We employ Monte Carlo simulation in the semi-grand canonical ensemble to obtain the coarse-grained free energy corresponding to an embedded-atom method description of a binary alloy. In particular, the Ginzburg-Landau free energy for a Cu–Ni alloy was determined from a tabulated histogram of the joint probability density of composition, energy, and volume. Using histogram reweighting techniques, the free energy is extrapolated to a range of points in parameter space from a small number of simulations. The results are interpreted by comparing the free energy with that corresponding to a regular solution model of an alloy. In addition, we obtain expressions for thermodynamic quantities in terms of the joint cumulants of the probability density at a given temperature and chemical potential difference. These expressions may then be likewise extrapolated to obtain the dependence of the composition on the temperature and the chemical potential difference over a wide range of parameter space.

1.
K.
Binder
,
Phys. Rev. Lett.
47
,
693
696
(
1981
).
2.
K.
Kaski
,
J. D.
Gunton
, and
K.
Binder
,
Phys. Rev. B
29
,
3996
(
1983
).
3.
A. D.
Bruce
and
N. B.
Wilding
,
Phys. Rev. Lett.
68
,
193
(
1992
).
4.
N. B.
Wilding
,
Phys. Rev. E
52
,
602
(
1995
).
5.
M.
Gracheva
,
J. M.
Rickman
, and
J. D.
Gunton
,
J. Chem. Phys.
113
,
3525
3529
(
2000
).
6.
M.
Asta
and
S. M.
Foiles
,
Phys. Rev. B
53
,
2389
2404
(
1996
).
7.
R.
LeSar
and
R.
Najafabadi
, and
D. J.
Srolovitz
,
Phys. Rev. Lett.
63
,
624
627
(
1989
).
8.
J. M.
Rickman
and
D. J.
Srolovitz
,
Philos. Mag. A
67
,
1081
1094
(
1993
).
9.
H. Y.
Wang
,
R.
Najafabadi
, and
D. J.
Srolovitz
, and
R.
LeSar
,
Phys. Rev. B
45
,
12028
12042
(
1992
).
10.
H. Y.
Wang
,
R.
Najafabadi
, and
D. J.
Srolovitz
, and
R.
LeSar
,
Interface Sci.
1
,
7
30
(
1993
).
11.
D.
Kofke
and
E.
Glandt
,
Mol. Phys.
64
,
1105
1131
(
1988
).
12.
S. M.
Foiles
,
Phys. Rev. B
32
,
7685
7693
(
1985
).
13.
S. M.
Foiles
,
Mater. Res. Soc. Symp. Proc.
63
,
61
66
(
1985
).
14.
H. B.
Callen
,
Thermodynamics and an Introduction to Thermostatistics
(
Wiley
,
Hoboken, NJ
,
1985
).
15.
C. H. P.
Lupis
,
Chemical Thermodynamics of Materials
(
Prentice-Hall
,
Englewood Cliffs, NJ
,
1983
).
16.
B.
Fultz
,
Prog. Mater. Sci.
55
,
247
352
(
2010
).
17.
P. C.
Clapp
and
S. C.
Moss
,
Phys. Rev.
142
,
418
(
1966
).
18.
P. C.
Clapp
and
S. C.
Moss
,
Phys. Rev.
171
,
754
(
1968
).
19.
A. M.
Ferrenberg
and
R. H.
Swendsen
,
Phys. Rev. Lett.
61
,
2635
(
1988
).
20.
A. M.
Ferrenberg
and
R. H.
Swendsen
,
Phys. Rev. Lett.
63
,
1195
(
1989
).
21.
J. M.
Rickman
and
S. R.
Phillpot
,
Phys. Rev. Lett.
66
,
349
(
1991
).
22.
N. G.
van Kampen
,
Stochastic Processes in Physics and Chemistry
(
North-Holland
,
Amsterdam
,
1992
).
23.
The semi-grand partition function, Ψ(T, P, Δμ) used here is related to the partition function, Υ(T, V, Δμ), defined in Ref. 11 by the transformation
$\Psi \left(T,P,\Delta \mu \right) = \int _{0}^{\infty } dV exp{\left(-\beta P V \right)}\; \Upsilon \left(T,V,\Delta \mu \right)$
ΨT,P,Δμ=0dVexpβPVΥT,V,Δμ
.
24.
A.
DasGupta
,
Asymptotic Theory of Statistics and Probability
(
Springer
,
New York
,
2008
). In practice, with the large number of samples in our simulations, other estimators can equally well be used.
25.
R.
Kubo
,
J. Phys. Soc. Jpn.
17
,
1100
(
1962
).
You do not currently have access to this content.