Gianmarco Munaò1, Santi Prestipino1, Jean-Marc Bomont2, Dino Costa1. 1. Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra, Università degli Studi di Messina, viale F. Stagno d'Alcontres 31, 98166 Messina, Italy. 2. Université de Lorraine, LCP-A2MC, UR 3469, 1 Blvd. François Arago, Metz F-57078, France.
Abstract
Self-assembling complex fluids are often modeled as particles with effective competing isotropic interactions, combining a short-range attraction (SA) followed by a longer-range repulsion (LR). For moderately low temperatures and densities, SALR particles form clusters in equilibrium, at least provided that the potential parameters are appropriate. Here we inquire into the possibility that cluster formation in SALR fluids might be pushed by a foreign species even under thermodynamic conditions that would not allow for clusterization of the pure system. To this aim, we study by Monte Carlo simulations a mixture of hard-sphere two-Yukawa particles and hard spheres, with a cross interaction modeled by a square-well attraction, and we investigate the conditions of clustering in terms of strength of attraction and relative concentration of the two species. We find that clusters can occur in the mixture for the same temperature and density where the pure SALR fluid is almost structureless. In particular, we single out a cross attraction such that clusters are formed with a SALR concentration as low as 5%. We also find a situation where nearly pure droplets of hard spheres are held together by a shell of SALR particles. Conversely, we show that clustering can be undermined in the mixture under conditions for which this process takes place in the parent SALR fluid. Using a simple criterion, based on the second virial coefficients of the attractive part of interaction potentials (the so-called "reference attractive fluids"), we are able to predict accurately whether clustering is favored (or hindered) in the mixture, as compared to the pure SALR fluid.
Self-assembling complex fluids are often modeled as particles with effective competing isotropic interactions, combining a short-range attraction (SA) followed by a longer-range repulsion (LR). For moderately low temperatures and densities, SALR particles form clusters in equilibrium, at least provided that the potential parameters are appropriate. Here we inquire into the possibility that cluster formation in SALR fluids might be pushed by a foreign species even under thermodynamic conditions that would not allow for clusterization of the pure system. To this aim, we study by Monte Carlo simulations a mixture of hard-sphere two-Yukawa particles and hard spheres, with a cross interaction modeled by a square-well attraction, and we investigate the conditions of clustering in terms of strength of attraction and relative concentration of the two species. We find that clusters can occur in the mixture for the same temperature and density where the pure SALR fluid is almost structureless. In particular, we single out a cross attraction such that clusters are formed with a SALR concentration as low as 5%. We also find a situation where nearly pure droplets of hard spheres are held together by a shell of SALR particles. Conversely, we show that clustering can be undermined in the mixture under conditions for which this process takes place in the parent SALR fluid. Using a simple criterion, based on the second virial coefficients of the attractive part of interaction potentials (the so-called "reference attractive fluids"), we are able to predict accurately whether clustering is favored (or hindered) in the mixture, as compared to the pure SALR fluid.
Nowadays, it is well
recognized that the phase behavior of a complex
fluid can be significantly rich and intriguing, owing to its ability
to self-assemble into aggregates exhibiting modulated patterns at
the mesoscale.[1−7] In this context, a large variety of colloidal dispersions, as well
as block copolymer melts and solutions of amphiphilic molecules, can
be described by effective pair interactions featuring a short-range
attraction (SA) followed, at larger distances, by a long-range repulsion
(LR) .[8−14] While the SA component, originating from van der Waals and/or depletion
forces, favors particle aggregation, the LR component arises from
electrostatic forces and imposes a penalty on the growth of a dense
macroscopic phase. The distinguishing feature of SALR fluids is their
attitude to self-assemble into equilibrium structures of various morphologies[15−23] characterized by spatial inhomogeneities whose typical length is
larger than the particle size, but definitely not macroscopic. The
size and shape of these patterns strongly depend on the detailed force
parameters, as well as on the values of the thermodynamic variables
(i.e., the temperature T and the density ρ).
Generally speaking, the knowledge of this dependence can be exploited
to steer the process of self-assembling toward the formation of the
desired structure. For example, for moderately low values of T, one expects to see clusters in the dilute fluid, giving
way to a percolated fluid at higher densities.[18,19,24,25] Using density-functional
theory, it has been shown that, for sufficiently low temperatures,
SALR particles give rise to periodic microphases exhibiting (in increasing
order of density) clusters, cylinders, lamellae, inverted cylinders,
and inverted clusters, just to name the simplest structures.[26−29] The equilibrium phase diagram of a cluster-forming fluid has been
also reconstructed by a thermodynamic model and assessed by computer
simulation.[30] The broad interest in the
physics of SALR fluids is witnessed by four recent reviews on this
subject.[31−34]If we restrict to low-density conditions, such that the self-organized
aggregates would essentially be clusters, the crucial problem is clearly
how to establish the occurrence of clusters in the simulation sample.
From a structural point of view, the characteristic condition for
the development of microphases would be a maximum in the static structure
factor S(k) at a wavenumber k0 ≠ 0, well below the location of the
main diffraction peak;[34−36] by contrast, a diverging S(0) invariably
implicates liquid–vapor separation. In fact, in a hard-sphere
two-Yukawa (HSTY) fluid—a prototypical instance of an SALR
fluid—the existence of a low-k peak in S(k) is not by itself sufficient to identify
a cluster phase;[18,19,35,36] rather, this peak is indicative of the development
of some kind of modulation (intermediate-range order), in the fluid.
As a matter of fact, a low-k peak can occur under
four different structural conditions, i.e., a monomer-dominated fluid,
a cluster fluid, a random percolated fluid, and a cluster percolated
fluid, as can be discriminated from the shape of the cluster-size
distribution (CSD).[18,19] In particular, a monotonically
decreasing CSD represents a fluid of nonbonded particles, whereas
the presence of a maximum in the CSD unambiguously identifies a cluster
fluid. When more than 50% of the particles are collected in the same
network, the system undergoes percolation. If the CSD exhibits a single
peak at a size comparable with the system size, then we speak of a
random percolated fluid. On the other hand, if in addition to this
peak the CSD also shows the maximum typical of a cluster fluid, then
we have a cluster percolated fluid. Interestingly, when the height
of the low-k peak exceeds a value ≈3, then
the system is either a cluster fluid or a cluster percolated fluid.[18,19] This empirical rule-of-thumb, reminiscent of the Hansen–Verlet
criterion for freezing of simple fluids,[37] is a useful means to locate the onset of a cluster phase. Other
criteria, based on structural indicators, have been proposed to identify
the onset of clustering in SALR fluids, either in terms of specific
features of the low-k peak[38,39] or in terms of the properties of real-space correlations.[40−42] As for thermal properties, a maximum is generally expected in the
constant-volume specific heat at the crossover between the monomer-
and the cluster-dominated fluid, since here a randomly selected particle
can equally be found as isolated or belonging to a cluster of nearly
optimal size.[43] This leads to strong energy
fluctuations and thus to a specific-heat peak, which then provides
a practical, easily accessible tool to discriminate between different
aggregation regimes.[43]So far, our
discussion has been limited to one-component SALR fluids,
though it is clear that the self-assembling scenario of a binary mixture
is potentially far richer. In this regard, one way to induce a spatially
modulated pattern in a mixture with attractive and repulsive short-range
forces would be to employ a suitable molecular structure for one of
the species; see, e.g., ref (44). Recently, we have followed this route in a number of papers[45−51] where we have reported on a variety of self-assembling structures
in a mixture made up of amphiphilic dimers and hard spheres. A second
possibility would be to adopt a fully coarse-grained view to the problem,
by considering a mixture of monatomic species, but then we must leverage
on the shape of interactions to produce stable microphases. Examples
of such mixtures are found in refs (52 and 53). In these studies, the particle core of both species is harshly
repulsive, self-interactions are of SALR type, and the cross interaction
is repulsive in the core and attractive at short distances. The force
parameters are so tuned that, for sufficiently low T and ρ, a one-component system of SALR particles forms clusters.
In another study, the self-interaction of one species was purely attractive
outside the core.[54] Then, if the cross
interaction is weak, this species undergoes liquid–vapor separation
at low T. For a strong cross attraction, the resulting
clusters are composed of the two species in more or less equal proportions.In the present paper, we study a mixture of two monatomic species:
type-1 particles interact via a HSTY potential, whereas type-2 particles
are simple hard spheres (HS). Outside the core, the cross interaction
is a square-well (SW) potential of depth ε12. The
proposed model would represent a generic colloidal mixture where species
1 is a cluster-former, whereas particles of species 2 are relatively
blind to each other, even though—due to its affinity to species
1—they will actively participate in the formation of aggregates.
Moreover, our system can describe the large class of soft materials—as
for instance solutions of biomolecules—in which solutes interact
through screened-Coulomb potentials with other species. Our mixture
has similarities with (and also differences from) the model investigated
in ref (54). For instance,
the type-2 interaction in the latter model reduces to hard-core interaction
in the limit of vanishing attraction. On the other hand, the cross
attraction is different, being a SW here and a Yukawa attraction in
ref (54). Our choice
possibly allows one to more effectively discriminate the role played
by the cross interaction in the overall organization of the mixture.
Finally, in ref (54), the mechanism of clustering is mainly investigated through a thermodynamic
model, whereas our approach is exclusively simulation-based.Once established the above-mentioned setup, two questions will
be addressed in the following: first, the role played by HS particles
in the formation of clusters of HSTY particles, as a function of ε12 and relative concentration. Second, the conditions under
which the HSTY particles are able to induce droplets of HS particles.
In particular, it would be interesting to know whether the HSTY particles
can form a coating shell around the HS particles, as it occurs for
amphiphilic dimers in mixtures with a small fraction of hard spheres.[47,49−51]The rest of the paper is organized as follows.
In Section we describe
the model and
the simulation method to perform the investigation. Sections –V contain the core of our study: first, we focus on the pure
HSTY fluid (Section ), establishing the temperature below which a cluster phase is stable
for a specific low value of the density. This analysis is preliminary
to the study of a HSTY–HS mixture, for which we examine the
effect of strengthening the cross interaction (Section ) or changing the relative concentration
(Section ), until
we clarify the exact terms of the interplay between the two species
with regard to clustering. Some concluding remarks follow in Section .
Model and Methods
Our mixture consists of hard-sphere two-Yukawa
particles and hard
spheres, henceforth labeled 1 and 2 respectively, with the same core
diameter σ. Beyond the hard core, the HSTY interaction is given
bywhere r* = r/σ; ε11 is the potential minimum at σ; za, and zr are the
inverse range of attraction and repulsion, respectively; α is
the ratio of strength of repulsion to attraction. The range of the
attractive well extends up toi.e., the zero of u11(r). In particular, we choose za = 10, zr = 0.5,
and α
= 0.1, and therefore, r0 ≃ 1.242σ.
With this parametrization, u11(r) corresponds to the HSDY1 case studied in ref (18). The cross interaction u12(r) is provided by a SW attraction
of depth ε12 (with the ratio ε12/ε11 varying between 0.01 and 1) and range r0. With this prescription, the HSTY and SW interactions
have the same attractive range. In Figure , we plot the shapes of u11(r) and u12(r) for all the values of ε12 investigated
in this work. We take σ and ε11 as units of
length and energy, respectively. Then, the density is given in units
of σ–3 while the temperature is measured in
units of ε11/kB, where kB is the Boltzmann constant.
Figure 1
Interatomic potentials
investigated in this work: the HSTY potential u11(r) (eq , black line), and the SW cross interaction u12(r), plotted for all ε12 investigated in this work (in the legend). The HS interaction u22(r) is not shown.
Interatomic potentials
investigated in this work: the HSTY potential u11(r) (eq , black line), and the SW cross interaction u12(r), plotted for all ε12 investigated in this work (in the legend). The HS interaction u22(r) is not shown.We carry out canonical-ensemble Monte Carlo (MC) simulations
of
a mixture composed of N1 HSTY particles
and N2 HS particles, with N = N1 + N2 = 2048, enclosed in a cubic box with periodic boundary conditions
to reduce surface effects. The concentration N1/N of HSTY particles is denoted χ.
Before moving to the mixture, we have studied a one-component system
of 500 HSTY particles, to fix reference thermodynamic conditions for
the clustering of the pure fluid. Thereby, we have set ρ = 0.05, T in the range 0.20–0.25, whereas χ varies
over the full range of relative concentrations. In our simulations, u11(r) is truncated at half
the box length (10.77σ for the pure HSTY fluid and 17.23σ
for the mixture). The chosen density is high enough to allow for cluster
formation at low temperatures, but still sufficiently low to prevent
packing effects from playing any role. In the selected temperature
range, the pure HSTY fluid undergoes the transformation from a weakly
inhomogeneous state to a deeply clustered state.The particles
are initially distributed at random (T = ∞); then, the system is quenched at a
given temperature T and equilibrated. From our experience
on self-assembling mixtures we know that a huge number (higher than
108) of MC cycles is typically required to properly equilibrate
the system at low temperatures. Therefore, we have optimized our MC
code in the attempt to make the numerical algorithm converge faster.
In particular, we have implemented two distinct values for the maximum
random displacement (mrd) of a particle, so as to account for the
possible existence of two different (intracluster and intercluster)
length scales in the system. The two mrd values are adjusted during
the equilibration run until the acceptance of translational MC moves
is around 30% for the longer moves and 80% for the shorter ones. This
gives mrd values of ≈0.1σ and ≈0.01σ, respectively.
Furthermore, we have introduced swapping moves, whereby the positions
of two randomly chosen HSTY and HS particles are exchanged. For both
moves, acceptance is decided based on the standard Metropolis test.
The schedule of all moves, the canonical moves and the new ones, is
such that detailed balance holds exactly at each step.The structure
of the mixture is investigated by computing the radial
distribution function g(r) and the structure factor S(k), with i and j labeling the two different species. Structure
factors are calculated as Fourier transforms of g(r), according to
the formula[37]To gain knowledge on the self- and cross-correlations
of global
variables, we also compute the Bathia–Thornton number–number,
concentration–concentration, and number-concentration structure
factors of the mixture, defined as[55,56]respectively.Aggregates are characterized
through a cluster analysis performed
by the Hoshen–Kopelman algorithm.[57] According to our convention, two particles (of whatever species)
are bonded if they are separated by less than r0, i.e., if the particles fall within the range of the SA/SW
potential. Following refs[18 and 58], the CSD is taken to bewhere n(s) is the average number
of clusters with size s in
a single configuration. The distribution N(s) is normalized in such a way that ∑N(s) = 1. In our
study, the distribution of cluster sizes is computed by averaging
over 1000 equispaced configurations extracted from the last part of
the production run.
Pure HSTY Fluid
Information about the structure attained by the HSTY fluid long
after the initial quench can be gained from the profile of the total
structure factor SNN(k) ≡ S11(k), reported
in Figure . For T = 0.25, the height of its low-k peak,
located at k0σ ≈ 1, attains
a value ≈1.8, which would suggest, according to the heuristic
criterion of refs (18 and 19), that the fluid exhibits intermediate-range order. This condition
preludes to the subsequent development of more structured aggregates
for T = 0.22, where indeed S11(k0) rises to ≈4.2, i.e.,
above the clustering threshold of ≈3. Based on the structural
evidence, for T = 0.20 [where S11(k0) exceeds 10] clusters appear
to be well structured. As for the real-space structure, we report
in the inset of Figure the radial distribution function g11(r) for the same three temperatures. While for T = 0.25 the system is little structured, the multiple solid-like
peaks of g11(r) for T = 0.22, and even more so for T = 0.20,
indicate a high degree of order in the arrangement of particles around
a reference particle, i.e., within the linear extent of a cluster.
The subsequent long-range oscillations in the spatial correlations
for r ≳ 4σ are another well-known indication
that a modulated phase is taking over in the fluid.
Figure 2
Structure factor and
radial distribution function (inset) of the
pure HSTY fluid for ρ = 0.05 and three different temperatures
(in the legend).
Structure factor and
radial distribution function (inset) of the
pure HSTY fluid for ρ = 0.05 and three different temperatures
(in the legend).The local arrangement
of the HSTY fluid is better elucidated by
a visual inspection of microscopic configurations, see Figure . For T =
0.25 (A), in the wake of development of intermediate-range order,
the fluid appears to be overall homogeneous, even though local inhomogeneities
are occasionally seen. Instead, for T = 0.22 (B),
the tendency of particles to aggregate is more evident, with clusters
starting to form in the system. For T = 0.20 (C),
very few particles are isolated and the cluster shape is approximately
spherical. Information on the cluster structure can be gained from
the CSD, plotted in Figure D: this decays monotonically for T = 0.25,
certifying that the system almost behaves as a dispersed fluid. For T = 0.22 a shallow peak develops around s = 15, witnessing the presence of clusters with this typical size.
The sign of clustering becomes definitely sharp at T = 0.20, where a distinct peak is visible in the CSD at s ≈ 20.
Figure 3
Microscopic configurations of the pure HSTY fluid. (A) T = 0.25; (B) T = 0.22; (C) T = 0.20; (D) CSD at the same temperatures.
Microscopic configurations of the pure HSTY fluid. (A) T = 0.25; (B) T = 0.22; (C) T = 0.20; (D) CSD at the same temperatures.To summarize this section, we have a coherent structural and microscopic
picture showing that in the HSTY fluid with density ρ = 0.05
clusters are absent for T = 0.25; they start appearing
for T = 0.22 and are fully developed for T = 0.20. In another study of the same model,[18] at about twice the density analyzed here, the
fluid for T = 0.25 was found in a clustered state,
suggesting that the characteristic temperatures marking the onset
of the various aggregation stages—intermediate-range order
first and clustered state afterward, possibly evolving into an arrested
state along the so-called λ-line—show a shallow parabolic
trend as a function of density, which is reminiscent of the liquid–vapor
binodal in fluids with short-range attraction.
Equimolar
HSTY–HS Mixture
Having clarified the behavior of the
HSTY fluid, we move to the
binary mixture obtained from the former by replacing half of the particles
with hard spheres (i.e., χ = 0.5). We choose thermodynamic conditions—ρ
= 0.05 and T = 0.25—such that, as shown in
the previous section, no stable clusters are present in the HSTY fluid.
Our purpose is to establish whether the presence of another species,
able to provide a bridge between two nearby HSTY particles, is sufficient
to promote cluster formation. In principle, this is one out of several
scenarios that could hypothetically arise once the balance between
attraction and repulsion in the mixture moves in favor of the former;
other two plausible outcomes, related to the strength of cross attraction
ε12, are that either the mixture stays almost homogeneous
as the pure HSTY fluid or, at the opposite end, that the mutual attraction
is now strong enough to overcome the competition with repulsion, thus
giving rise to liquid–vapor separation. In this regard, it
seems unlikely that demixing can occur, because ruled out by the 1–2
attraction.To ascertain this issue we have simulated equimolar
mixtures for
values of ε12 in the range 0.01–1 (in units
of ε11). Results for the potential energy are collected
in Figure : as a preliminary
observation, the equilibration time strongly depends on ε12, ranging from 106 MC cycles for ε12 = 0.01 to 108 or more MC cycles for ε12 = 1. To check whether equilibrium has been reached—especially
for the deepest attractions, ε12 > 0.50—we
have performed additional simulations for ε12 = 0.75
and ε12 = 1, using a big spherical cluster encompassing
all particles as initial configuration, see Figure A. As for ε12 = 0.75, we
have verified that the final state of the system along this route
(in terms of potential energy, structural, and microscopic appearance,
see Figure B–D)
matches with the previous one, indicating that equilibrium has eventually
been attained. On the other hand, for ε12 = 1, the
time needed for the decay of the big-cluster configuration is much
longer than we could achieve in our analysis. Our conclusion, also
supported by the slow energy drift in Figure , is that for ε12 = 1 the
system is still slowly approaching equilibrium, even though this fact
would have no serious impact on the considerations presented below.
Figure 4
Equimolar
HSTY–HS mixture for T = 0.25.
Potential energy per particle vs MC cycles for different ε12, in the legend; results for the pure HSTY fluid are also
shown, for comparison. Inset: asymptotic values (symbols) vs ε12 are fitted by two different straight lines.
Figure 5
Equimolar HSTY–HS mixture for T = 0.25
and ε12 = 0.75. (A) Big-cluster initial configuration,
containing 2048 randomly dispersed HSTY and HS spheres. (B) After
2.5 × 107 MC moves, the initial cluster is reduced
in fragments, now resembling the cluster fluid obtained from a fully
homogeneous initial configuration; see Figure B below. After equilibration, the potential
energy fluctuates around a fixed value, which is roughly independent
of the initial configuration (C). Interestingly enough, the initial
energy of the system in the big cluster is lower than in the final
cluster-fluid configuration; hence, it is the relevant entropy gain
achieved by forming many smaller clusters that ensures that the cluster
fluid is more stable than the big cluster. Also the final structure
factors are similar in the two runs (D), but for a small mismatch
in the position and height of the low-k peak.
Equimolar
HSTY–HS mixture for T = 0.25.
Potential energy per particle vs MC cycles for different ε12, in the legend; results for the pure HSTY fluid are also
shown, for comparison. Inset: asymptotic values (symbols) vs ε12 are fitted by two different straight lines.Equimolar HSTY–HS mixture for T = 0.25
and ε12 = 0.75. (A) Big-cluster initial configuration,
containing 2048 randomly dispersed HSTY and HS spheres. (B) After
2.5 × 107 MC moves, the initial cluster is reduced
in fragments, now resembling the cluster fluid obtained from a fully
homogeneous initial configuration; see Figure B below. After equilibration, the potential
energy fluctuates around a fixed value, which is roughly independent
of the initial configuration (C). Interestingly enough, the initial
energy of the system in the big cluster is lower than in the final
cluster-fluid configuration; hence, it is the relevant entropy gain
achieved by forming many smaller clusters that ensures that the cluster
fluid is more stable than the big cluster. Also the final structure
factors are similar in the two runs (D), but for a small mismatch
in the position and height of the low-k peak.
Figure 9
Microscopic
configurations for the equimolar mixture at T = 0.25
(HSTY, green; HS, orange). (A) ε12 = 0.5; (B) ε12 = 0.75; (C) ε12 = 1; (D) CSD for the same
values of ε12.
Turning back to the behavior of the potential energy
per particle
in Figure , it appears
that for ε12 ≤ 0.50 the mixture behaves similarly
to the HSTY fluid of same T; i.e., the system quickly
attains equilibrium and the final energy is between −0.05 and
−0.25. However, when ε12 is increased from
0.50 to 0.75, the scenario changes drastically, with the energy now
exhibiting a sharp drop until reaching a final value of ≈−2
after about 107 MC steps. Upon further increasing the attraction
strength to ε12 = 1, the energy approaches ≈−3
after about 5 × 107 MC steps. In particular, we see
that the rate of (absolute) energy increase grows abruptly as ε12 overcomes 0.50. This can be appreciated in the inset of Figure , where the asymptotic
energies are reported as a function of ε12: the energy
values can be grouped in two sets (i.e., up to ε12 = 0.50 and from ε12 = 0.75 onward) which are fitted
by different straight lines, in this way corroborating the idea that
the crossover between the two regimes follows a threshold-like behavior.The evolution of potential energy with ε12 suggests
that the system exhibits some form of aggregation for ε12 > 0.50, even though we cannot yet say whether it is liquid–vapor
separation or clusterization that occurs. To clarify this point, we
analyze in Figure A the partial structure factor S11(k) of HSTY particles: we see that, upon increasing ε12, the k → 0 limit of S11(k) does not change significantly;
on the other hand, for ε12 > 0.50, S11(k0) jumps over 10, indicating
that clusterization, rather than liquid–vapor separation, takes
place in the system for sufficiently strong cross attraction. Correlations
involving species 2 are shown in panels B and C of Figure , but they hardly add anything
new to what we have already learned from S11(k), since S12(k) and S22(k) also show a remarkable increase of the low-k peak
for ε12 > 0.50. Global variables, expressed according
to eqs –6, are reported in panels D–F for the same
values of ε12: the total structure factor SNN(k) (D) is similar to S11(k), both in shape and height
of the peaks, confirming that the indications provided by the structure
factor of the HSTY species alone hold for the mixture too. A similar
trend is also observed in S (E), whereas S (F), behaves differently: in this case, besides the development
of the low-k peak, we observe an increasing structuring
with ε12, as indicated by the multiple peaks found
for ε12 > 0.50. Therefore, significant concentration
fluctuations are found over a wide range of k values,
as can be expected in a cluster-forming system, due to the spatial
rearrangement of particles inside the aggregates.
Figure 6
Equimolar HSTY–HS
mixture for T = 0.25.
(A) S11(k); (B) S12(k); (C) S22(k); (D) SNN(k); (E) SNc(k); (F) Scc(k). Values of ε12 are shown in panel A, with the
same colors applying for all panels. The pure HSTY case is also reported
in panels A and D for comparison. Note the semilogarithmic scales
in panels A, C, D, and E.
Equimolar HSTY–HS
mixture for T = 0.25.
(A) S11(k); (B) S12(k); (C) S22(k); (D) SNN(k); (E) SNc(k); (F) Scc(k). Values of ε12 are shown in panel A, with the
same colors applying for all panels. The pure HSTY case is also reported
in panels A and D for comparison. Note the semilogarithmic scales
in panels A, C, D, and E.To complete our thermodynamic/structural survey, we mentioned in
the Introduction that a maximum in the specific heat at constant volume, cV, provides another reasonable indication of
the onset of clustering.[43] In particular,
the specific heat is related to energy fluctuations according to the
expression[37](where H is the Hamiltonian
of the system) and indeed such fluctuations become large when clusters
form and disrupt with similar probability. In Figure , cV is reported
as a function of ε12 at constant T = 0.25. It clearly emerges that the observed behavior corroborates
our previous finding: cV shows a maximum
for ε12 = 0.75, where, according to internal energy
(see Figure ) and
structure factors (see Figure ), clusters show up for the first time. For ε12 = 1 clusters are already formed and quite stable, therefore energy
fluctuations are less marked and in turn cV attains smaller values.
Figure 7
Equimolar HSTY–HS mixture for T = 0.25. cV/k vs ε12. The error
bars represent maximum dispersions
from the mean as computed from 10 independent runs.
Equimolar HSTY–HS mixture for T = 0.25. cV/k vs ε12. The error
bars represent maximum dispersions
from the mean as computed from 10 independent runs.Once having ascertained that a second species is able to
promote
the cluster formation under proper conditions, we have computed a
number of properties to characterize the structure of aggregates,
see Figure A: the
number of isolated particles monotonically decreases with increasing
ε12 (left), signaling that aggregates encompass more
and more particles; concurrently, the largest cluster size increases
(middle) and the total number of clusters decreases (right), indicating
that aggregates appear and grow in size with increasing ε12. This picture is reflected in the probability distribution
of the number of bonds, plotted in Figure B. Here the particles are classified according
to the number of bonded “neighbors”: the monotonic decay
for ε12 = 0.5 is replaced by a trimodal distribution
for ε12 = 0.75, with peaks at Nb = 0, 6, and 12, respectively associated with isolated particles,
outer cluster particles, and inner cluster particles. In particular,
the peak at Nb = 12 (more enhanced for
ε12 = 1) strongly points to a liquid-like (if not
even fcc-like) ordering inside clusters. The comparatively higher
number of bonds formed for larger values of ε12 can
be better appreciated in the inset of Figure B: here the probability to form more than
two bonds is remarkably low for ε12 = 0.5, whereas
the trend is reversed for ε12 = 0.75 and, even more
so, for ε12 = 1, where 8 and 10 bonds per particle
occur with a rather high frequency.
Figure 8
Equimolar mixture for T = 0.25. (A) Number of
isolated spheres (left), largest cluster size (middle), and total
number of clusters (right) for various ε12 values.
Standard deviations are also shown. (B) Probability distribution of
the number of bonds for a number of ε12 values, in
the legend. In the inset, the same data are plotted vs ε12 for various Nb, in the legend.
Equimolar mixture for T = 0.25. (A) Number of
isolated spheres (left), largest cluster size (middle), and total
number of clusters (right) for various ε12 values.
Standard deviations are also shown. (B) Probability distribution of
the number of bonds for a number of ε12 values, in
the legend. In the inset, the same data are plotted vs ε12 for various Nb, in the legend.The above picture is completed by the microscopic
configurations
reported in Figure : as ε12 grows from 0.50 (A) to 0.75 (B),
up to 1 (C), clusters become progressively more structured. In analogy
with the behavior of the pure HSTY fluid upon cooling (Figure ), for ε12 = 0.75 and 1, the shape of the clusters is approximately spherical,
although in the latter case nonspherical aggregates also exist. Under
these conditions, very few isolated particles appear in the box, due
to a strong HSTY–HS interaction. A closer look at Figure C shows that cluster
particles are instead tightly packed for ε12 = 1,
similar to what occurs in the solid-like nuclei developing in a supercooled
vapor or liquid which is about to crystallize.[59] Indeed, a high degree of order in the arrangement of particles
within a cluster is implied by the behavior of g11(r) (not shown here), which displays multiple
solid-like peaks akin to those observed in the inset of Figure for T ≤
0.22. More refined investigations of the liquid–solid transition
inside clusters, like those described in ref (60), are deferred to future
studies. The cluster-size statistics (computed by making no difference
between the species) is reported in Figure D: for ε12 = 0.50 the CSD
is a monotonically decreasing function of the cluster size s, a profile compatible with a dispersed fluid. On the contrary,
for ε12 = 0.75 the CSD has a well-definite maximum
around s = 60, indicating this preferred cluster
size. In addition, we observe a non-negligible fraction of larger
clusters comprising up to 100 particles. For ε12 =
1, we see multiple peaks in the CSD, suggesting the existence of as
many preferential cluster sizes, although the distribution is centered
around the same size as for ε12 = 0.75. In addition,
we see no sign of a percolated structure, in spite of the existence
of large aggregates with up to 200 particles. Overall, the distributions
reported in Figure closely resemble those in Figure , suggesting that the strength of cross attraction
plays a role similar to inverse temperature in a HSTY fluid.Microscopic
configurations for the equimolar mixture at T = 0.25
(HSTY, green; HS, orange). (A) ε12 = 0.5; (B) ε12 = 0.75; (C) ε12 = 1; (D) CSD for the same
values of ε12.Summing up, a sufficiently large ε12 can sustain
clusters in an equimolar HSTY–HS system, notwithstanding their
absence in the pure HSTY fluid of same density and temperature. The
same conclusion was already drawn in ref (54) but using mutually attractive spheres as foreign
species. Our results demonstrate that even particles that do not attract
each other are able to provide the extra attraction needed by HSTY
particles to undergo clusterization.To rationalize our evidence,
we turn to the interpretation of clustering
given in refs (18 and 19). Therein
it is argued that the clustering threshold in HSTY systems falls upon
(roughly) the same thermodynamic conditions for which a modified HSTY
fluid with the long-range repulsion switched off would phase-separate
into liquid and vapor. We hereafter refer to this modified HSTY fluid
[i.e., with u11(r) truncated
at r0] as the “reference attractive”
HSTY fluid. In other words, adding an appropriate long-range repulsion
on top of a purely attractive tail breaks the liquid–vapor
mixture into separate, noninteracting fragments (the clusters). A
similar scenario has been described in regard to spinodal decomposition
in ref (23), where
the behavior of a fluid interacting via a generalized Lennard-Jones
plus a repulsive-Yukawa tail was investigated in the regime where
arrested states hold the stage. If the same argument applies for the
present mixture, then for T = 0.25, χ = 0.5,
and ε12 = 0.75 the liquid–vapor binodal line
of the reference attractive HSTY–HS mixture will lie above
that of the reference attractive HSTY fluid. Accordingly, a measure
of the overall amount of attraction (i.e., the “glue”
keeping particles together) will be larger for the mixture than for
the pure HSTY fluid alone.To check this conjecture, we have
employed the second virial coefficient B2, which provides an integrated measure of the
strength of interactions in the system. The virial coefficient of
the reference attractive mixture is[61]withfor ij = 11 or 12, and B222 = 2πσ3/3. Only the first
term on the r.h.s. of eq (with χ = 1) needs to be considered for the reference attractive
HSTY fluid. In Figure we plot B2 and B211, for χ
= 0.5 and different temperatures, as a function of ε12: for a given T, the intersection between B2 and B211 falls atwithand
Figure 10
Second virial coefficient
of the reference attractive fluids for
the equimolar mixture (full lines) and the pure HSTY (dashed lines)
vs ε12 for various temperatures, in the legend. Intersections
are marked by crosses.
Second virial coefficient
of the reference attractive fluids for
the equimolar mixture (full lines) and the pure HSTY (dashed lines)
vs ε12 for various temperatures, in the legend. Intersections
are marked by crosses.For the temperatures
in Figure , we have
the pairs [T, ε12*] = [0.20, 0.5621],
[0.22, 0.5465], [0.25, 0.5272], and [0.30, 0.5032], each marked by
a cross in the figure. In particular, for T = 0.25,
the reference attractive mixture will be more attractive than the
reference attractive HSTY fluid for ε12 > ε12* = 0.5272 (see
red lines and cross). Accordingly, the liquid–vapor binodal
of the former falls above the binodal line of the latter for ε12 > ε12*, while lying below otherwise. This prediction is in gratifying
agreement with results shown in Figures –9, confirming
the validity of our approach: for T = 0.25 the equimolar
mixture with ε12 = 0.50 is unable to sustain cluster
formation, similar to the HSTY fluid; conversely, for ε12 = 0.75, the clustering tendency of the mixture will be enhanced
with respect to the HSTY fluid.We may wonder whether the same
comparison also applies in reverse,
so that clusterization is preempted in the mixture for the same density
and temperature where clusters occur in the pure HSTY fluid. To verify
this hypothesis, we take T = 0.22, where clusters
are present in the pure HSTY fluid (see Figure ). At this temperature, the crossing of B2 lines occurs for ε12* = 0.5465 (see Figure , blue lines and cross). Structural
data are presented in Figure for ε12 = 0.30 and 0.75, i.e., two values
on opposite sides of 0.5465. While the height of the low-k peak is ≈4 in the pure HSTY fluid, the same peak falls below
2 in the mixture with ε12 = 0.30, meaning that with
a proper choice of ε12 (to be discriminated on the
basis of the B2 criterion) clustering
can be suppressed. On the other side of the threshold, i.e., for ε12 = 0.75, the attraction is so intense that clusterization
is strongly enhanced [S(k0) ≈ 30].
Figure 11
Equimolar mixture for T = 0.22. S11(k) for ε12 = 0.30
and 0.75. Results for the pure HSTY fluid of the same density and
temperature are also reported for comparison.
Equimolar mixture for T = 0.22. S11(k) for ε12 = 0.30
and 0.75. Results for the pure HSTY fluid of the same density and
temperature are also reported for comparison.To sum up, the crossing of the B2 vs
ε12 lines falls in the narrow interval ε12 ≈ 0.50–0.56 in the T range
0.20–0.30, where the pure HSTY fluid experiences the crossover
from a rather homogeneous fluid to a strongly structured cluster fluid.
Our method provides a viable means to tune the onset of clustering
in the equimolar HSTY–HS mixture; this tuning acts in both
directions, namely enhancing or depressing the tendency to clusterization
by just increasing or decreasing the strength of cross attraction
at a given temperature. We have thus provided another assessment of
the clustering picture proposed in refs (18, 19, and 23), according
to which clusters develop for the same thermodynamic conditions where
the reference attractive fluid undergoes liquid–vapor separation.Our analysis also confirms that S(k0) ≈ 3 is a sensitive indicator of the onset of
clustering. As we move around this value (in the present case, in
the temperature range 0.22–0.25, see Figure ), clusters can be reversibly created or
destroyed by adjusting ε12 on the basis of the relative
balance in B2 between the (attractive)
mixture and HSTY fluid. However, this tuning no longer works when
we penetrate too much in the clustering region. Indeed, for T = 0.20 [where S(k0) ≈ 10 in the pure HSTY fluid, see Figure ] we find S(k0) ≳ 12 for ε12 = 0.75 and S(k0) ≳
6 for ε12 = 0.30. Therefore, a change in ε12 will certainly affect the quality of the clustered state,
but with no possibility to recover homogeneity.
Changing
the Relative Concentration
Finally, we elucidate the effect
of varying the relative concentration
of the species on the formation of clusters. We set T = 0.25 and ε12 = 0.75 (allowing for the presence
of clusters in the equimolar mixture, as shown in the previous section)
and span the whole range of HSTY concentrations. The behavior of S11(k) is shown in Figure A, where, for the
sake of comparison, we have also included S(k) of the pure HSTY fluid. We see that S11(k0) > 3 in almost all
cases;
in particular, S11(k0) falls between 4 and 5 for both χ = 0.05 and χ
= 0.9, while rising above 10 between these extremes. As a result,
at the given conditions of temperature and density, changing the concentration
will only moderately affect the clustered nature of the mixture, with
the only exception being χ = 0.01, where clusters are apparently
absent. In particular, we can induce clustering in a fluid of hard
spheres by replacing a fraction as low as 5% of HS particles with
HSTY particles. Moreover, compared to the pure fluid, the main peak
of S11(k) is more pronounced
and better resolved; at the same time, k0 moves closer and closer to zero as hard spheres become progressively
dominant in the mixture, pointing to the presence of increasingly
large clusters. Therefore, the inclusion of HS particles invariably
gives rise to stabilization of the clustered state, with the strongest
effect near equimolarity, as demonstrated by the largest value of S(k0) attained for χ =
0.3 and 0.5. The tendency of HSTY particles to form clusters acts
as a dragging mechanism for the structural properties of the whole
mixture, as can be appreciated from the similarity between S11(k) and the total structure
factor SNN(k) in Figure B. Some discrepancy
only emerges for low χ, where indeed a large number of HS particles
stay isolated, giving rise to a homogeneous background for clusters.
Figure 12
Mixture
for T = 0.25 and ε12 =
0.75. (A) S11(k); (B) SNN(k). The whole range of HSTY
concentrations is shown; see the legend.
Mixture
for T = 0.25 and ε12 =
0.75. (A) S11(k); (B) SNN(k). The whole range of HSTY
concentrations is shown; see the legend.Our conclusions, based so far on the sole structural evidence,
are confirmed by the microscopic analysis of MC configurations. In Figure we show the CSD
for various concentrations: for all concentrations examined, the CSD
shows the typical features of a clustered state—specifically,
a nonmonotonic decay accompanied by a well-definite local peak at
the most probable size. All distributions vanish beyond s ≈ 100–200, therefore suggesting the absence of any
tendency to percolation. Moreover, we see that comparatively larger
clusters are stabilized in the range χ = 0.1–0.5, a feature
already noted when analyzing structural correlations. Under the same
conditions, the fraction of isolated (mainly HS) particles keeps relatively
high, as shown in the inset.
Figure 13
CSD for T = 0.25, ε12 = 0.75,
and a few selected values of χ (in the legend). Inset: fraction
of isolated particles vs χ.
CSD for T = 0.25, ε12 = 0.75,
and a few selected values of χ (in the legend). Inset: fraction
of isolated particles vs χ.The simultaneous occurrence of large clusters and a high number
of isolated HS for χ = 0.1 and 0.3 can be better appreciated
in the snapshots reported in Figure ; in particular, a glance at panels A and B—where
the same χ = 0.1 configuration is shown with and without isolated
particles—indicates that HS (in orange) are homogeneously distributed
across the sample. A few large clusters (formed by particles of both
species in equal proportions) are immersed in the bath of isolated
HS, thus corroborating the picture emerging from the structure. As
the HSTY concentration increases (χ = 0.3, panel C) the coupling
between HSTY and HS becomes more effective, with an ensuing smaller
number of isolated HS. As said before, the optimal condition for mutual
aggregation is at equimolarity where practically all HS particles
are involved in the formation of aggregates (see Figure B and Figure , inset). Starting from χ = 0.7 onward
(panels D and E), the opposite trend sets in, with a progressively
higher number of isolated HSTY particles and the presence of many
smaller clusters. The ultimate fate of this process is already known
(see Figure A): as
the HS are completely removed, clusters break apart, and the now pure
HSTY fluid is nearly homogeneous.
Figure 14
Microscopic configurations for T = 0.25 and ε12 = 0.75. (A and B) χ
= 0.1, with and without isolated
particles; (C) χ = 0.3; (D) χ = 0.7; (E) χ = 0.9;
(F) average eccentricity with standard deviation of the largest cluster
as a function of χ.
Microscopic configurations for T = 0.25 and ε12 = 0.75. (A and B) χ
= 0.1, with and without isolated
particles; (C) χ = 0.3; (D) χ = 0.7; (E) χ = 0.9;
(F) average eccentricity with standard deviation of the largest cluster
as a function of χ.To gain more information on the cluster structure, we have determined
the shape distribution of the largest cluster across configurations,
as a function of χ. To this aim, we have followed the method
devised in ref (62), in which the cluster eccentricity ec is defined aswhere R and R are, respectively, the minimum and maximum values
of the gyration radius Rg of the largest
cluster and the average is taken over sufficiently many configurations.
By definition, the value of ec ranges
from 0 (perfect sphere) to 1 (ellipsoid). The method slightly differs
from a similar protocol proposed in ref (63). The behavior of ec as a function of χ is reported in Figure F, along with standard deviations: clearly,
no sensible dependence of ec on χ
is found, with all values of eccentricity ranging between 0.23 and
0.32. This suggests that the largest clusters have a nearly spherical
shape regardless of the relative concentration of the species.One further remark is worth making in this context. We see in Figure D, corresponding
to χ = 0.7, that HS are gathered in droplets essentially held
together by an outer shell of SALR particles. This surprising outcome
indicates the possibility of encapsulating inert particles by a second
species with affinity to them, such that they are held apart from
the solvent (here only implicitly defined).We end this section
by an analysis of B2 along the same lines
followed before, now in terms of HSTY concentration
for ε12 = 0.75 and fixed temperature. Results are
shown in Figure : as seen, the two B2 lines cross for
χ = 1 (which is trivial) and forFor
the temperatures considered in the figure,
we have the pairs [T, χ*] = [0.20, 0.1434],
[0.22, 0.1432], [0.25, 0.1447], and [0.30, 0.1490], each marked by
a cross. Hence, over the rather extended concentration range χ
≈ 0.14–1, the reference attractive mixture is more attractive
than the reference attractive HSTY fluid. Accordingly, clusters would
appear more structured in the mixture than in the HSTY fluid. At the
same time, we must note a discrepancy between the B2 threshold (χ = 0.14) and the simulation threshold
(χ ≈ 0.05). Despite this mismatch, our expectation that
clusters are strengthened by replacing even a large fraction of SALR
particles with HS is in accordance with the simulation.
Figure 15
Second virial
coefficient of the reference attractive fluids for
the mixture with ε12 = 0.75 (full lines) and the
pure HSTY (dashed lines) vs χ for different temperatures, in
the legends. Intersections are marked by crosses.
Second virial
coefficient of the reference attractive fluids for
the mixture with ε12 = 0.75 (full lines) and the
pure HSTY (dashed lines) vs χ for different temperatures, in
the legends. Intersections are marked by crosses.Compared to the ε12* dependence on T, now a weaker
dependence of χ* on T is found. This is due
to a minimum attained by χ* for T = 0.22; as
a result, χ* slowly changes in the range from T = 0.20 to T = 0.30, which is a close neighborhood
of the minimum. We finally observe that B2 of the reference attractive mixture reaches a minimum at χ
≈ 0.57. Coherently with our previous conclusion, the optimal
conditions for maximizing the number of bonds (hence, for minimizing
the energy) are met near equimolarity.
Conclusions
We have carried out Monte Carlo simulations of a model mixture
of hard-sphere two-Yukawa particles and hard spheres, being coupled
through an attractive square-well potential.We have ascertained
that the inclusion of HS particles can induce
the formation of clusters under conditions for which the pure HSTY
fluid would not allow for their appearance. As already recognized
in ref (54), the tendency
of HSTY particles to form clusters can indeed be enhanced by a second
species having sufficient affinity to them. We have also verified
that the same mechanism can be employed the other way around, so that
clustering is hampered in the mixture for the same temperatures where
they are present in the pure HSTY fluid.By simulating the equimolar
HSTY–HS mixture at sufficiently
low temperatures, it emerges that clusters contain HSTY and HS particles
mixed together in equal proportions. Upon moving away from equimolarity,
we observe a net preference of the majority species at the cluster
surface. In particular, hard spheres can be loosely encapsulated by
HSTY particles and, in this way, separated from the (implicit) solvent.For fixed strength of cross interaction, clustering turns out to
be only weakly dependent on the HSTY concentration. In this regard,
one of the most interesting results is that clusters can even be induced
in a HS fluid by replacing a small fraction of spheres (as low as
5%) with HSTY particles, provided that a sufficiently large attraction
(ε12 ≥ 0.75) exists between the species. Hence,
given a sample composed by inert colloidal particles, clustering can
be induced by even marginal chemical substitution with a species with
competing interactions and a suitable degree of affinity to the host
particles. The optimal condition for aggregation is realized near
50% concentration, where almost all particles participate in the formation
of aggregates.We have placed our results in the more general
framework provided
in refs (18 and 19), according to which
cluster formation takes place under the same conditions where the
reference system (without long-range repulsion) would give rise to
liquid–vapor phase separation. To substantiate this idea, we
have computed the second virial coefficient B2 of the reference attractive mixture and compared it with
the B2 of the similarly modified HSTY
fluid. It emerges that clustering in the mixture—for fixed
temperature and density—is invariably obtained as it becomes
more attractive than the pure HSTY fluid. Conversely, when the B2 of the reference attractive mixture falls
below that of the pure fluid, clustering is undermined in the HSTY–HS
mixture. This indication is in perfect agreement with the evidence
got from the structural and the microscopic analysis.In the
near future, we plan to explore the space of model parameters
further, in particular by considering other values of the square-well
width and also varying the relative size of the two species. To this
aim, aside from simulations, we plan to resort on refined, thermodynamically
self-consistent integral equation theories of the fluid phase.
Authors: Anna Stradner; Helen Sedgwick; Frédéric Cardinaux; Wilson C K Poon; Stefan U Egelhaaf; Peter Schurtenberger Journal: Nature Date: 2004-11-25 Impact factor: 49.962
Authors: Yufeng Wang; Yu Wang; Dana R Breed; Vinothan N Manoharan; Lang Feng; Andrew D Hollingsworth; Marcus Weck; David J Pine Journal: Nature Date: 2012-11-01 Impact factor: 49.962