Diffusion behavior in Nickel–Aluminum and Aluminum–Uranium diluted alloys

Ramunni, V.P.

doi:10.1016/j.commatsci.2014.06.039

Cited by 11 publications

(10 citation statements)

References 51 publications

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“…A similar accordance with experimental data have been obtained using also a classical model, namely classical Kinetic Monte Carlo algorithm with temperature dependent pair interactions [4]. It must be noted that, the agreement between CMS calculation and experimental data is not fortuitous, it have been recently observed for diffusion in NiÀAl and AlÀU fcc lattices [3]. Hence, the atomic diffusion process in metals is a classical phenomena, for which the large number of atoms and the temperature has suppressed any coherent effect.…”

Section: Discussionsupporting

confidence: 83%

“…On the other hand, employing classical molecular statics (CMS) technique, in order to obtain the needed frequency jumps, one of us has presented studies of impurity diffusion behavior in NickelAluminium and Aluminium-Uranium fcc diluted alloys [3]. It is then shown that all the diffusion coefficients obtained with CMS are in good agreement with experimental data for both alloys.…”

Section: Introductionmentioning

confidence: 76%

“…It can be seen from (55) that If L VS is negative (G > À1), solute and vacancy are moving in opposite directions, while, if L VS positive (G < À1), a drag mechanism is dominant implying that vacancies and solutes are moving in the same direction [3,5,8]. The parameter G for fcc structures is calculated from the L-coefficients expressions, (16)e(18) and (31)e(38), for bcc and fcc lattices respectively.…”

Section: The Tracer Diffusion Coefficients For Diluted Alloysmentioning

confidence: 98%

“…In the linear response framework the diffusion coefficients, as was early shown [3,5], can be entirely expressed in terms of the commonly known Onsager coefficients L ij . The L ij are the fundamental kinetic quantities.…”

Section: Introductionmentioning

confidence: 99%

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Diffusion behavior of Cr diluted in bcc and fcc Fe: Classical and quantum simulation methods

Ramunni

Rivas

2015

Materials Chemistry and Physics

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 76%

Section: The Tracer Diffusion Coefficients For Diluted Alloysmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Diffusion behavior of Cr diluted in bcc and fcc Fe: Classical and quantum simulation methods

Ramunni

Rivas

2015

Materials Chemistry and Physics

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“…The following numerical data were used: activation barriers for elementary diffusion of Ni, Cr, and Al in Ni alloys were E Ni = 1.08 eV, E Cr = 0.81 eV, and E Al = 0.70 eV for bulk alloys, and E Ni = 0.35 eV, E Cr = 0.09 eV, and E Al = 0.15 eV for the higher energy Σ = 9/(221) grain boundary. 24 Note that the activation barriers for a low-energy Σ = 3/(111) grain boundary are very similar to those in the bulk, 24 11,27 Simulations were performed at 360 • C matching the temperature employed in the experimental work. The PNP/cDFT simulations were done using code we have developed, which is parallelized by the multigrid approach and a linear scaling with respect to the number of grid points has been achieved.…”

Section: B Theorymentioning

confidence: 99%

Multiscale model of metal alloy oxidation at grain boundaries

Sushko

Alexandrov

Schreiber

et al. 2015

The Journal of Chemical Physics

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High temperature intergranular oxidation and corrosion of metal alloys is one of the primary causes of materials degradation in nuclear systems. In order to gain insights into grain boundary oxidation processes, a mesoscale metal alloy oxidation model is established by combining quantum Density Functional Theory (DFT) and mesoscopic Poisson-Nernst-Planck/classical DFT with predictions focused on Ni alloyed with either Cr or Al. Analysis of species and fluxes at steady-state conditions indicates that the oxidation process involves vacancy-mediated transport of Ni and the minor alloying element to the oxidation front and the formation of stable metal oxides. The simulations further demonstrate that the mechanism of oxidation for Ni-5Cr and Ni-4Al is qualitatively different. Intergranular oxidation of Ni-5Cr involves the selective oxidation of the minor element and not matrix Ni, due to slower diffusion of Ni relative to Cr in the alloy and due to the significantly smaller energy gain upon the formation of nickel oxide compared to that of Cr2O3. This essentially one-component oxidation process results in continuous oxide formation and a monotonic Cr vacancy distribution ahead of the oxidation front, peaking at alloy/oxide interface. In contrast, Ni and Al are both oxidized in Ni-4Al forming a mixed spinel NiAl2O4. Different diffusivities of Ni and Al give rise to a complex elemental distribution in the vicinity of the oxidation front. Slower diffusing Ni accumulates in the oxide and metal within 3 nm of the interface, while Al penetrates deeper into the oxide phase. Ni and Al are both depleted from the region 3-10 nm ahead of the oxidation front creating voids. The oxide microstructure is also different. Cr2O3 has a plate-like structure with 1.2-1.7 nm wide pores running along the grain boundary, while NiAl2O4 has 1.5 nm wide pores in the direction parallel to the grain boundary and 0.6 nm pores in the perpendicular direction providing an additional pathway for oxygen diffusion through the oxide. The proposed theoretical methodology provides a framework for modeling metal alloy oxidation processes from first principles and on the experimentally relevant length scales.

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