Fcc Aluminum Research Articles

SYNTHESIZING OF AN ALUMINUM ALLOY RICH IN IRON AND SILICON BY SURFACING WITH A CONSUMABLE ELECTRODE

Developing lightweight, high-strength materials is an important technological problem of the present decade. However, alloying with expensive elements is mainly used to increase the strength of structural materials. In contrast, aluminum alloys with a specific ratio of silicon and iron show very high mechanical properties. This work aims to develop a technology for synthesizing an aluminium-based alloy with a high content of iron and silicon, consisting mainly of intermetallic phases and having high strength and hardness. The additive technology method of surfacing with a consumable electrode produced the alloy. The ratio of the initial components, meticulously determined, led to the precise chemical composition of the alloy. As a result of the synthesis, an ingot with a uniform microstructure and insignificant porosity, a testament to the careful process, was obtained. At room temperature, the alloy has a phase composition of 42.6% β-phase, 43.4% θ-phase and 13.5% FCC-phase. Phases β and θ are large particles between which the FCC aluminum phase is located. The hardness of the intermetallic β/θ is 450.8±5 HV1, FCC aluminum has a hardness of 92.5 HV1. This research has the potential to inspire further developments in materials science and engineering.

Modeling of Mode I crack-tip dislocation nucleation in three FCC materials: Ni, Cu and Al

An accurate estimation of the critical stress intensity factor for crack tip dislocation nucleation under Mode I loading is of great importance to determine whether a material is intrinsically ductile or not. Here, shear displacements and energy change at crack tip in FCC nickel, copper and aluminum are investigated during Mode I fracture process using atomistic simulations. In light of our simulation results, a new shear resistance model is formulated by a general Fourier expansion with coefficients identified by the computed energy curve. The new model involving the step formation energy which can be regarded as a new parameter and unstable stable stacking fault energy, reduces to Rice theory if no step exists. The criterion for nucleation is developed based on the idea that crack tip behaviors are controlled by the shear resistance and the maximum point serves as an obstacle to conquer. The predictions of the critical shear displacement corresponding to maximum shear resistance position and the critical nucleation energy show good agreement with simulation results. In addition, the new model can be further utilized to study the effect of complex stress state on Mode I crack tip dislocation nucleation.

Modeling of shock wave propagation in porous magnesium based on artificial neural network

Data transfer from the level of atomistic simulations to the level of continuum modeling is one of the urgent problems in the mechanics of materials. In this work, we perform multiple molecular dynamics (MD) simulations of the uniaxial (along different crystallographic directions) and volumetric (isotropic) compression of porous HCP magnesium single crystals in order to study the atomistic processes of the plastic deformation of anisotropic porous material and to create a reference dataset (strain dependencies of stresses, porosity and dislocation density at different temperatures and initial porosities). The MD data are used to train two artificial neural networks (ANNs): the first ANN is a surrogate of the constitutive equation of porous magnesium, while the second ANN describes the dislocation nucleation/emission as the onset of plastic flow. In contrast to the previously considered case of porous FCC aluminum, the present approach takes into account the anisotropy of the matrix material. The ANN-based constitutive equation is successfully used within the continuum mechanics model for numerical study on the shock wave structure in porous magnesium in comparison with direct MD simulation of the shock wave problem.

Multiscale modelling of biomolecular corona formation on metallic surfaces.

In the realm of food industry, the choice of non-consumable materials used plays a crucial role in ensuring consumer safety and product quality. Aluminum is widely used in food packaging and food processing applications, including dairy products. However, the interaction between aluminum and milk content requires further investigation to understand its implications. In this work, we present the results of multiscale modelling of the interaction between various surfaces, that is (100), (110), and (111), of fcc aluminum with the most abundant milk proteins and lactose. Our approach combines atomistic molecular dynamics, a coarse-grained model of protein adsorption, and kinetic Monte Carlo simulations to predict the protein corona composition in the deposited milk layer on aluminum surfaces. We consider a simplified model of milk, which is composed of the six most abundant milk proteins found in natural cow milk and lactose, which is the most abundant sugar found in dairy. Through our study, we ranked selected proteins and lactose adsorption affinities based on their corresponding interaction strength with aluminum surfaces and predicted the content of the naturally forming biomolecular corona. Our comprehensive investigation sheds light on the implications of aluminum in food processing and packaging, particularly concerning its interaction with the most abundant milk proteins and lactose. By employing a multiscale modelling approach, we simulated the interaction between metallic aluminum surfaces and the proteins and lactose, considering different crystallographic orientations. The results of our study provide valuable insights into the mechanisms of lactose and protein deposition on aluminum surfaces, which can aid in the general understanding of protein corona formation.

Trajectory sampling and finite-size effects in first-principles stopping power calculations

Real-time time-dependent density functional theory (TDDFT) is presently the most accurate available method for computing electronic stopping powers from first principles. However, obtaining application-relevant results often involves either costly averages over multiple calculations or ad hoc selection of a representative ion trajectory. We consider a broadly applicable, quantitative metric for evaluating and optimizing trajectories in this context. This methodology enables rigorous analysis of the failure modes of various common trajectory choices in crystalline materials. Although randomly selecting trajectories is common practice in stopping power calculations in solids, we show that nearly 30% of random trajectories in an FCC aluminum crystal will not representatively sample the material over the time and length scales feasibly simulated with TDDFT, and unrepresentative choices incur errors of up to 60%. We also show that finite-size effects depend on ion trajectory via “ouroboros” effects beyond the prevailing plasmon-based interpretation, and we propose a cost-reducing scheme to obtain converged results even when expensive core-electron contributions preclude large supercells. This work helps to mitigate poorly controlled approximations in first-principles stopping power calculations, allowing 1–2 order of magnitude cost reductions for obtaining representatively averaged and converged results.

Robust crystal structure identification at extreme conditions using a density-independent spectral descriptor and supervised learning

The increased time- and length-scale of classical molecular dynamics simulations have led to raw data flows surpassing storage capacities, necessitating on-the-fly integration of structural analysis algorithms. As a result, algorithms must be computationally efficient, accurate, and stable at finite temperature to reliably extract the relevant features of the data at simulation time. In this work, we leverage spectral descriptors to encode local atomic environments and build crystal structure classification models. In addition to the classical way spectral descriptors are computed, i.e. over a fixed radius neighborhood sphere around a central atom, we propose an extension to make them independent from the material’s density. Models are trained on defect-free crystal structures with moderate thermal noise and elastic deformation, using the linear discriminant analysis (LDA) method for dimensionality reduction and logistic regression (LR) for subsequent classification. The proposed classification model is intentionally designed to be simple, incorporating only a limited number of parameters. This deliberate simplicity enables the model to be trained effectively even when working with small databases. Despite the limited training data, the model still demonstrates inherent transferability, making it applicable to a broader range of scenarios and datasets. The accuracy of our models in extreme conditions (high temperature, high density, large deformation) is compared to traditional algorithms from the literature, namely adaptive common neighbor analysis (a-CNA), polyhedral template matching (PTM) and diamond structure identification (IDS). Finally, we showcase two applications of our method: tracking a solid–solid BCC-to-HCP phase transformation in Zirconium at high pressure up to high temperature, and visualizing stress-induced dislocation loop expansion in single crystal FCC Aluminum containing a Frank–Read source, at high temperature.

Investigating the Influence of Diffusion on the Cohesive Zone Model of the SiC/Al Composite Interface.

Modeling metal matrix composites in finite element software requires incorporating a cohesive zone model (CZM) to represent the interface between the constituent materials. The CZM determines the behavior of traction-separation (T-S) in this region. Specifically, when a diffusion zone is formed due to heat treatment, it becomes challenging to determine experimentally the equivalent mechanical properties of the interface. Additionally, understanding the influence of heat treatment and the creation of a diffusion zone on the T-S law is crucial. In this study, the molecular dynamics approach was employed to investigate the effect of the diffusion region formation, resulting from heat treatment, on the T-S law at the interface of a SiC/Al composite in tensile, shear, and mixed-mode loadings. It was found that the formation of a diffusion layer led to an increase in tensile and shear strengths and work of separation compared with the interfaces without heat treatment. However, the elastic and shear moduli were not significantly affected by the creation of the diffusion layer. Moreover, the numerical findings indicated that the shear strength in the diffusion region was higher when compared with the shear strength of the {111} slip plane within the fcc aluminum component of the composite material. Therefore, in the diffusion region, crack propagation did not occur in the pure shear loading case; however, shear sliding was observed at the aluminum atomic layers.

Prediction of dislocation - grain boundary interactions in FCC aluminum bicrystals using a modified continuum criterion and machine learning methods

Mechanical properties of metals such as strength and toughness are strongly correlated to complex interactions between various defects in the crystalline structure. While elementary interactions between these defects have been investigated using recent micro- and nano-characterization techniques, understanding of the detailed interaction mechanisms has hardly been obtained. To understand defect-driven plasticity at various time and length scales, it is necessary to formulate a general guideline to predict both the interaction type (transmission or reflection) and the dislocation's subsequent slip system after the interaction. Many criteria based on the geometric alignment of the defects have been developed to predict this phenomenon, but these have yet to be found to be accurate when applied to general data sets of grain boundaries (GBs). With this motivation, we conduct a systematic study using molecular dynamics (MD) models of bicrystals to analyze defect interaction process between a prismatic dislocation loop and eleven different grain boundaries of the following character: three tilt, three twist, and five mixed. Based on the MD observations, two new prediction methods are developed: the first is a new data-driven parametric score function based on the classical geometric criteria, and the second is by applying Gaussian process machine learning methods to find the probability distribution of a hidden function. The proposed data-driven prediction methods could pave a new way to predict the unit interaction of dislocations with various GBs, which could show much higher accuracy compared to pre-existing geometric criteria.

Efficient single-grid and multi-grid solvers for real-space orbital-free density functional theory

To improve the computational efficiencies of the real-space orbital-free density functional theory, this work develops a new single-grid solver by directly providing the closed-form solution to the inner iteration and using an improved bisection method to accelerate the line search process in the outer iteration, and extended the single-grid solver to a multi-grid solver. Numerical examples show that while maintaining high level of accuracy, the proposed single-grid solver can improve the computational efficiencies by two orders of magnitude comparing with the methods in the literature (For example, the ground state energy of a 45×45×45 FCC Aluminum cluster (376786 atoms) can be computed within 4h27min on a desktop computer.) and the multi-grid solver can improve the computational efficiencies even once for the cases where high-resolution electron densities are needed.

Tuning the defects density in additively manufactured fcc aluminium alloy via modifying the cellular structure and post-processing deformation

In this study, using an L-PBF AlSi10Mg alloy with different microstructural properties, the typical structural defects caused by severe plastic deformation are investigated by scanning electron microscopy and high-resolution transmission electron microscopy. Microscopic characterization shows that the deformed L-PBF AlSi10Mg alloy exhibits a heterogeneous microstructure consisting of Al/Si interfaces and a high density of dislocations, stacking faults, and nanotwins. On the basis of experimental data, it is also shown that high stresses build up at the Al/Si interface due to incompatible deformation, enabling the activation of novel deformation modes that control the plastic deformation of the hard Si twin phase and amorphization in the solid state. The revealed synergy and novel deformation modes open a new horizon for the development of next-generation structural materials and provide insights into the atomically resolved structures of dislocations and GBs in nanostructured L-PBF alloys.

Identification of Linear Elastic Fracture Mechanics Parameters Through the Atomistic Simulation Based Analysis

The contribution presents atomistic modeling of the proximate crack tip and notch stress fields through molecular dynamics method. The study is aspired to comparing atomistic stress distributions for monocrystalline fcc copper and aluminum with continuous stress fields obtained on the basis of classical continuum fracture mechanics. Atomistic simulations were implemented for pure tensile loadings and mixed (I+II mixed loadings) mode loadings in Large-scale Atomistic/ Molecular Massively Parallel Simulator (LAMMPS). In atomistic computations specimens with central cracks and single edge notches made of crystalline fcc copper and aluminum under mixed mode loadings are considered. The elastic tensor components of the selected crystalline materials are obtained via molecular dynamics simulations and the circumferential distributions of stress fields in the straight away proximity of the crack and notch tips in aluminum and copper are constructed. The main regularities arising from the comparative analysis of the atomistic and continuum approaches are revealed. The major conclusion that can be reached after atomistic modeling is that the stress apportionments given by classical linear fracture mechanics qualitatively and quantitatively describe the molecular dynamics stress distributions.

Controlling polymorph selection during nucleation by tuning the structure of metallic melts.

Controlling the polymorphism of crystals is crucial to the design of novel metallic materials with specific properties; however, the atomistic mechanism underlying polymorph selection during crystallization remains unclear. In this work, molecular dynamics simulations combined with well-tempered metadynamics simulations are employed to explore the atomic mechanisms of polymorph selection during the nucleation process of FCC aluminum and copper. Simulation results suggest that the distinct nucleation pathways of both FCC metals originate from different free-energy surfaces of nucleation processes and diverse symmetries of nucleation precursors. The initially forming phase from undercooled melts is most likely to be the one that has the symmetry closest to the precursors. Besides, tiny seeds with diverse crystal symmetries could induce the formation of preordered precursors for nucleation around the seed, leading to the reduction of free-energy barrier and thus the promotion of nucleation. Controlling polymorph selection with tiny seeds is realized by tuning the symmetry of precursors. Our findings not only shed significant light on understanding polymorph selection, but also provide theoretical guidance for better controlling the nucleation pathway in practice.

Void Mediated Failure at the Extremes: Spallation in Magnesium and Aluminum

This paper reviews the role of void nucleation, growth, and coalescence on the spall failure process in light metals. Based on the review of the open literature, the preponderance of evidence show that void nucleation, growth, and coalescence are prevalent in light metals such as HCP magnesium and FCC aluminum alloys. The as-received microstructure and its evolution play a crucial role on how voids nucleate, grow, and coalesce. Nucleation of voids in these light metals and metallic alloys can be either homogeneous and heterogeneous but at high enough stresses, both homogeneous and heterogeneous nucleation can be activated simultaneously. Secondary phase particles and intermetallics can strongly influence spall failure, through matrix-precipitate/intermetallic debonding or precipitate/intermetallic cracking during shock compression. Studying spall failure through modeling has proven to be an invaluable tool in developing a fundamental understanding of void nucleation, growth, coalescence, and consequent spall failure. However, since new alloys are currently been developed, more experimental and modeling research are needed to further understand how spall failure initiate and grow in these new alloys.

Determination of the Efficiency of Hot Nano-Grinding of Mono-Crystalline Fcc Metals Using Molecular Dynamics Method.

Abrasive processes are essential to the manufacturing field, due to their capability of rendering high-quality surfaces with minimum effect on workpiece integrity. As it is especially difficult to perform sufficient experimental work, numerical studies can be successfully employed to evaluate techniques for the improvement of the efficiency of nanometric abrasive processes. In the present study, for the first time, cases of nanogrinding on workpieces of three different fcc metals, namely, copper, nickel, and aluminum are investigated under different preheating temperatures, in order to determine the efficiency of the hot nano-grinding technique. For the simulations, a molecular dynamics model for peripheral nanogrinding is developed including multiple abrasive grains and realistic grain trajectory and grinding forces, and chip characteristics and subsurface alterations are evaluated. The results indicate that using elevated preheating temperatures is beneficial for nanogrinding, as forces can be considerably reduced and material removal can be facilitated, especially for temperatures over 40% of the material melting temperature (Tm). However, the detrimental effect on workpiece integrity is also evident at higher preheating temperatures, due to the high temperature on the whole workpiece, posing limitations to the applicability of the hot nano-grinding technique. Based on the findings of this study, preheating temperatures in the range of 0.4–0.55 Tm are recommended.

Two distinct non-Arrhenius behaviors of hydrogen diffusivities in fcc aluminum, silver, and copper determined byab initiopath integral simulations

Nuclear quantum effects (NQEs) are highly important for understanding a host of kinetic processes that occur with the participation of H (e.g., H adsorption, diffusion, permeation, and trapping in materials). In this paper, ab initio path integral molecular dynamics simulations were used to investigate NQEs on the lattice diffusion of H in common face-centered cubic (fcc) metals such as Al, Ag, and Cu over a wide temperature range of 75--1200 K (75--900 K for Al). We determined that the dependence of H diffusivities on temperature in Ag and Cu has a ``reversed-S'' shape on Arrhenius plots, as confirmed for fcc Pd in our recent study [H. Kimizuka et al., Phys. Rev. B 100, 024104 (2019)]. This result illustrates that the phenomenon is common in many fcc metals in which H atoms prefer to occupy octahedral sites. On the other hand, in the case of Al, in which H atoms prefer to occupy tetrahedral sites, the dependence of H diffusivities on temperature exhibits a familiar ``C'' shape. Such counterintuitive behavior is ascribed to differences in the dependence on temperature of the activation barriers for H migration between both types of fcc metals; this is due to the NQEs involving a competition between deceleration of H migration, which becomes effective at high temperatures because of zero-point vibrations, and acceleration of H migration, which becomes effective at low temperatures because of quantum tunneling. The dominance of the two mechanisms is determined by the coupling of the NQEs and the site preference of H depending on the metal. This finding has important implications for the interpretation of kinetic processes involving the crossover from classical to quantum behavior of H atoms jumping between different types of interstitial sites.

Anharmonic effects on the dynamics of solid aluminium from ab initio simulations

Two approaches to simulations of phonon properties of solids beyond the harmonic approximation, the self-consistent ab initio lattice dynamics (SCAILD) and decoupled anharmonic mode approximation (DAMA) are critically benchmarked against each other and molecular dynamics simulations using a density-functional-theory description of electronic states, and compared to experimental data for fcc aluminium. The temperature-dependence of phonon dispersion and the phonon density-of-states, heat capacity, and the mean atomic displacement for fcc aluminium are examined with these approaches at ambient pressure. A comparison of results obtained with the harmonic approximation to the ones predicted by SCAILD and DAMA reveal a negligible anharmonic contribution to phonon frequencies, a small, but significant influence on heat capacity, and a strong effect on atomic mean-square displacement. The phase space accessed with SCAILD and DAMA is reduced relative to molecular and harmonic lattice dynamics simulations. In particular the DAMA results are in good agreement with displacement amplitudes determined by the Debye–Waller factor in x-ray diffraction experiments.

Space‐Projected Conductivity and Spectral Properties of the Conduction Matrix

Herein, the Kubo–Greenwood formula is utilized to project the electronic conductivity into real space, and a Hermitian positive semidefinite matrix Γ is discussed, which is called the conduction matrix, that reduces the computation of spatial conduction activity to a diagonalization. It is shown that for low‐density amorphous carbon, connected sp2 rings and sp chains are conduction‐active sites in the network. In amorphous silicon, transport involves hopping through tail states mediated by the defects near the Fermi level. It is found that for liquid silicon, thermal fluctuations induce spatial and temporal conductivity fluctuations in the material. The frequency‐dependent absorption of light as a function of wavelength in an amorphous silicon suboxide (a‐SiO1.3) is also studied. It is shown that the absorption is strongly frequency dependent and selects out different oxygen vacancy subnetworks depending on the frequency. Γ is diagonalized to obtain conduction eigenvalues and eigenvectors, and it is shown that the density of states of the eigenvalues for FCC aluminum has an extended spectral tail that distinguishes metals from insulators and semiconductors. The method is easy to implement with any electronic structure code, providing suitable estimates for single‐particle electronic states and energies.

The role of orientation on the shock response of single crystal tantalum

The response of single crystalline tantalum to one-dimensional shock loading has been investigated as a function of crystalline orientation to the loading axis. Results show that this has a significant effect, particularly on the Hugoniot elastic limit (HEL). [100] and [111] HELs are near identical with the [110] HEL having the lowest strength. This is contrary to predictions obtained by applying the Schmid factor analysis, where the ordering was expected to be (highest strength first) [111], [110], with the [100] orientation being the softest. Adopting a more appropriate model based on uniaxial strain conditions, as was previously done successfully for FCC aluminum and copper, did not rationalize our observations. We show that a non-Schmid effective stress model, incorporating twinning/anti-twinning asymmetry, has much greater success in reproducing the experimental relative HELs magnitudes. Using this model, we make a quantitative estimation of the magnitude of non-Schmid effects and compare these to equivalent low temperature, quasi-static estimates from the literature.

Effect of the Structural Properties on the Electrical Resistivity of the Al/Ag Thin Films during the Solid-State Reaction

Based on the results of in situ electron diffraction study of the solid-state reaction and electrical resistivity measurements on the Al/Ag thin films with an atomic ratio of Al : Ag = 1 : 3, the temperature of the reaction onset has been established and a model of the structural phase transitions has been proposed. The solid-state reaction begins at 70°C with the formation of the Al–Ag solid solution at the interface between the aluminum and silver nanolayers. It has been found that, in the course of the reaction, the intermetallic compounds γ-Ag2Al → μ-Ag3Al are successively formed. It is shown that the possibility of the formation of the μ‑Ag3Al phase during the solid-state reaction in the Al/Ag thin films depends on the aluminum-to-silver ratio, while the formation of the μ-Ag3Al phase begins only after all fcc aluminum has reacted.

Влияние структурных свойств на электросопротивление тонких пленок Al/Ag в процессе твердофазной реакции

Based on the study of a solid-state reaction process in Al/Ag thin films (the atomic ratio being Al:Ag=1:3) carried out by in situ electron diffraction method and electrical resistivity measurements, the reaction initiation temperature has been determined and a model of structural phase transitions occurring during the solid-state reaction has been proposed. The solid-state reaction begins at 70°C with the formation of an Al-Ag solid solution at the interface of aluminum and silver nanolayers. It has been found that in the reaction process intermetallic compounds γ-Ag2Al => µ-Ag3Al are successively formed. It has been established that for the formation of the µ-Ag3Al phase in thin films (up to 100 nm) the following is necessary: first, significant excess of silver over aluminum in the atomic composition, second, the formation of the µ-Ag3Al phase begins only after all the FCC aluminum has reacted. The work was supported by the Russian Science Foundation (grant #18-13-00080).