: Bond-order potentials have been developed for the Ti₃AlC₂ and Ti₃SiC₂ MAX phases within the Tersoff formalism. Parameters were determined by independently considering each interatomic interaction present in the system and fitting them to the relevant structural, elastic, and defect properties for a number of unary, binary, and ternary structures. A number of material properties, including those not used in the fitting procedure, are reproduced with a high degree of accuracy when compared to experiment and ab initio calculations. Additionally, well-documented MAX phase behaviors such as plastic anisotropy and kinking nonlinear elasticity are demonstrated to be captured by the potentials. As a first highly accurate atomistic model for MAX phases, these potentials provide the opportunity to study some of the fundamental mechanisms behind unique MAX phase properties. Additionally, the fitting procedure employed is highly transferable and should be applicable to numerous other MAX phases.

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: Ni–Al–Co is a promising system for ferromagnetic shape memory applications. This paper reports on the development of a ternary embedded-atom potential for this system by fitting to experimental and first-principles data. Reasonably good agreement is achieved for physical properties between values predicted by the potential and values known from experiment and/or first-principles calculations. The potential reproduces basic features of the martensitic phase transformation from the B2-ordered high-temperature phase to a tetragonal CuAu-ordered low-temperature phase. The compositional and temperature ranges of this transformation and the martensite microstructure predicted by the potential compare well with existing experimental data. These results indicate that the proposed potential can be used for simulations of the shape memory effect in the Ni–Al–Co system.

Abstract: Interatomic potentials for pure Co and the Co–Al binary system have been developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM) potential formalism. The potentials can describe various fundamental physical properties of the relevant materials in good agreement with experimental information. The potential is utilized to an atomistic computation of interfacial properties between fcc-Co (γ) and Co₃Al (γ′) phases. It is found that the anisotropy in the γ/γ′ interfacial energy is relatively small and leaves a room for further modification by alloying other elements. The applicability of the atomistic approach to an elaborate alloy design of advanced Co-based superalloys through the investigation of the effect of alloying elements on interfacial and elastic properties is discussed.

Abstract: Interatomic potentials of the embedded atom and embedded defect type were derived for the Co–Al system by empirical fitting to the properties of the B2 CoAl phase. The embedded atom potentials reproduced most of the properties needed, except that, in using this method, the elastic constants cannot be fitted exactly because CoAl has a negative Cauchy pressure. In order to overcome this limitation and fit the elastic constants correctly, angular forces were added using the embedded defect technique. The effects of angular forces to the embedded atom potentials were seen in the elastic constants, particularly C44. Planar fault energies changed up to 30% in the 110 and 112 γ surfaces and the vacancy formation energies were also very sensitive to the non-central forces. Dislocation core structures and Peierls stress values were computed for the 〈100〉 and 〈111〉 dislocations without angular forces. As a general result, the dislocations with a planar core moved for critical stress values below 250 MPa in contrast with the nonplanar cores for which the critical stress values were above 1500 MPa. The easiest dislocations to move were the 1/2〈111〉 edge superpartials, and the overall preferred slip plane was 110. These results were compared with experimental observations in CoAl and previously simulated dislocations in NiAl.

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: Molecular dynamics simulations were used to study the deposition and growth of a thin film of high-entropy CoCrFeMnNi alloy on an Al(100) substrate. Interatomic interactions were modeled using Morse potentials, which were developed with mixing rules adopted for regular solutions. A total of 50000 atoms with an incident energy of 10 eV were deposited for 100 ns, forming a film with a thickness of 6.1 nm. The resulting film exhibited face-centered cubic, body-centered cubic, hexagonal close-packed, and amorphous phases. Radial distribution function analysis determined the nearest neighbor distances and lattice parameters, which showed good agreement with experimental data.

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: 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: Interatomic potentials for the Ni-Co binary and Ni-Al-Co ternary systems have been developed on the basis of the second nearest-neighbor modified embedded-atom method (2NN MEAM) formalism. The potentials describe structural, thermodynamic, deformation and defect properties of solid solution phases or compound phases in reasonable agreements with experiments or first-principles calculations. The results demonstrate the transferability of the potentials and their applicability to large-scale atomistic simulations to investigate the effect of an alloying element, cobalt, on various microstructural factors related to mechanical properties of Ni-based superalloys on an atomic scale.

Abstract: Ni–Al–Co is a promising system for ferromagnetic shape memory applications. This paper reports on the development of a ternary embedded-atom potential for this system by fitting to experimental and first-principles data. Reasonably good agreement is achieved for physical properties between values predicted by the potential and values known from experiment and/or first-principles calculations. The potential reproduces basic features of the martensitic phase transformation from the B2-ordered high-temperature phase to a tetragonal CuAu-ordered low-temperature phase. The compositional and temperature ranges of this transformation and the martensite microstructure predicted by the potential compare well with existing experimental data. These results indicate that the proposed potential can be used for simulations of the shape memory effect in the Ni–Al–Co system.

Abstract: Classical effective potentials are indispensable for any large-scale atomistic simulations, and the relevance of simulation results crucially depends on the quality of the potentials used. For complex alloys such as quasicrystals, however, realistic effective potentials are almost non-existent. We report here our efforts to develop effective potentials especially for quasicrystalline alloy systems. We use the so-called force-matching method, in which the potential parameters are adapted so as to reproduce the forces and energies optimally in a set of suitably chosen reference configurations. These reference data are calculated with ab-initio methods. As a first application, embedded-atom method potentials for decagonal Al–Ni–Co, icosahedral Ca–Cd, and both icosahedral and decagonal Mg–Zn quasicrystals have been constructed. The influence of the potential range and degree of specialization on the accuracy and other properties is discussed and compared.

Abstract: Classical effective potentials are indispensable for any large-scale atomistic simulations, and the relevance of simulation results crucially depends on the quality of the potentials used. For complex alloys such as quasicrystals, however, realistic effective potentials are almost non-existent. We report here our efforts to develop effective potentials especially for quasicrystalline alloy systems. We use the so-called force-matching method, in which the potential parameters are adapted so as to reproduce the forces and energies optimally in a set of suitably chosen reference configurations. These reference data are calculated with ab-initio methods. As a first application, embedded-atom method potentials for decagonal Al–Ni–Co, icosahedral Ca–Cd, and both icosahedral and decagonal Mg–Zn quasicrystals have been constructed. The influence of the potential range and degree of specialization on the accuracy and other properties is discussed and compared.

Abstract: Ordered L1₂ γ′ Ni₃Al intermetallics are essential strengthening components to maintain the high strength of Ni-based superalloys and recently developed high entropy alloys at elevated temperatures. Under service conditions, structural disorder is usually encountered in these intermetallics, resulting in significant loss of their strengthening functionality. Thus, retaining the degree of order of the L1₂ intermetallics is vital for their long-term reliability and serviceability. In this study, atomistic simulations and rate equation analysis are employed to highlight a notable enhancement in the reordering ability of L1₂ intermetallics by incorporating multiple principal elements. Specifically, we examine the effects of Co and Ti addition on the irradiation-induced disordering and kinetic reordering process of L1₂ intermetallics. Our results reveal that the incorporation of Ti in the Al sublattice can maintain comparable disordering resistance as Ni₃Al. Better yet, the introduction of Ti or Co fosters vacancy migration, which accelerates the kinetic reordering rate during the defect diffusion stage. A synergistic effect of Ti and Co in promoting kinetic reordering is also observed. Our work thus suggests a promising approach for designing irradiation-resistant multicomponent intermetallics, which can retain a high degree of structural order under irradiation with chemical disorder contributed by desirable compositions.

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: 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.