SimpleN-body potentials for the noble metals and nickel

In silico assessment of nanoparticle toxicity powered by the Enalos Cloud Platform: Integrating automated machine learning and synthetic data for enhanced nanosafety evaluation

The rapid advance of nanotechnology has led to the development and widespread application of nanomaterials, raising concerns regarding their potential adverse effects on human health and the environment. Traditional (experimental) methods for assessing the nanoparticles (NPs) safety are time-consuming, expensive, and resource-intensive, and raise ethical concerns due to their reliance on animals. To address these challenges, we propose an in silico workflow that serves as an alternative or complementary approach to conventional hazard and risk assessment strategies, which incorporates state-of-the-art computational methodologies. In this study we present an automated machine learning (autoML) scheme that employs dose-response toxicity data for silver (Ag), titanium dioxide (TiO2), and copper oxide (CuO) NPs. This model is further enriched with atomistic descriptors to capture the NPs' underlying structural properties. To overcome the issue of limited data availability, synthetic data generation techniques are used. These techniques help in broadening the dataset, thus improving the representation of different NP classes. A key aspect of this approach is a novel three-step applicability domain method (which includes the development of a local similarity approach) that enhances user confidence in the results by evaluating the prediction's reliability. We anticipate that this approach will significantly expedite the nanosafety assessment process enabling regulation to keep pace with innovation, and will provide valuable insights for the design and development of safe and sustainable NPs. The ML model developed in this study is made available to the scientific community as an easy-to-use web-service through the Enalos Cloud Platform (www.enaloscloud.novamechanics.com/sabydoma/safenanoscope/), facilitating broader access and collaborative advancements in nanosafety.

Evaluation of Sampling Algorithms Used for Bayesian Uncertainty Quantification of Molecular Dynamics Force Fields

New Bayesian parameter estimation methods have the capability to enable more physically realistic and reliable molecular dynamics (MD) simulations by providing accurate estimates of uncertainties of force-field (FF) parameters and associated properties. However, the choice of which Bayesian parameter estimation algorithm to use has not been widely investigated, despite its impact on the effective exploration of parameter space. Here, using a case example of the Embedded Atom Method (EAM) FF parameters, we investigated the ramifications of several of the algorithm choices. We found that Ensemble Slice Sampling (ESS) and Affine-Invariant Ensemble Sampling (AIES) demonstrate a new level of superior performance, culminating in more accurate parameter and property estimations with tighter uncertainty bounds, compared to traditional methods such as Metropolis-Hastings (MH), Gradient Search (GS), and Uniform Random Sampler (URS). We demonstrate that Bayesian Uncertainty Quantification with ESS and AIES leads to significantly more accurate and reliable predictions of the FF parameters and properties. The results suggest that ESS and AIES should be used to obtain more accurate parameter and uncertainty estimations while providing deeper physical insights.

Effects of the temperature, strain rate, and loading conditions on the deformation behaviors and mechanical properties of the Ni/Ni3Al superalloy

Using the molecular dynamics method, we comprehensively studied the effects of temperature, strain rate, and loading conditions on the deformation behaviors and the mechanical properties of the Ni/Ni3Al superalloy. Our investigation revealed that, an increase of the deformation temperature led to a significant improvement of plastic deformation capacity of the system, but the tensile strength and elastic modulus decreased. And the tensile strength and plastic deformation capacity of the system drastically increased with the strain rate. At high deformation temperature and strain rate, the loading conditions had a large effect on the deformation behaviors and the mechanical properties of the system. The difference of the mechanical properties of the system was mainly due to the different deformation mechanism of the system under different deformation temperature, strain rate and loading conditions. Our study offered a theoretical framework for explaining the difference of the mechanical properties for the Ni/Ni3Al superalloy at different service conditions.

Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals

Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials. Such physics-based models, while extensively deployed for predicting the dynamics and properties of nanoscale systems over the past two decades, tend to perform poorly in predicting nanoscale potential energy surfaces (PESs) when compared to high-fidelity first-principles calculations. These limitations stem from the lack of flexibility in such models, which rely on a predefined functional form. Machine learning (ML) models and approaches have emerged as a viable alternative to capture the diverse size-dependent cluster geometries, nanoscale dynamics, and the complex nanoscale PESs, without sacrificing the bulk properties. Here, we introduce an ML workflow that combines transfer and active learning strategies to develop high-dimensional neural networks (NNs) for capturing the cluster and bulk properties for several different transition metals with applications in catalysis, microelectronics, and energy storage, to name a few. Our NN first learns the bulk PES from the high-quality physics-based models in literature and subsequently augments this learning via retraining with a higher-fidelity first-principles training data set to concurrently capture both the nanoscale and bulk PES. Our workflow departs from status-quo in its ability to learn from a sparsely sampled data set that nonetheless covers a diverse range of cluster configurations from near-equilibrium to highly nonequilibrium as well as learning strategies that iteratively improve the fingerprinting depending on model fidelity. All the developed models are rigorously tested against an extensive first-principles data set of energies and forces of cluster configurations as well as several properties of bulk configurations for 10 different transition metals. Our approach is material agnostic and provides a methodology to transfer and build upon the learnings from decades of seminal work in molecular simulations on to a new generation of ML-trained potentials to accelerate materials discovery and design.

Gradual weakening down to complete disappearance of the velocity correlated cluster emission effect in keV collisions of C60 with light metallic targets: Microscopic insights via molecular dynamics simulations

The so-called velocity correlated cluster emission (VCCE) effect is the recently reported emission of large clusters with nearly the same velocity from an atomically heavy target (such as coinage metals) following a single C60- impact at the keV kinetic energy range. The effect was observed to get weaker for a meaningfully lighter target (Al) down to its complete disappearance for C60-Be impact. Microscopic insight into the subpicosecond evolution and thermalization of the impact induced energy spike (driving the effect) is achieved using molecular dynamics simulations. It is shown that the weakening of the VCCE effect for aluminum (toward its complete disappearance for Be) is due to ultrafast decay of the atomic number density within the spike nanovolume, thus not enabling the buildup of sufficient subsurface pressure as required for driving the correlated emission. For the Be target, an extremely rapid decay of nearly 90% of the initial density within 200 fs from impact is observed. This finding provides further support for the conclusion that the emission of the velocity correlated clusters as observed for the heavier targets takes place within an ultra-short time window of only a few hundreds of femtoseconds, roughly extending from 200 to 500 fs from impact. The lower bound is dictated by the requirement for a relatively slow rate of decay of number density, enabling the buildup of a sufficiently intense pressure spike. The upper bound is dictated by the cooling rate of the spike (still maintaining an extremely high temperature of kT ≥ 1 eV, as experimentally observed) and the onset of the evolution of the impact crater.

Goldilocks Energy Minimum: Peptide-Based Reversible Aggregation and Biosensing

Colorimetric biosensors based on gold nanoparticle (AuNP) aggregation are often challenged by matrix interference in biofluids, poor specificity, and limited utility with clinical samples. Here, we propose a peptide-driven nanoscale disassembly approach, where AuNP aggregates induced by electrostatic attractions are dissociated in response to proteolytic cleavage. Initially, citrate-coated AuNPs were assembled via a short cationic peptide (RRK) and characterized by experiments and simulations. The dissociation peptides were then used to reversibly dissociate the AuNP aggregates as a function of target protease detection, i.e., main protease (Mpro), a biomarker for severe acute respiratory syndrome coronavirus 2. The dissociation propensity depends on peptide length, hydrophilicity, charge, and ligand architecture. Finally, our dissociation strategy provides a rapid and distinct optical signal through Mpro cleavage with a detection limit of 12.3 nM in saliva. Our dissociation peptide effectively dissociates plasmonic assemblies in diverse matrices including 100% human saliva, urine, plasma, and seawater, as well as other types of plasmonic nanoparticles such as silver. Our peptide-enabled dissociation platform provides a simple, matrix-insensitive, and versatile method for protease sensing.

Atomistic Simulation of Physical Vapor Deposition of Optical Thin Films

A review of the methods and results of atomistic modeling of the deposition of thin optical films and a calculation of their characteristics is presented. The simulation of various processes in a vacuum chamber, including target sputtering and the formation of film layers, is considered. Methods for calculating the structural, mechanical, optical, and electronic properties of thin optical films and film-forming materials are discussed. The application of these methods to studying the dependences of the characteristics of thin optical films on the main deposition parameters is considered. The simulation results are compared with experimental data.

Curvature-Selective Nanocrystal Surface Ligation Using Sterically-Encumbered Metal-Coordinating Ligands

Organic ligands are critical in determining the physiochemical properties of inorganic nanocrystals. However, precise nanocrystal surface modification is extremely difficult to achieve. Most research focuses on finding ligands that fully passivate the nanocrystal surface, with an emphasis on the supramolecular structure generated by the ligand shell. Inspired by molecular metal-coordination complexes, we devised an approach based on ligand anchoring groups that are flanked by encumbering organic substituents and are chemoselective for binding to nanocrystal corner, edge, and facet sites. Through experiment and theory, we affirmed that the surface-ligand steric pressures generated by these organic substituents are significant enough to impede binding to regions of low nanocurvature, such as nanocrystal facets, and to promote binding to regions of high curvature such as nanocrystal edges.

In situ atomic-scale observation of dislocation climb and grain boundary evolution in nanostructured metal

Non-conservative dislocation climb plays a unique role in the plastic deformation and creep of crystalline materials. Nevertheless, the underlying atomic-scale mechanisms of dislocation climb have not been explored by direct experimental observations. Here, we report atomic-scale observations of grain boundary (GB) dislocation climb in nanostructured Au during in situ straining at room temperature. The climb of a edge dislocation is found to occur by stress-induced reconstruction of two neighboring atomic columns at the edge of an extra half atomic plane in the dislocation core. This is different from the conventional belief of dislocation climb by destruction or construction of a single atomic column at the dislocation core. The atomic route of the dislocation climb we proposed is demonstrated to be energetically favorable by Monte Carlo simulations. Our in situ observations also reveal GB evolution through dislocation climb at room temperature, which suggests a means of controlling microstructures and properties of nanostructured metals.

Dislocation climb is crucial to plasticity and creep of materials. Here, the authors report real-time atomic-scale observations of grain boundary dislocation climb in nanostructured Au at room temperature. The dislocation climb occurs by reconstruction of two atomic columns in the dislocation core.

Deformation Mechanisms of FCC-Structured Metallic Nanocrystal with Incoherent Twin Boundary

Incoherent twin boundaries (ITBs) can significantly affect the mechanical properties of twin-structured metals. However, most previous studies have focused on the deformation mechanism of the coherent twin boundary (CTB), and metals with ITB-accommodated plasticity still require further investigation. In this study, deformation mechanisms of FCC-structured nanocrystal metals with ITBs were investigated using molecular dynamic (MD) simulations. We revealed that three deformation mechanisms occur in metals with ITBs. The first type of deformation was observed in Au, where the plasticity is governed by partial dislocation intersections with CTBs or reactions with each other to form Lomer–Cottrell (L–C) locks. In the second type, found in Al, the deformation is governed by reversible ITB migration. The third type of deformation, in Ni and Cu, is governed by partial dislocations emitted from the ITB or the tips of the stacking faults (SFs). The observed L–C lock formation, as well as the reversible ITB migration and partial dislocation emission from the tips of SFs, have rarely been reported before.

Construction of an n-Body Potential for Revealing the Atomic Mechanism for Direct Alloying of Immiscible Tungsten and Copper

W-Cu laminated composites are critical materials used to construct nuclear fusion reactors, and it is very important to obtain direct alloying between W and Cu at the W/Cu interfaces of the composites. Our previous experimental studies showed that it is possible to overcome the immiscibility between W and Cu and obtain direct alloying when the alloying temperature is close to the melting point of Cu. Because the W-Cu interatomic potentials published thus far cannot accurately reproduce the alloying behaviors of immiscible W and Cu, an interatomic potential suitable for the W-Cu system has been constructed in the present study. Based on this potential, direct alloying between W and Cu at high temperature has been verified, and the corresponding diffusion mechanism has been studied, through molecular dynamics (MD) simulations. The results indicate that the formation of an amorphous Cu layer at the W/Cu interface plays a critical role in alloying because it allows Cu atoms to diffuse into W. The simulation results for direct alloying between W and Cu can be verified by experimental results and transmission electron microscopy observations. This indicates that the constructed W-Cu potential can correctly model the high-temperature performance of the W-Cu system and the diffusion mechanism of direct alloying between W and Cu.

First-principles studies on optical absorption of [010] screw dislocation in KDP crystals

The stress caused by the [010] dislocation in KDP deforms the crystal structure, introduces extra optical absorption and narrows the band gap.

Quantized Grain Boundary States Promote Nanoparticle Alignment During Imperfect Oriented Attachment

Oriented attachment (OA) has become a well-recognized mechanism for the growth of metal, ceramic, and biomineral crystals. While many computational and experimental studies of OA have shown that particles can attach with some misorientation then rotate to remove adjoining grain boundaries, the underlying atomistic pathways for this "imperfect OA" process remain the subject of debate. In this study, molecular dynamics and in situ transmission electron microscopy (TEM) are used to probe the crystallographic evolution of up to 30 gold nanoparticles during aggregation. It is found that Imperfect OA occurs because 1) grain boundaries become quantized when their size is comparable to the separation between constituent dislocations and 2) kinetic barriers associated with the glide of grain boundary dislocations are small. In support of these findings, TEM experiments show the formation of a single crystal aggregate after annealing nine initially misoriented, agglomerated particles with evidence of dislocation activity and twin formation during particle/grain alignment. These observations motivate future work on assembled nanocrystals with tailored defects and call for a revision of Read-Shockley models for grain boundary energies in nanocrystalline materials.

The Effect of Vacancies on Grain Boundary Segregation in Ferromagnetic fcc Ni

This work presents a comprehensive and detailed ab initio study of interactions between the tilt Σ5(210) grain boundary (GB), impurities X (X = Al, Si) and vacancies (Va) in ferromagnetic fcc nickel. To obtain reliable results, two methods of structure relaxation were employed: the automatic full relaxation and the finding of the minimum energy with respect to the lattice dimensions perpendicular to the GB plane and positions of atoms. Both methods provide comparable results. The analyses of the following phenomena are provided: the influence of the lattice defects on structural properties of material such as lattice parameters, the volume per atom, interlayer distances and atomic positions; the energies of formation of particular structures with respect to the standard element reference states; the stabilization/destabilization effects of impurities (in substitutional (s) as well as in tetragonal (iT) and octahedral (iO) interstitial positions) and of vacancies in both the bulk material and material with GBs; a possibility of recombination of Si⁽ⁱ⁾+Va defect to Si^(s) one with respect to the Va position; the total energy of formation of GB and Va; the binding energies between the lattice defects and their combinations; impurity segregation energies and the effect of Va on them; magnetic characteristics in the presence of impurities, vacancies and GBs. As there is very little experimental information on the interaction between impurities, vacancies and GBs in fcc nickel, most of the present results are theoretical predictions, which may motivate future experimental work.

Analytical bond-order potential for silver, palladium, ruthenium and iodine bulk diffusion in silicon carbide

The analytical bond-order potential has been developed for simulating fission product (Ag, Pd, Ru, and I) behavior in SiC, especially for their diffusion. We have proposed adding experimentally available elastic constants and physical properties of the elements as well as important defect formation energies calculated from density functional theory simulation to the list of typical properties as the extensive fitting database. The results from molecular dynamics simulations are in a reasonable agreement with defect properties and energy barriers of their experimental/computational counterparts. The successful validation of the new potential has established a good reliability and transferability of the potentials, which enables the ability of simulation in extended scale. The kinetic behavior such as diffusion of different interstitials is then realized by applying the new interatomic potentials. The bulk diffusion is less likely to dominate the transport of the four fission products under pure thermal condition, when we refer to their extremely small values of the effective diffusion coefficients. The interstitial mechanism is hard for Pd, Ru, and I to access due to the high formation energy and high migration energy. However, it is found that the migration energy of silver is relatively low, which indicates Ag diffusion via an interstitial mechanism being feasible, especially under irradiation condition, where massive interstitials can be formed in high-temperature nuclear reactors.

Channeling effects in gold nanoclusters under He ion irradiation: insights from molecular dynamics simulations

The interpretation of helium ion microscopy (HIM) images of crystalline metal clusters requires microscopic understanding of the effects of He ion irradiation on the system, including energy deposition and associated heating, as well as channeling patterns. While channeling in bulk metals has been studied at length, there is no quantitative data for small clusters. We carry out molecular dynamics simulations to investigate the behavior of gold nanoparticles with diameters of 5-15 nm under 30 keV He ion irradiation. We show that impacts of the ions can give rise to substantial heating of the clusters through deposition of energy into electronic degrees of freedom, but it does not affect channeling, as clusters cool down between consecutive impact of the ions under typical imaging conditions. At the same time, high temperatures and small cluster sizes should give rise to fast annealing of defects so that the system remains crystalline. Our results show that ion-channeling occurs not only in the principal low-index, but also in the intermediate directions. The strengths of different channels are specified, and their correlations with sputtering-yield and damage production is discussed, along with size-dependence of these properties. The effects of planar defects, such as stacking faults on channeling were also investigated. Finally, we discuss the implications of our results for the analysis of HIM images of metal clusters.

Oriented attachment induces fivefold twins by forming and decomposing high-energy grain boundaries

Natural and synthetic nanoparticles composed of fivefold twinned crystal domains have distinct properties. The formation mechanism of these fivefold twinned nanoparticles is poorly understood. We used in situ high-resolution transmission electron microscopy combined with molecular dynamics simulations to demonstrate that fivefold twinning occurs through repeated oriented attachment of ~3-nanometer gold, platinum, and palladium nanoparticles. We discovered two different mechanisms for forming fivefold twinned nanoparticles that are driven by the accumulation and elimination of strain. This was accompanied by decomposition of grain boundaries and the formation of a special class of twins with a net strain of zero. These observations allowed us to develop a quantitative picture of the twinning process. The mechanisms provide guidance for controlling twin structures and morphologies across a wide range of materials.

Density-functional tight-binding approach for metal clusters, nanoparticles, surfaces and bulk: application to silver and gold

Density-functional based tight-binding (DFTB) is an efficient quantum mechanical method that can describe a variety of systems, going from organic and inorganic compounds to metallic and hybrid materials. The present topical review addresses the ability and performance of DFTB to investigate energetic, structural, spectroscopic and dynamical properties of gold and silver materials. After a brief overview of the theoretical basis of DFTB, its parametrization and its transferability, we report its past and recent applications to gold and silver systems, including small clusters, nanoparticles, bulk and surfaces, bare and interacting with various organic and inorganic compounds. The range of applications covered by those studies goes from plasmonics and molecular electronics, to energy conversion and surface chemistry. Finally, perspectives of DFTB in the field of gold and silver surfaces and NPs are outlined.

Interatomic Potentials Transferability for Molecular Simulations: A Comparative Study for Platinum, Gold and Silver

A perfectly transferable interatomic potential that works for different materials and systems of interest is lacking. This work considers the transferability of several existing interatomic potentials by evaluating their capability at various temperatures, to determine the range of accuracy of these potentials in atomistic simulations. A series of embedded-atom-method (EAM) based interatomic potentials has been examined for three precious and popular transition metals in nanoscale studies: platinum, gold and silver. The potentials have been obtained from various credible and trusted repositories and were evaluated in a wide temperature range to tackle the lack of a transferability comparison between multiple available force fields. The interatomic potentials designed for the single elements, binary, trinary and higher order compounds were tested for each species using molecular dynamics simulation. Validity of results arising from each potential was investigated against experimental values at different temperatures from 100 to 1000 K. The data covers accuracy of all studied potentials for prediction of the single crystals’ elastic stiffness constants as well as the bulk, shear and Young’s modulus of the polycrystalline specimens. Results of this paper increase users’ assurance and lead them to the right model by a way to easily look up data.

Understanding the cooperative atomic motion and shape change of ultrasmall Au nanoparticles below the premelting temperature

Surface melting is widely observed in crystalline materials, which has a significant influence on their interfacial properties.

Shear-coupled grain boundary migration assisted by unusual atomic shuffling

Shear-coupled grain boundary (GB) migration can be an efficacious mechanism to accommodate plastic deformation when the grain size of polycrystalline materials goes small. Nevertheless, how this kind of GB motion comes into play at the atomic level has not been fully revealed. Here, we have investigated the shear-coupled migration (SCM) of typical [100] group symmetrical tilt GBs in bcc W using atomistic simulations. Depending on GB character, the SCM is found to proceed via dislocation slipping in the 〈100〉 or 〈110〉 mode with striking shear strength difference between them. We demonstrate that there exists an unusual atomic shuffling along the tilt axis, which greatly assists SCM to operate in the easier 〈110〉 mode instead of the 〈100〉 one. The present results highlight the significant role of GB character in the atomistic SCM process and contribute to the future design and fabrication of high-performance materials in GB engineering.

Approach and Coalescence of Gold Nanoparticles Driven by Surface Thermodynamic Fluctuations and Atomic Interaction Forces

The approach and coalescence behavior of gold nanoparticles on a silicon surface were investigated by experiments and molecular dynamics simulations. By analyzing the behavior of the atoms in the nanoparticles in the simulations, it was found that the atoms in a single isolated nanoparticle randomly fluctuated and that the surface atoms showed greater fluctuation. The fluctuation increased as the temperature increased. When there were two or more neighboring nanoparticles, the fluctuating surface atoms of the nanoparticles "flowed" toward the neighboring nanoparticle because of atomic interaction forces between the nanoparticles. With the surface atoms "flowing", the gold nanoparticles approached and finally coalesced. The simulation results were in good agreement with the experimental results. It can be concluded that surface thermodynamic fluctuations and atomic interaction forces are the causes of the approach and coalescence behavior of the gold nanoparticles.

Mechanical integrity of a carbon nanotube/copper-based through-silicon via for 3D integrated circuits: a multi-scale modeling approach

Carbon nanotube (CNT)/copper (Cu) composite material is proposed to replace Cu-based through-silicon vias (TSVs) in micro-electronic packages. The proposed material is believed to offer extraordinary mechanical and electrical properties and the presence of CNTs in Cu is believed to overcome issues associated with miniaturization of Cu interconnects, such as electromigration. This study introduces a multi-scale modeling of the proposed TSV in order to evaluate its mechanical integrity under mechanical and thermo-mechanical loading conditions. Molecular dynamics (MD) simulation was used to determine CNT/Cu interface adhesion properties. A cohesive zone model (CZM) was found to be most appropriate to model the interface adhesion, and CZM parameters at the nanoscale were determined using MD simulation. CZM parameters were then used in the finite element analysis in order to understand the mechanical and thermo-mechanical behavior of composite TSV at micro-scale. From the results, CNT/Cu separation does not take place prior to plastic deformation of Cu in bending, and separation does not take place when standard thermal cycling is applied. Further investigation is recommended in order to alleviate the increased plastic deformation in Cu at the CNT/Cu interface in both loading conditions.

Interplay between intrinsic point defects and low-angle grain boundary in bcc tungsten: effects of local stress field

We have used molecular statics in conjunction with an embedded atom method to explore the interplay between native point defects (vacancies and self-interstitials (SIAs)) and a low-angle grain boundary (GB) in bcc tungsten. The low-angle GB has biased absorption of SIAs over vacancies. We emphasize the significance of phenomena such as vacancy delocalization and SIA instant absorption around the GB dislocation cores in stabilizing the defect structures. Interstitial loading into the GB can dramatically enhance the interaction strength between the point defects and the GB due to SIA clustering (SIA cloud formation) or SIA vacancy recombination. We propose that the 'maximum atom displacement' can complement the 'vacancy formation energy' in evaluating unstable vacancy sites. Calculations of point defect migration barriers in the vicinity of GB dislocation cores show that vacancies and SIAs preferentially migrate along the pathways in the planes immediately above and below the core, respectively.

Cohesive Zone Model for the Interface of Multiwalled Carbon Nanotubes and Copper: Molecular Dynamics Simulation

Due to their superior mechanical and electrical properties, multiwalled carbon nanotubes (MWCNTs) have the potential to be used in many nano-/micro-electronic applications, e.g., through silicon vias (TSVs), interconnects, transistors, etc. In particular, use of MWCNT bundles inside annular cylinders of copper (Cu) as TSV is proposed in this study. However, the significant difference in scale makes it difficult to evaluate the interfacial mechanical integrity. Cohesive zone models (CZM) are typically used at large scale to determine the mechanical adherence at the interface. However, at molecular level, no routine technique is available. Molecular dynamic (MD) simulations is used to determine the stresses that are required to separate MWCNTs from a copper slab and generate normal stress–displacement curves for CZM. Only van der Waals (vdW) interaction is considered for MWCNT/Cu interface. A displacement controlled loading was applied in a direction perpendicular to MWCNT's axis in different cases with different number of walls and at different temperatures and CZM is obtained for each case. Furthermore, their effect on the CZM key parameters (normal cohesive strength (σmax) and the corresponding displacement (δn) has been studied. By increasing the number of the walls of the MWCNT, σmax was found to nonlinearly decrease. Displacement at maximum stress, δn, showed a nonlinear decrease as well with increasing the number of walls. Temperature effect on the stress–displacement curves was studied. When temperature was increased beyond 1 K, no relationship was found between the maximum normal stress and temperature. Likewise, the displacement at maximum load did not show any dependency to temperature.

Interfacial Strength Between Single Wall Carbon Nanotubes and Copper Material: Molecular Dynamics Simulation

Due to their promising mechanical and electrical properties, carbon nanotubes (CNTs) have the potential to be employed in many nano/microelectronic applications e.g., through silicon vias (TSVs), interconnects, transistors, etc. In particular, use of CNT bundles inside annular cylinders of copper (Cu) as TSV is proposed in this study. To evaluate mechanical integrity of CNT-Cu composite material, a molecular dynamics (MD) simulation of the interface between CNT and Cu is conducted. Different arrangements of single wall carbon nanotubes (SWCNTs) have been studied at interface of a Cu slab. Pullout forces have been applied to a SWCNT while Cu is spatially fixed. This study is repeated for several different cases where multiple CNT strands are interfaced with Cu slab. The results show similar behavior of the pull-out-displacement curves. After pull-out force reaches a maximum value, it oscillates around an average force with descending amplitude until the strand/s is/are completely pulled-out. A linear relationship between pull-out forces and the number of CNT strands was observed. Second order interaction effect was found to be negligible when multiple layers of CNTs were studied at the interface of Cu. C–Cu van der Waals (vdW) interaction was found to be much stronger than C–C vdW's interactions. Embedded length has no significance on the average pull-out force. However, the amplitude of oscillations increases as the length of CNTs increases. As expected when one end of CNT strand was fixed, owing to its extraordinary strength, large amount of force was required to pull it out. Finally, an analytical relationship is proposed to determine the interfacial shear strength between Cu and CNT bundle.

Modelling the sputtering of Au surfaces using a multi time-scale technique

We present results from an atomistic computer simulation model of the sputtering of gold crystal surfaces under 500 eV ion bombardment by Au and Ar ions for doses up to 10 14  ions cm −2 . The multi time-scale technique uses molecular dynamics to calculate the fast ballistic collision processes in the early stages of the cascade, whereas an on-the fly kinetic Monte Carlo technique is used to model the relaxation and diffusion processes between successive ion impacts when the defect motion has begun to be dominated by rare events. The results indicate a large amount of crystalline recovery between impacts, some facetting of the crystal surfaces but no large sub-surface defect accumulation. Because of this recovery process, sputtering yields and energy distributions are in good agreement with those obtained assuming a perfect crystal surface and also with those experimentally measured.

Atomistic Modeling of Extended Defects in Metalic Alloys: Dislocations and Grain Boundaries in Ll2 Compounds

Extended defects, such as dislocations and grain boundaries, control a wide variety of material properties and their atomic structure is often a governing factor. A necessary precursor for modeling of these structures is a suitable description of atomic interactions. We present here empirical many-body potentials for alloys which represent a very simple scheme for the evaluation of total energies and yet reflect correctly the basic physical features of the alloy systems modeled. As examples of atomistic studies we show results of calculations of the core structures of screw dislocations in Ll2 compounds. The same potentials have also been used to calculate structures of grain boundaries in these compounds. The deformation and fracture behavior of Ll2 alloys is then discussed in the light of grain boundary and dislocation core studies.

The Properties of Twinning Dislocations in Alpha-Titanium Simulated With A Many-Body Interatomic Potential

Computer simulation of the atomic structure and movement of twinning dislocations in four twin boundaries in the h.c.p. metal α-Ti is described. These dislocations have the form of steps on the twin boundary, and whereas some have cores which are very widely spread over the interface, others are only an interatomic spacing or so across. These configurations are determined mainly by whether or not atomic shuffles are required to restore the h.c.p. crystal structure when the dislocation is introduced. The mobility of the dislocations is also controlled by the same effect, and is found to correlate well with experiment.

Atomistic Simulation of Mobile Defect Clusters in Metals

The structure, stability and thermally-activated motion of interstitial and vacancy clusters in Fe and Cu have been studied using atomic scale computer simulation. All studied interstitial clusters and perfect interstitial loops (PILs) in Fe are mobile whereas their mobility in Cu can be suppressed at large sizes (bigger than 49–61 self-interstitials depending on the temperature) due to dissociation. A comparative study of relaxed configurations has shown that the structure of small perfect dislocation loops of vacancy and self-interstitial nature is very similar. Molecular dynamics simulation has demonstrated that small perfect vacancy loops (PVLs) in Fe consisting of more than 37 vacancies are stable over a wide temperature range and produce atomic displacements by a thermally-activated movement in the direction of the Burgers vector. The mechanism is qualitatively similar to that of SIA clusters studied earlier. Motion of vacancy loops in Cu does not occur because they transform into sessile configurations similar to stacking fault tetrahedra. These results point to the possibly important contribution of vacancy loop mobility to the difference in radiation damage between bcc and fcc metals, and between fcc metals with different stacking fault energy.

Kinetic Lattice Monte Carlo Simulations of Cascade Aging in Iron and Dilute Iron-Copper Alloys

Neutron hardening and embrittlement of pressure vessel steels is due to a high density of nm scale features, including copper-manganese-nickel rich precipitates and what are generally believed to be defect cluster-solute complexes. It has been postulated that the sub nanometer defect cluster-solute complexes form directly in displacement cascades. Cluster-complexes that are thermally unstable mediate the effect of flux on embrittlement kinetics. Larger cluster-complexes, that are relatively thermally stable for irradiation times up to 1 Gs, cause embrittlement in low copper steels. Robust characterization of these two types of so-called matrix defects has been an elusive goal. In this work, Kinetic Lattice Monte Carlo (KLMC) simulations of the long term evolution of the vacancy-rich cascade core regions were carried out for both pure iron and dilute iron-copper alloys at the nominal irradiation temperature of 563°K up to times when the vacancy clusters completely dissolve. Energetics were based on lattice embedded atom method potentials. Special time scaling and pulse annealing techniques were used to deal with the enormous range of inherent time scales involved, viz., rapid free vacancy jumps to slow emission from large complexes. Three-dimensional clusters rapidly form, containing a wide range of vacancies, as well as copper atoms in alloys. Small complexes are very mobile and growth takes place primarily by coalescence. The vacancy clusters ultimately dissolve at times from less than 0.1 to more than 100 MS. These simulations support the hypotheses that cascade cluster- complexes constitute both thermally stable and unstable matrix defect features.

Mobility of Self-Interstitial Clusters in FE and CU

Molecular dynamics (MD) simulation has been used to study the thermally activated mobility of clusters of self-interstitial atoms (SIAs) in Fe and Cu. Such clusters are formed in metals during irradiation with energetical particles and, according to the cascade production bias model, they play an important role in the microstructure evolution of metals under irradiation. An extensive simulation of clusters from 2 to 30 interstitials has been carried out for the temperature range ≍360-1200K using long-range interatomic pair potentials. The results show that clusters bigger than two SIAs are one-dimensionally mobile. Di-interstitials have two migration mechanisms depending on the temperature. At low temperature the mechanism is one-dimensional whereas at high temperature the probability of rotation and three-dimensional migration increases. It was found that in both metals the effective migration energy of clusters estimated via their jump frequency does not depend on the cluster size, although the cluster jump frequency decreases as the cluster size increases. The mechanism of cluster migration and problems of the treatment of one-dimensional mobility are discussed.

Atomistic simulation of slow grain boundary motion

Existing atomistic simulation techniques to study grain boundary motion are usually limited to either high velocities or temperatures and are difficult to compare to realistic experimental conditions. Here we introduce an adapted simulation method that can access boundary velocities in the experimental range and extract mobilities in the zero driving force limit at temperatures as low as ∼0.2T(m) (T(m) is the melting point). The method reveals three mechanistic regimes of boundary mobility at zero net velocity depending on the system temperature.

First principles calculations of vacancy-vacancy interactions in nickel: thermal expansion effects

The energetic properties of the divacancy defect in fcc nickel are studied by ab initio calculations based on density functional theory. The formation and binding enthalpies of the divacancy in the first (1nn), second (2nn) and third (3nn) nearest-neighbor configurations are presented. Results show that the 1nn divacancy configuration is the most stable with a formation enthalpy H(2v)(f) of 2.71 eV and a small binding energy H(2v)(b) of 0.03 eV. In the 2nn configuration, the monovacancy-monovacancy interaction is repulsive, and it vanishes in the 3nn configuration. The migration process of the divacancy in its stable configuration is studied. We find that the divacancy migrates in the (111) plane by successive rotational steps of 60°. The corresponding migration enthalpy H(2v)(m) is predicted to be 0.59 eV, about half of that found for the monovacancy. For a better comparison of our results with high temperature experimental data, we have analyzed the effects of thermal expansion. Our results show that the inclusion of thermal expansion allows us to reproduce satisfactorily the experimental predictions.