higher temperature, about 1200 K. This feature was explained
[52]
by the
contribution of short-circuit diffusion, since polycrystalline material was
used. Frank et al.
[53]
thoroughly measured Ni self-diffusion, combining the
tracer technique at higher temperatures and the SIMS analysis at lower
ones in poly- and single-crystalline Ni
3
Al, respectively. No curvature of
the Arrhenius plot was established [see Fig. 4.8(a)], confirming the expla-
nation given by Shi et al.
[52]
These data indicate that only one diffusion
mechanism operates in the temperature interval under consideration. This
mechanism is commonly identified with the Ni-sublattice diffusion mech-
anism.
[52, 53]
According to this mechanism, a Ni vacancy performs random
jumps in the Ni sublattice with the coordination number 8 (see Fig. 4.5).
Some controversy still exists about the compositional dependence of
Ni self-diffusion in Ni
3
Al (Fig. 4.9). Hoshino et al.
[51]
have found a shal-
low minimum of D
*
Ni
at the stoichiometric composition below T 1100 K.
Shi et al.
[52]
also observed such a minimum in D
*
Ni
, but around 76 at.% Ni
and, again, at the lowest temperature of their investigations, about 1200 K.
At higher temperatures, the variation of D
*
Ni
with composition in all inves-
tigations was within experimental uncertainities. These fine features
resulted in a maximum activation enthalpy Q
Ni
at about 76 at.% Ni
[52]
(Fig. 4.9). Since Ni grain boundary diffusion in Ni
3
Al shows a deep min-
imum at the stoichiometric composition, Frank and Herzig
[55]
suggested
that short-circuit diffusion via grain boundaries affected the low-temperature
data of Hoshino et al.
[51]
and Shi et al.,
[52]
and produced a slight minimum
in the bulk diffusion data. Comparing results of different investigations,
Fig. 4.9 suggests that the change of the activation enthalpy Q
Ni
with com-
position in Ni
3
Al is within experimental uncertainties. In contrast, a min-
imum in D
*
Ni
was found in a recent Monte Carlo study of Ni diffusion in
Ni
3
Al at the stoichiometric composition
[56]
due to the existence of Al and
Ni antistructure atoms in Ni- and Al-rich alloys, which enhance Ni self-
diffusion by lowering the energy barriers for the Ni vacancy jumps. In that
approach, pair interaction potentials were used and no lattice relaxation
was taken into account.
For additional insight into this problem, we simulated self-diffusion
in Ni
3
Al using the Voter and Chen EAM potentials.
[24]
The calculations
show that there is a negligible effect of adjacent Ni and Al antistructure
atoms on the energy barriers for Ni vacancies performing jumps via the
Ni sublattice. (The energy barriers change by about 10 kJ/mol, depend-
ing on the particular configuration.) Thus, the vacancy jump rates are
nearly the same, regardless of the composition of Ni
3
Al. Calculations of
the Ni vacancy concentration [Fig. 4.3(c)] and the effective formation
energies also resulted in very similar values for Al-rich, stoichiometric,
and Ni-rich compounds. Simultaneous Monte Carlo simulations of the
correlation effects demonstrated that the correlation factor for the Ni
192 DIFFUSION PROCESSES IN ADVANCED TECHNOLOGICAL MATERIALS