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Atomistic Simulations and Experimental Analysis of the Effect of Ti Additions on the Structure of NiAl

The Bozzolo-Ferrante-Smith (BFS) semiempirical method for alloy energetics is applied to the study of ternary additions to NiAl alloys. A detailed description of the method and its application to alloy design is given. Two different approaches are used in the analysis of the effect of Ti additions to NiAl. First, a thorough analytical study is performed, where the energy of formation, lattice parameter and bulk modulus are calculated for hundreds of possible atomic distributions of Ni, Al and Ti. Substitutional site preference schemes and formation of precipitates are thus predicted and analyzed. The second approach used consists of the determination of temperature effects on the final results, as obtained by performing a number of large scale numerical simulations using the Monte Carlo - Metropolis procedure and BFS for the calculation of the energy at every step in the simulation. The results indicate a sharp preference of Ti for Al sites in Ni-rich NiAl alloys and the formation of ternary Heusler precipitates beyond the predicted solubility limit of 5 at. % Ti. Experimental analysis of three NiAl+Ti alloys confirms the theoretical predictions.

Bozzolo, Guillermo

Atomistic Simulations of Ti Additions to NiAl

The development of more efficient engines and power plants for future supersonic transports depends on the advancement of new high-temperature materials with temperature capabilities exceeding those of Ni-based superalloys. Having theoretical modelling techniques to aid in the design of these alloys would greatly facilitate this development. The present paper discusses a successful attempt to correlate theoretical predictions of alloy properties with experimental confirmation for ternary NiAl-Ti alloys. The B.F.S. (Bozzolo-Ferrante-Smith) method for alloys is used to predict the solubility limit and site preference energies for Ti additions of 1 to 25 at.% to NiAl. The results show the solubility limit to be around 5% Ti, above which the formation of Heusler precipitates is favored. These results were confirmed by transmission electron microscopy performed on a series of NiAl-Ti alloys.

Bozzolo, Guillermo

'Atomistic' Simulation of Decanano Devices

When the devices are scaled to decanano dimensions the discreteness of charge and matter introduces significant 'intrinsic' parameter fluctuations. Atomic level 3D process and device modelling on statistical scale is required to understand the effects, the scale of the fluctuations and to design fluctuation resistant devices.

Asenov, Asen

Random Telegraph Signal Amplitudes in Sub 100 nm (Decanano) MOSFETs: A 3D 'Atomistic' Simulation Study

In this paper we use 3D simulations to study the amplitudes of random telegraph signals (RTS) associated with the trapping of a single carrier in interface states in the channel of sub 100 nm (decanano) MOSFETs. Both simulations using continuous doping charge and random discrete dopants in the active region of the MOSFETs are presented. We have studied the dependence of the RTS amplitudes on the position of the trapped charge in the channel and on the device design parameters. We have observed a significant increase in the maximum RTS amplitude when discrete random dopants are employed in the simulations.

Asenov, Asen

An Atomistic Simulation of Crack Propagation in a Nickel Single Crystal

The main objective of this paper is to determine mechanisms of crack propagation in a nickel single crystal. Motivation for selecting nickel as a case study is because we believe that its physical properties are very close to that of nickel-base super alloy. We are directed in identifying some generic trends that would lead a single crystalline material to failure. We believe that the results obtained here would be of interest to the experimentalists in guiding them to a more optimized experimental strategy. The dynamic crack propagation experiments are very difficult to do. We are partially motivated to fill the gap by generating the simulation results in lieu of the experimental ones for the cases where experiment can not be done or when the data is not available.

Majid Karimi

First Principles Based Reactive Atomistic Simulations to Understand the Effects of Molecular Hypervelocity Impact on Cassini's Ion and Neutral Mass Spectrometer

We report here on the predicted impact of species such as ice-water, CO2, CH4, and NH3, on oxidized titanium, as well as HC species on diamond surfaces. These simulations provide the dynamics of product distributions during and after a hypervelocity impact event, ionization fractions, and dissociation probabilities for the various species of interest as a function of impact velocity (energy). We are using these results to determine the relevance of the fragmentation process to Cassini INMS results, and to quantify its effects on the observed spectra.

hypervelocity collisions

Atomistic Simulations of Complex DNA DSBs and the Interactions with Ku70/80 Heterodimer

Compared to DNA with simple DSBs, the complex lesions can enhance the hydrogen bonds opening rate at the DNA terminus, and increase the mobility of the whole duplex. Binding of Ku drastically reduces the structural disruption and flexibility caused by the complex lesions. In all complex DSBs systems, the binding of DSB terminus with Ku70 is softened while the binding of the middle duplex with Ku80 is tightened. Binding of Ku promotes the rigidity of DNA duplexes, due to the clamp structure of the inner surface of the rings of Ku70/80.

Hu, Shaowen

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics

Ductility mechanisms in complex concentrated refractory alloys from atomistic fracture simulations

The striking variation in damage tolerance among refractory complex concentrated alloys is examined through the analysis of atomistic fracture simulations, contrasting behavior in elemental Nb with that in brittle NbMoTaW and ductile Nb45Ta25Ti15Hf15. We employ machine-learning interatomic potentials (MLIPs), including a new MLIP developed for NbTaTiHf, in atomistic simulations of crack tip extension mechanisms based on analyses of atomistic fracture resistance curves. While the initial behavior of sharp cracks shows good correspondence with the Rice theory, fracture resistance curves reveal marked changes in fracture modes for the complex alloys as crack extension proceeds. In NbMoTaW, compositional complexity appears to promote dislocation nucleation relative to pure Nb, despite theoretical predictions that the alloy should be relatively more brittle. In Nb45Ta25Ti15Hf15, alloying alters the fracture mode compared to elemental Nb, promoting crack tip blunting and enhancing resistance to crack propagation.

Computational methods

Multiscale Modeling of Damage Processes in Aluminum Alloys: Grain-Scale Mechanisms

This paper has two goals related to the development of a physically-grounded methodology for modeling the initial stages of fatigue crack growth in an aluminum alloy. The aluminum alloy, AA 7075-T651, is susceptible to fatigue cracking that nucleates from cracked second phase iron-bearing particles. Thus, the first goal of the paper is to validate an existing framework for the prediction of the conditions under which the particles crack. The observed statistics of particle cracking (defined as incubation for this alloy) must be accurately predicted to simulate the stochastic nature of microstructurally small fatigue crack (MSFC) formation. Also, only by simulating incubation of damage in a statistically accurate manner can subsequent stages of crack growth be accurately predicted. To maintain fidelity and computational efficiency, a filtering procedure was developed to eliminate particles that were unlikely to crack. The particle filter considers the distributions of particle sizes and shapes, grain texture, and the configuration of the surrounding grains. This filter helps substantially reduce the number of particles that need to be included in the microstructural models and forms the basis of the future work on the subsequent stages of MSFC, crack nucleation and microstructurally small crack propagation. A physics-based approach to simulating fracture should ultimately begin at nanometer length scale, in which atomistic simulation is used to predict the fundamental damage mechanisms of MSFC. These mechanisms include dislocation formation and interaction, interstitial void formation, and atomic diffusion. However, atomistic simulations quickly become computationally intractable as the system size increases, especially when directly linking to the already large microstructural models. Therefore, the second goal of this paper is to propose a method that will incorporate atomistic simulation and small-scale experimental characterization into the existing multiscale framework. At the microscale, the nanoscale mechanics are represented within cohesive zones where appropriate, i.e. where the mechanics observed at the nanoscale can be represented as occurring on a plane such as at grain boundaries or slip planes at a crack front. Important advancements that are yet to be made include: 1. an increased fidelity in cohesive zone modeling; 2. a means to understand how atomistic simulation scales with time; 3. a new experimental methodology for generating empirical models for CZMs and emerging materials; and 4. a validation of simulations of the damage processes at the nano-micro scale. With ever-increasing computer power, the long-term ability to employ atomistic simulation for the prognosis of structural components will not be limited by computation power, but by our lack of knowledge in incorporating atomistic models into simulations of MSFC into a multiscale framework.

Hochhalter, J. D.