1. Introduction
Granular suspensions comprising sufficiently large particles with diameters ranging between
$O(10)$
${\unicode{x03BC}}$
m and
$O(1)$
mm in a liquid are ubiquitous in industrial applications and daily life, such as in the synthesis of composite materials (Rueda et al. Reference Prasad, Santangelo and Grason2017; Zarei & Aalaie Reference Zarei and Aalaie2020), pipeline transportation (Fazli et al. Reference Fazli, Rudman, Kuang and Chryss2024), and several types of liquid food. For dense granular suspensions at solid volume fraction
$\phi \geq 0.5$
, the flows often exhibit pronounced continuous shear thickening (CST) (Fall et al. Reference Fall, Lemaître, Bertrand, Bonn and Ovarlez2010; Boyer, Guazzelli & Pouliquen Reference Boyer, Guazzelli and Pouliquen2011; Sakaï et al. Reference Rueda, Auscher, Fulchiron, Périé, Martin, Sonntag and Cassagnau2019; Xu, Singh & Jaeger Reference Xu, Singh and Jaeger2020; Tapia et al. Reference Sun and Sundaresan2022). The viscosity
$\eta$
increases continuously with an increasing shear rate
$\dot {\gamma }$
or stress
$\sigma$
via direct particle-to-particle contact and frictional interactions. Industrial suspensions typically contain multimodal particles with varied sizes and relative contents of each size class. Adopting a suitable particle size distribution (PSD) can distinctly reduce the friction between particles as well as the viscosity at a fixed
$\phi$
(Rueda et al. Reference Prasad, Santangelo and Grason2017; Chen et al. Reference Chen, Xue, Li, Wen, Liu, Xue, Shi, Zhou, Xie and Mai2019). However, polydisperse particles inevitably increase the complexity of the microstructure, such as shear-induced layering (Malbranche, Chakraborty & Morris Reference Luan2023) and size segregation (Fan & Hill Reference Fan and Hill2011) that appear only under certain PSDs. Relevant microstructural transformations may cause abrupt changes in the properties of shear thickening, especially at
$\phi$
close to the jamming limit
$\phi _J$
. The extent of the analogy between discontinuous shear thickening (DST) transition and phase transition remains an open question (Morris Reference More and Ardekani2025).
Particle size polydispersity design, or the optimisation of the PSD, has been widely adopted as an economically effective method for improving the flowability of dense suspensions (Metzner Reference Mari, Seto, Morris and Denn1985; Kaully, Siegmann & Shacham Reference Huang, Ovarlez, Bertrand, Rodts, Coussot and Bonn2007; Rueda et al. Reference Prasad, Santangelo and Grason2017; Chen et al. Reference Chen, Xue, Li, Wen, Liu, Xue, Shi, Zhou, Xie and Mai2019). Particles can achieve the highest random close packing fraction
$\phi _{rcp}$
through efficient hierarchical packing at the theoretical optimal PSD. For bidisperse systems, the relative volume fraction of small particles
$\zeta _1$
(defined as
$\zeta _1=V_1/(V_1+V_2)$
, where
$V_i=(\pi /6)N_id_i^3$
denotes the total volume occupied by
$N_i$
spheres of type
$i=1$
or
$2$
) at this optimal PSD lies within the range
$0.25\leq \zeta _1\leq 0.35$
, and is strongly dependent on the packing details, such as the particle shape, size ratio and surface roughness (Shapiro & Probstein Reference Seto, Singh, Chakraborty, Denn and Morris1992; Kwan, Wong & Fung Reference Kumar, Singh, Giri and Mishra2015; Pednekar, Chun & Morris Reference O’Hern, Silbert, Liu and Nagel2018; Fu et al. Reference Fu, Liu, Lu and Sun2024). In general, the
$\phi _{rcp}$
values of dry spheres are higher than the fluidity limit, or jamming volume fraction
$\phi _J$
, of suspensions filled with frictional particles, and they are correlated by a constant of proportionality (Shapiro & Probstein Reference Seto, Singh, Chakraborty, Denn and Morris1992). Suspensions that adopt the optimal PSD are expected to have the lowest rate-independent viscosity via the well-known relation
$\eta \propto (1-\phi /\phi _J)^{-\alpha }$
with
$\alpha \approx 2$
(Lerner, Düring & Wyart Reference Lee, Jiang, Wang, Sandy, Narayanan and Lin2012; Wyart & Cates Reference Wyart and Cates2014; Malbranche et al. Reference Luan2023). However, this scenario may not be applicable to the rate-dependent suspension rheology in which direct contact between particles is crucial. For instance, in steady-state shear experiments, the bidisperse suspension with
$\zeta _1=0.20$
exhibited even higher viscosity in the thickening regime, although this PSD corresponded to a relatively high
$\phi _J$
compared with the other PSDs studied (Guy et al. Reference Guy, Ness, Hermes, Sawiak, Sun and Poon2020). Microscopically, the reduced viscosity around the optimal PSD is closely related to the shear-induced large-particle layering (Malbranche et al. Reference Luan2023). The discrepancy in viscosity changes related to the PSD in different flow regimes suggests novel microstructural features during shear thickening.
Shear-induced ordering has been reported extensively in dry granular materials (Tsai, Voth & Gollub Reference Trulsson, DeGiuli and Wyart2003; López-González et al. Reference López-González, Pacheco-Vázquez and Donado2023), colloidal systems (Malkin Reference Malbranche, Chakraborty and Morris2021) and dense suspensions (Malbranche et al. Reference Luan2023). The depletion effect, which is rooted in the entropy-driven phase transition theory (Stavans Reference Singh, Ness, Sharma, de Pablo and Jaeger2000; Shinbrot & Muzzio Reference Shäfer, Dippel and Wolf2001), explains this self-organisation phenomenon of micron-sized particles (Wang & Hong Reference Wang and Hong2008). The region around large particles that is inaccessible to the centres of small particles is known as the depletion zone. When two large particles approach one another, their depletion zones overlap, releasing part of the movement space for small particles. Large particles tend to align in layers when subjected to steady or oscillatory shear; the decrease in the configurational entropy of large particles is well compensated for by the increase in the translational entropy of small particles. Ultimately, the entropy of the entire system increases through the formation of layered large particles. This layered structure corresponds to the optimal configuration of bidisperse dense suspensions with
$\zeta _1$
near the optimal PSD. For jammed suspensions of soft particles, the optimal configuration can be amorphous, layered or crystals, depending on the size ratio, PSD, volume fraction and shear rate (Alrashdan et al. Reference Alrashdan, Yankah, Cloître and Khabaz2024). To enhance the depletion effect, a large number of large particles is needed to increase the overlapping depletion zones; at the same time, a sufficient number of small particles is also needed to occupy the interstices between the large particles to increase the system entropy. Therefore, through an appropriate combination of the size and number of different particle size classes, the entropic force forming shear-induced ordered structures may reach its maximum, i.e. the degree of ordering is sufficiently high to form complete layers.
In contrast, the locally or globally ordered structures that are formed through self-organisation in granular suspensions, which are practically always out of equilibrium (Ness, Seto & Mari Reference Ness, Mari and Cates2022), are metastable. As
$\phi$
approaches
$\phi _J$
, particles do not have sufficient space to explore the optimal layered configuration, and the suspensions tend to jam at infinitesimal shear rate, exhibiting rigidity due to a more interconnected particle contact network. This jamming effect, which is also known as the fluid-to-solid phase transition, is often accompanied by a drastic viscosity jump (Trappe et al. Reference Tapia, Ichihara, Pouliquen and Guazzelli2001; Das, Vinutha & Sastry Reference Das, Vinutha and Sastry2020). The shear jamming, which corresponds to the lower bound of jamming volume fraction, occurs at a random configuration (Shapiro & Probstein Reference Seto, Singh, Chakraborty, Denn and Morris1992). In the 1970s, Hoffman (Reference van Hecke1972, Reference Hoffman1974) postulated an order-to-disorder (OD) transition mechanism to explain the phenomenon of strong thickening and DST in concentrated colloidal suspensions. In near-monodisperse systems, the formation of ordered structures is highly sensitive to the particle size, monodispersity and measurement conditions (Lee et al. Reference Kwan, Wong and Fung2018). The OD mechanism remains controversial; experiments on Brownian or colloidal suspensions (with typical particle diameter
$d \lesssim \textit {O}(1)$
${\unicode{x03BC}}$
m) showed no significant correlation between DST and phase transition (Sierou & Brady Reference Shire, O’Sullivan and Hanley2002; Kulkarni & Morris Reference Krishnan and Leighton2009). In granular suspensions, inertia at the particle scale prevails, which largely alleviates the thermally stochastic motion of particles that could hinder long-range ordering. In addition, the depletion effect of large particles makes it easier for bidisperse suspensions to form ordered structures. Despite the extensive research, the role of phase transition in the thickening of bidisperse systems remains unclear owing to (i) limited experimental insights into the dynamics of the internal microstructural evolution, and (ii) the inherent ‘fragility’ of shear-induced layered structures under varying flow conditions.
In this study, we directly addressed these issues through three-dimensional particle-based simulations that integrated hydrodynamic lubrication with an appropriate particle contact model. We demonstrated the OD transition in bidisperse suspensions with a theoretically optimal PSD, which leads to DST in inertial flows. This finding provides a promising perspective for understanding the high viscosity under certain PSDs that cannot be described by the classical mean field approach (Wyart & Cates Reference Wyart and Cates2014; Guy et al. Reference Guy, Ness, Hermes, Sawiak, Sun and Poon2020). The rearrangement of particles diminishes the anisotropy of the contact network. In addition, we investigated the effect of phase transition on the friction coefficient of the system; this knowledge is fundamental to the development of a universal rheological theory for polydisperse suspensions.
2. Methodology
We consider granular suspension models with non-Brownian particles that are dispersed in a Newtonian liquid at a solid volume fraction
$\phi$
(
$\phi =(V_1+V_2)/V$
, where
$V$
is the total volume of the simulation box). The solid and fluid phases are density matched to eliminate buoyancy-driven convections. For most of the models reported in the results section, the large-to-small particle diameter ratio is
$\lambda =5$
. This
$\lambda$
exceeds the percolation threshold
$\lambda \approx 4.44$
(Guy et al. Reference Guy, Ness, Hermes, Sawiak, Sun and Poon2020) – a critical ratio above which small spheres can fit within the interstices of four touching large spheres. We also conducted simulations on models with a broader size range at
$\lambda =7$
and
$\lambda =9$
to investigate the parameter range in which the OD transition occurs; see supplementary material § 3 are available at http://doi.org/10.1017/jfm.2026.11717. The fraction of small particles (
$\zeta _1$
) in real-life bidisperse suspensions is usually designed not to exceed that of large particles (
$\zeta _2$
) to achieve good fluidity (Dangtungee & Supaphol Reference Dangtungee and Supaphol2010; Rueda et al. Reference Prasad, Santangelo and Grason2017; Chen et al. Reference Chen, Xue, Li, Wen, Liu, Xue, Shi, Zhou, Xie and Mai2019). Accordingly, we study the cases of PSDs at
$\zeta _1=0.10, 0.26, 0.50$
. The corresponding models at
$\phi =0.55$
are shown in figure 1. Among these three PSDs,
$\zeta _1=0.26$
corresponds to the theoretical optimal PSD that can achieve the highest frictionless, random close-packing density (Prasad, Santangelo & Grason Reference Plimpton2017; Fu et al. Reference Fu, Mao, Wang, Li, Sun and Lu2023). We varied the volume fraction from
$\phi =0.55$
to above the jamming limit
$\phi _J$
for most suspensions to explore the
$\phi$
-dependent properties. The jamming volume fractions
$\phi _J$
were determined by fitting the Krieger–Dougherty equation
$\eta _r=(1-\phi /\phi _J)^{-[\eta ]\phi _J}$
(Krieger & Dougherty Reference Kim and Karrila1959) (where
$[\eta ]$
is the intrinsic viscosity, and
$[\eta ]=2.5$
for spheres) to the simulated data of rate-independent viscosity
$\eta _r$
at different
$\phi$
; see supplementary material § 5. Values of
$\phi _J$
for the three cases of PSDs shown in figure 2 were determined as 0.648 (
$\zeta _1=0.10$
), 0.731 (
$\zeta _1=0.26$
) and 0.690 (
$\zeta _1=0.50$
). For the models with
$\lambda =5$
, our simulations employed assemblies comprising
$\sim 10\,000$
particles, which is a sufficiently large scale to ensure that the bulk rheology is independent of both the domain size and PSD (Fu et al. Reference Fu, Liu, Lu and Sun2024). For the models with
$\lambda =7$
and
$\lambda =9$
, we set the minimum number of large particles
$N_2^{min}=80$
and the minimum total volume of small particles
$V_1^{min}=({4}/{3})\pi (d_2/2)^3N_2^{min}$
to ensure statistical representativeness in each PSD case. The total number of particles in the
$\zeta _1=0.26$
suspensions with
$\lambda =7$
and
$\lambda =9$
are 21 452 and 45 395, respectively.
Packings of simulated bidisperse suspensions at small particle fractions
$\zeta _1=0.10, 0.26, 0.50$
(
$\phi =0.55$
). Large-to-small particle diameter ratio is
$\lambda =5$
. Effective size polydispersity of both small and large size classes is
$s_{\textit{eff}}=10\,\%$
.

Figure 1. Long description
The image displays three cubic containers, each filled with granular suspensions. The containers are labeled with different solid volume fractions: 0.10, 0.26, and 0.50. The suspensions contain particles of varying sizes, with larger blue particles and smaller pink particles. As the volume fraction increases from left to right, the density of the particles also increases, showing a progression from a loosely packed structure to a more densely packed structure. The particles are depicted in a three-dimensional space within each cube, illustrating the distribution and interaction of the particles within the liquid medium.
Particles within a single size class rarely exhibit a uniform size distribution in real suspensions. Based on experimental characterisation (Guy et al. Reference Guy, Ness, Hermes, Sawiak, Sun and Poon2020), the effective polydispersity
$s_{\textit{eff}}$
(where
$s_{\textit{eff}}=(d_{i2}-d_{i1})/(d_{i2}+d_{i1})$
, with
$d_{i1}$
and
$d_{i2}$
denoting the minimum and maximum particle sizes, respectively; Voivret et al. Reference Voivret, Radjai, Delenne and El Youssoufi2009) of both small and large particle size classes was set to
$10\,\%$
to represent a narrow distribution. We investigated the influence of the particle size polydispersity on the shear-induced order by comparing the cases of no polydispersity (
$s_{\textit{eff}}=0$
), narrow polydispersity (
$s_{\textit{eff}}=10\,\%$
) and polydispersity
$s_{\textit{eff}}=17\,\%$
(corresponding to
$d_{i2}=1.4d_{i1}$
) commonly used in numerical models of near-monodisperse systems to avoid strong ordering (Seto et al. Reference Samadani and Kudrolli2013; Mari et al. Reference Malkin2014; Ness, Mari & Cates Reference Ness2018; Singh et al. Reference Sierou and Brady2020); see supplementary material § 1. No shear-induced ordering was observed in the model with
$s_{\textit{eff}}=17\,\%$
, and the data of bidisperse suspensions reported in the results section are all based on the models with
$s_{\textit{eff}}=10\,\%$
. For the sake of comparison, we also established near-monodisperse granular suspension models of radii
$a$
and
$1.4a$
. Volume ratio approximately
$1:1$
was used to minimise crystallisation during flow. The number of particles in near-monodisperse systems is
$N=2048$
.
We followed an established discrete-particle simulation technique (Ness Reference Morris2021; Blair & Ness Reference Blair and Ness2022) using the simulation package LAMMPS (Plimpton Reference Pednekar, Chun and Morris1995). Strain-controlled simple shear simulations were performed over a wide range of the shear rate
$\dot {\gamma }$
. Lees–Edwards boundary conditions (Allen & Tildesley Reference Allen and Tildesley2017) with periodicity in the
$x$
,
$y$
and
$z$
directions were employed to mitigate potential boundary effects. Particles interact through three types of force and torque: drag (
F
$^{D}$
,
T
$^{D}$
), short-range pairwise lubrication (
F
$^{L}$
,
T
$^{L}$
), and direct particle contact (
F
$^{C}$
,
T
$^{C}$
). The Stokes drag forces and torques on a particle
$i$
with radius
$a_i$
are expressed as
where
$\eta _{f}$
is the liquid viscosity,
$\boldsymbol{U}_i$
is the velocity of particle
$i$
,
$\boldsymbol{\varOmega }_i$
is the rotational velocity of particle
$i$
,
$\boldsymbol{U}^{\infty }(\boldsymbol{x}_i)$
is the liquid streaming velocity at the centre of mass of particle
$i$
, and
$\boldsymbol{\varOmega }^{\infty }=({1}/{2})(\boldsymbol{\nabla }\times \boldsymbol{U}^{\infty })$
.
The hydrodynamic interactions of dense suspensions with extremely close particles are dominated by pairwise near-contact lubrication forces, and the many-body long-range forces can be effectively screened by intervening particles (Ball & Melrose Reference Ball and Melrose1997). The pairwise lubrication forces and torques between neighbouring particles
$i$
and
$j$
are expressed as (Kim & Karrila Reference Kaully, Siegmann and Shacham2013; Li, Royer & Ness Reference Lerner, Düring and Wyart2024)
\begin{align} \boldsymbol{F}_{i,j}^L &= -\boldsymbol{F}_{j,i}^L \nonumber\\&= (X_{11}^A\boldsymbol{n}_{i,j}\boldsymbol{n}_{i,j}+Y_{11}^A(\boldsymbol{I}-\boldsymbol{n}_{i,j}\boldsymbol{n}_{i,j}))(\boldsymbol{U}_j-\boldsymbol{U}_i) +Y_{11}^B(\boldsymbol{\varOmega }_i\times \boldsymbol{n}_{i,j})+Y_{21}^B(\boldsymbol{\varOmega }_j\times \boldsymbol{n}_{i,j}),\end{align}
where
$\boldsymbol{n}_{i,j}$
is the centre-to-centre unit vector, and
$\boldsymbol{I}$
is the identity tensor. The scalar prefactors are calculated as
The prefactors
$X$
and
$Y$
encode the geometry of the interacting pair. In this case,
$\lambda =a_j/a_i$
is the particle size ratio, and
$\xi =2(|\boldsymbol{r}_{i,j}|-(a_i+a_j))/(a_i+a_j)$
is the dimensionless inter-particle gap. The lubrication interactions were calculated for
$\xi$
within the range
$0.001 \lt \xi \lt 0.05$
(Ness & Sun Reference Ness, Seto and Mari2015; Li et al. Reference Lerner, Düring and Wyart2024) to mitigate the contact singularity at
$\xi \to 0$
in
$X$
and
$Y$
while not affecting the overall effective interactions between particle pairs.
Hydrodynamic forces are regularised and particle surfaces come into contact below
$\xi _{min}=0.001$
. For simplicity, contact interactions between particles
$i$
and
$j$
were modelled via a linear spring model governed by the stiffness constants
$k_n$
and
$k_t$
, respectively (Seto et al. Reference Samadani and Kudrolli2013; Blair & Ness Reference Blair and Ness2022). The contact force and torque are determined by
where
$\delta _{i,j}=a_i+a_j-|\boldsymbol{r}_{i,j}|$
is the overlap between particles
$i$
and
$j$
with the centre-to-centre vector
$\boldsymbol{r}_{i,j}$
, and
$\boldsymbol{\xi }_{i,j}$
is the tangential displacement accumulated over the duration of the contact. The friction coefficient
$\mu$
sets an upper bound on
$\boldsymbol{\xi }_{i,j}$
through
$|\boldsymbol{\xi }_{i,j}|\leq \mu k_n\delta _{i,j}/k_t$
. In this study, we adopted
$\mu =1$
, which is justified by the surface roughness effects on near-ideal spherical particles (Mari et al. Reference Malkin2014; Hsu et al. Reference Hoffman2018; More & Ardekani Reference Metzner2020). The stiffness constants
$k_n$
and
$k_t$
were set sufficiently large to mimic hard spheres with the minimal particle overlap at low and moderate shear rates
$\dot {\gamma }$
. At high
$\phi$
and/or
$\dot {\gamma }$
, we tuned
$k_n$
and
$k_t\sim \dot {\gamma }$
to avoid introducing an artificial shear-rate dependence caused by linear springs (Seto et al. Reference Samadani and Kudrolli2013); the relative particle overlapping volume
$V_r=V_o/V_p$
(where
$V_o$
and
$V_p$
represent the overlapping and total particle volumes, respectively) was maintained at less than
$0.2\,\%$
, similar to the criterion for the overlapping length (Mari et al. Reference Malkin2014). Across the entire ranges of
$\dot {\gamma }$
and
$\phi$
studied, the value of
$k_n$
varies within the range
$10^4{-}1.6\times 10^5$
(lj units) and
$k_t=2/7k_n$
(Shäfer et al. Reference Shinbrot and Muzzio1996; Sun & Sundaresan Reference Stavans2011).
The stress tensors, which are primarily decomposed into the contributions of particle-particle contact (
$\boldsymbol{\varSigma }^C$
) and hydrodynamic lubrication (
$\boldsymbol{\varSigma }^L$
), are expressed as
The relevant stresses under simple shear flow are the
$xy$
component (
$x$
for the flow direction, and
$y$
for the gradient direction) of each contribution
$\varSigma _{xy}$
and the mean normal stress (i.e. pressure)
$P=({1}/{3})(\varSigma _{xx}+\varSigma _{yy}+\varSigma _{zz})$
. The ensemble-averaged stresses were obtained using the data from 10 realisations with randomised initial particle positions. Most simulations in this study were run over strains of at least
$\dot {\gamma }t=50$
, with larger termination strain at higher shear rates. Transient start-ups were excluded, and the time-averaged stresses in the steady states, which last at least as long as the transient start-ups, were recorded for analysis. For
$\zeta _1=0.10$
suspensions that do not undergo large-scale ordering during shearing, the suspensions can reach steady states within
$5{-}10$
strain units, with the transient start-ups lasting for approximately
$3$
strain units; for
$\zeta _1=0.26$
and
$\zeta _1=0.50$
suspensions, the transient period extends longer, to
$30{-}50$
strain units, due to the large-scale ordering.
The degree of random close packing of particles is determined by calculating the coordination number or number of contacts per particle. Bidisperse particles have three types of contact: small-to-small, small-to-large or large-to-small, and large-to-large. In particular, we calculated the partial mean coordination number
$C_{ij}$
for each type of contact (
$i,j=1,2$
for a small or large component, respectively). This number is equal to the total occurrences of contact between particles of types
$i$
and
$j$
divided by the number of type
$i$
with non-zero contact numbers. The partial mean coordination number
$C_{ij}$
characterises the geometric arrangement of packed particles (Fischer & Koch Reference Fischer and Koch1979). The average number of particle-particle contacts
$Z$
is equal to the total number of contacts divided by the number of particles with non-zero contacts.
Relative viscosity
$\eta _r$
versus Stokes number
$St$
for bidisperse suspensions with (a)
$\zeta _1=0.10$
, (b)
$\zeta _1=0.50$
, (c)
$\zeta _1=0.26$
across various volume fractions
$\phi$
(particle size ratio
$\lambda =5$
, particle size polydispersity of both small and large size classes
$s_{\textit{eff}}=10\,\%$
). The critical Stokes number for the viscous-to-inertial transition,
$St_{v \to i}$
, is determined as the point of interception of the low-
$St$
data (horizontal grey dashed line) with the simplest power-law fit of the whole dataset excluding those at extremely high shear rates (black dashed line). The black dashed line in (c) marks the critical points of the OD transition. (d) Plot of
$\eta _r/\eta _{r0}(St\to 0)$
versus
$St/St_{v\to i}$
for shear thickening data in (a) and (b), illustrating a transition from Newtonian (slope
$0$
) to Bagnoldian (slope
$1$
) rheology. Hollow symbols indicate data from figure 2 of Tapia et al. (Reference Sun and Sundaresan2022) for large poly(methyl methacrylate) spheres with mean diameter
$d=4.65$
mm and four suspension fluids with viscosities
$\eta _f=11, 20, 50, 86\,\text{mPa}{\cdot}\text{s}$
.

Figure 2. Long description
The image contains four graphs labeled (a), (b), (c), and (d). Each graph plots relative viscosity (ηr) against Stokes number (St) for bidisperse suspensions with different volume fractions (ϕ) and particle size ratios (ζ1). Graphs (a), (b), and (c) show data for different values of ζ1 and ϕ, with various symbols representing different volume fractions. The critical Stokes number for the viscous-to-inertial transition (Stc) is determined as the intersection of the low-St data (horizontal grey dashed line) with a power-law fit of the dataset (black dashed line). In graph (c), the black dashed line marks the critical points of the OD transition. Graph (d) plots ηr/ηr0 versus St/Stv→i, illustrating a transition from Newtonian (slope 1) to Bagnoldian (slope greater than 1) rheology. Hollow symbols in graph (d) indicate data from a study by Tapia et al. (2022) for large poly(methyl methacrylate) spheres with a mean diameter of 5 millimeters and four suspension fluids with viscosities ranging from 1 to 100 millipascal seconds.
We used the
$xy$
component of the fabric tensor
$|\boldsymbol{A}_{12}|$
to quantify the extent of structural anisotropy (Sun & Sundaresan Reference Stavans2011). The fabric tensor is constructed as
\begin{equation} \boldsymbol{A}_{i,j} = \frac {1}{N_c}\sum _{\alpha =1}^{N_c}\boldsymbol{n}_{i,j}\boldsymbol{n}_{i,j}-\frac {1}{3}\boldsymbol{I}, \end{equation}
where
$N_c$
is the number of contacts between particles, and
$\boldsymbol{I}$
is the identity tensor. To characterise the layered structure, the relative number densities of small particles
$\rho _1$
and large particles
$\rho _2$
along the velocity gradient direction (
$y$
-axis) were calculated by dividing the number density of each size class in a slice of the system by the corresponding number density in the initial random structure (Fu et al. Reference Fu, Liu, Lu and Sun2024). The slice width is
$2d_{1}$
, where
$d_{1}$
is the mean diameter of small particles.
3. Results and discussion
3.1. Bulk rheology
Below the critical volume fraction, i.e. the jamming threshold at which particles can no longer avoid each other and the bulk and shear moduli simultaneously become non-zero (O’Hern et al. Reference Nordstrom, Verneuil, Arratia, Basu, Zhang, Yodh, Gollub and Durian2003), the rheology of granular suspensions is governed by the relative magnitude of the inertial forces of the particles and viscous forces, namely the Stokes number
$St=\rho a_1^2\dot {\gamma }/\eta _{f}$
. Considering that in experiments (Chong, Christiansen & Baer Reference Chong, Christiansen and Baer1971; Krishnan & Leighton Reference Krieger and Dougherty1995; Chen et al. Reference Chen, Xue, Li, Wen, Liu, Xue, Shi, Zhou, Xie and Mai2019; Guy et al. Reference Guy, Ness, Hermes, Sawiak, Sun and Poon2020) and simulations (Guy et al. Reference Guy, Ness, Hermes, Sawiak, Sun and Poon2020; Malbranche et al. Reference Luan2023; Singh et al. Reference Singh, Ness, Seto, de Pablo and Jaeger2024), the characteristic stress scales or shear rate scales of bidisperse suspensions adopting different PSDs are generally not distinguished, the radius of the small particles
$a_1$
is used to define
$St$
. Figures 2(a–c) present rheology data showing the reduced viscosity
$\eta _r=\varSigma _{xy}/\eta _{f}\dot {\gamma }$
as a function of
$St$
for bidisperse suspensions with different PSDs. Two flow regimes are distinguished for suspensions with
$\zeta _1=0.10$
and
$0.50$
: a rate-independent viscous regime at low shear rates, followed by an inertial shear thickening regime in which
$\eta _r$
scales linearly with
$\dot {\gamma }$
. The critical Stokes number for the viscous-to-inertial transition, denoted by
$St_{v\rightarrow i}$
, is defined as the intersection of the low shear plateau with this scaling. The values of
$St_{v\to i}$
at various volume fractions
$\phi$
are listed in table 1. Within the range of
$\phi$
studied,
$St_{v\rightarrow i}$
decreases with increasing
$\phi$
, which implies close proximity to the jamming transition where flow stops. This trend agrees qualitatively with that reported for monodisperse systems when
$\phi$
approaches
$\phi _J$
(Lerner et al. Reference Lee, Jiang, Wang, Sandy, Narayanan and Lin2012; DeGiuli, McElwaine & Wyart Reference DeGiuli, McElwaine and Wyart2016; Trulsson, DeGiuli & Wyart Reference Trappe, Prasad, Cipelletti, Segre and Weitz2017). The viscous-to-inertial transition for suspensions at
$\phi$
exceeding
$\phi _J$
occurs at an infinitesimally small shear rate, i.e.
$St_{v\rightarrow i}$
approaches zero. The viscosity
$\eta _r$
diverges at
$St\ll 1.0$
, and suspensions containing jammed particles behave like a solid. Note that ideal hard particles would cease to flow at such a high
$\phi$
.
Critical Stokes number
$St_{v\to i}$
for viscous-to-inertial transition, shown for two bidisperse suspensions with
$\zeta _1=0.10$
and
$0.50$
, and for various volume fractions
$\phi$
.

Table 1. Long description
The table presents data on the critical Stokes number for the viscous-to-inertial transition in bidisperse suspensions. It includes two sets of data for different particle size distributions, with values of xi1 and xi2 specified. The table has four columns: the first column lists the volume fractions, the second column shows the reduced viscosity values, and the third and fourth columns display the critical Stokes numbers for the two different particle size distributions. The data indicates that as the volume fraction increases, the critical Stokes number decreases, suggesting that the suspensions are approaching the jamming transition where flow stops. This trend is consistent with observations in monodisperse systems. The table provides a clear comparison of how the critical Stokes number varies with volume fraction for different particle size distributions.
The shear thinning behaviours at
$\phi =0.65$
(
$\zeta _1=0.10$
) and
$0.69$
(
$\zeta _1=0.50$
) are essentially soft-particle rheology. At volume fractions above the jamming limit, quasi-static rheology is observed for low and moderate Stokes number, in which the shear stress is almost rate-independent and extrapolates towards a non-zero yield stress (see supplementary material § 4). The shear thinning observed in this quasi-static regime is thus due to the yield stress at volume fractions above
$\phi _J$
for particles of finite stiffness. Similar shear thinning phenomena have been reported in experiments on soft colloids above jamming (Nordstrom et al. Reference Ness and Sun2010) and associated theory (Samadani & Kudrolli Reference Sakaï, Moulinet, Lechenault and Adda-Bedia2000). Here,
$k_n$
represents the normal contact stiffness between particles, which quantifies the resistance of the particle contact interface to normal deformation under compressive stress. For very hard particles with
$k_n \to \infty$
, it would be impossible to assess their soft-particle rheology as
$\hat {\dot {\gamma }} \to \infty$
, which would correspond to
$St \to \infty$
(Ness & Sun Reference Ness, Seto and Mari2015).
(a) Plot of
$\eta _r$
versus shear strain
$\dot {\gamma }t$
for bidisperse suspensions at two critical states before and after the viscosity jump (
$\phi =0.70$
). Inset: number density curves of small (
$\rho _1$
, solid symbols) and large (
$\rho _2$
, hollow symbols) particles in layers along the gradient direction (
$y$
-axis) at
$\dot {\gamma }t=20$
(
$St=1.6$
),
$\dot {\gamma }t=175$
(
$St=1.6$
) and
$\dot {\gamma }t=100$
(
$St=2.0$
), as marked by arrows with the corresponding symbols. The snapshots on the right-hand sides show the microstructure of the bidisperse suspensions at the steady state. (b) Number density curves of small (
$\rho _1$
) and large (
$\rho _2$
) particles in the steady-state suspensions with
$\zeta _1=0.10$
(
$\phi =0.64$
) and
$\zeta _1=0.50$
(
$\phi =0.68$
) at the Stokes numbers marked in figures 2(a) and 2(b).

Figure 3. Long description
The image contains two main sections labeled (a) and (b). Section (a) features a plot of viscosity versus shear strain for bidisperse suspensions at two critical states before and after a viscosity jump. The plot includes data points for two Stokes numbers, 1.6 and 2.0, represented by solid and dashed lines respectively. An inset within this plot shows number density curves of small and large particles in layers along the gradient direction at specific shear strains, marked by arrows. The snapshots on the right-hand side display the microstructure of the bidisperse suspensions at the steady state. Section (b) presents number density curves of small and large particles in steady-state suspensions with different volume fractions of small particles at specified Stokes numbers. The curves are shown for two different volume fractions, 0.10 and 0.50, with corresponding snapshots of the microstructures on the right-hand side. The graphs illustrate the variations in particle distribution and viscosity under different conditions.
Similar features of CST of suspensions with
$\zeta _1=0.10$
and
$0.50$
suggest a reduction in the flow curves at various
$\phi$
values to follow a universal thickening law. Figure 2(d) shows the viscosities normalised by their rate-independent values (
$\eta _r/\eta _{r0}$
) versus the normalised Stokes number (
$St/St_{v\rightarrow i}$
) for the suspensions below
$\phi _J$
. All data collapse onto one master curve, and the slope of the thickening section is 1. The experimental results (Tapia et al. Reference Sun and Sundaresan2022) of poly(methyl methacrylate) spheres (with mean diameter
$d=4.65$
mm) also fall onto this curve. Indeed, this
$\tau \propto \dot {\gamma }^2$
Bagnoldian scaling (Bagnold Reference Bagnold1954) has been widely observed in nearly monodisperse suspensions/granular systems (
$\lambda \gtrsim 1$
) (Fall et al. Reference Fall, Lemaître, Bertrand, Bonn and Ovarlez2010; Fernandez et al. Reference Fernandez, Mani, Rinaldi, Kadau, Mosquet, Lombois-Burger, Cayer-Barrioz, Herrmann, Spencer and Isa2013; Ness & Sun Reference Ness, Seto and Mari2015; Tapia et al. Reference Sun and Sundaresan2022). This universal flow curve indicates that both monodisperse and bidisperse suspensions that do not exhibit significant structural transformation during thickening (as shown in figure 3
b) obey a viscous-to-inertial transition mode of shear thickening.
In contrast, the flow curves of bidisperse suspensions with
$\zeta _1=0.26$
, i.e. the theoretical optimal PSD, appear somewhat discontinuous. At intermediate volume fractions (
$0.50\leq \phi \leq 0.65$
), the viscosity
$\eta _r$
jumps slightly in the shear thickening regime (figure 2
c). As
$\phi$
increases further, the increase in viscosity becomes more pronounced by several orders of magnitude at the critical shear rate
$\dot {\gamma }_c$
. To investigate the microstructural picture associated with this viscosity jump, we calculated the relative number densities of small (
$\rho _1$
) and large (
$\rho _2$
) particles along the velocity gradient direction (
$y$
-axis) at two critical states before (
$St=1.6$
) and after (
$St=2.0$
) the viscosity jump at
$\phi =0.70$
(see inset of figure 3
a). The oscillating number density curves represent a layered particle structure with alternating aggregated large and small particles, whereas the almost flat number density curves indicate uniformly distributed disordered particles. At
$St=1.6$
, the viscosity decreases by an order of magnitude upon reaching a steady state. Correspondingly, the initially disordered particles are rearranged into an ordered layered structure, as illustrated by the change in the pattern of the particle number density curves. Early studies on monodisperse suspensions also attributed shear thinning to the formation of ordered structures (Ackerson & Pusey Reference Ackerson and Pusey1988; Hoffman Reference Hoffman1998; Lee et al. Reference Kwan, Wong and Fung2018). At a slightly higher shear rate (
$St=2.0$
), the viscosity remains essentially unchanged around a considerably high value, with no significant structural transformation occurring during the flow. Therefore, the particle phase change results in a discontinuous viscosity jump in inertial flows of bidisperse granular suspensions. Similar OD transitions are also observed at the remaining volume fractions at
$\phi \geq 0.50$
; see supplementary material § 6. As
$\zeta _1$
increases from 0.10 to 0.26, the flows exhibit a gradual transition from CST to DST (see supplementary material § 2). The abruptness of the viscosity jump is positively correlated with
$\zeta _1$
. For the range
$0.26\leq \zeta _1\leq 0.50$
, the phenomenon of viscosity jump is pronounced at
$\zeta _1=0.26$
and
$\zeta _1=0.34$
; with a further increase in
$\zeta _1$
, the DST behaviour weakens.
Figure 3(b) shows the evolution of the particle number densities of suspensions with
$\zeta _1=0.10$
and
$0.50$
(the corresponding models are marked in figures 2
a,b). Neither suspension exhibits significant structural changes during shear thickening. At
$\zeta _1=0.50$
(
$\phi =0.68$
), the relative content of large particles (
$\zeta _2=0.50$
) is not sufficient to form a complete layered structure. Large particles form shear-induced strips or a partially layered structure, as shown by oscillating density curves milder than those in figure 1(a). These partially layered structures are more stable than the layered structure at the theoretical optimal PSD, with no significant change in the particle arrangement during flow regime transition. Compared with the suspensions with
$\zeta _1=0.26$
and
$0.50$
, the
$\zeta _1=0.10$
suspension maintains a disordered structure throughout the entire flow regime transitions, as shown by the nearly flat density curves in figure 3(b). Overall, the
$\zeta _1=0.26$
suspensions that form layered structures under low stresses have the lowest structural stability.
The black dashed line in figure 2(c) shows the critical points of the OD transition. Evidently, this transition depends on both
$\phi$
and
$\dot {\gamma }$
. At low shear rates, the particles are lubricated apart by a strong network of lubrication films, which retards inertial collisions. Under the constant energy input provided by simple shear, large particles self-organise into ordered layers. As the volume fraction increases, the distance between large particles within one layer is reduced, leading to an increase in the overlapping depletion zone. This leaves relatively more space for small particles to move. Consequently, the ordering becomes more pronounced at higher shear rates as the volume fraction increases, as shown by the positive slope of the OD transition line. As
$\phi$
approaches
$\phi _J$
, the flow is primarily dominated by the collective rearrangements of particles owing to sufficient constraints to lock the structure (Seto et al. Reference Samadani and Kudrolli2013). This results in rapid shear jamming, i.e. the suspensions transition from layered to a solid-like disordered state at a diminishing critical shear rate
$\dot {\gamma }_c$
, as indicated by the almost flat OD transition line at
$\phi \geq 0.67$
in figure 2(c).
Simulations of the steady flow of bidisperse suspensions with larger particle size ratios
$\lambda =7$
and
$\lambda =9$
show a similar phenomenon of viscosity jump resulting from the OD transition (see supplementary material § 3). Although the magnitude of viscosity jump and critical shear rate vary systematically with
$\lambda$
, the qualitative trend of DST behaviour (dependence on
$St$
and
$\phi$
) is consistent across models with different size ratios. The layered ordered states of suspensions with different size ratios, volume fractions and shear rates primarily fall within the same region on the reduced Stokes number
$St\times (a_2/a_2^0)^2$
reduced volume fraction
$\phi / \phi _{rcp}$
plane (where
$a_2^0$
represents the large particle radius in the model with
$\lambda =5$
). For suspensions with a wider particle size range, the
$\phi$
window of the OD transition is larger due to higher
$\phi _{rcp}$
, while the
$St$
window of the OD transition is smaller. When the volume fraction
$\phi$
falls within the range
$0.80\phi _{rcp}{-}0.83\phi _{rcp}$
, the range of
$St$
over which layered structures can form is the largest, indicating the greatest possibility of forming such ordered structures. When
$\phi$
exceeds this range, however, the range of
$St$
forming a layered structure decreases rapidly, making it difficult for the system to order.
In brief, the competition between the depletion effect, tending towards layering when particles have sufficient room for movement, and the jamming effect, which tends to form a solid-like disordered structure at
$\phi$
near
$\phi _J$
, results in the curved OD transition line. Although being more localised, the shear-induced order in monodisperse colloidal suspensions also becomes more pronounced as
$\phi$
and
$\dot {\gamma }$
increase, but it may not be present at small
$\phi$
or
$\dot {\gamma }$
values (Ackerson Reference Ackerson1990).
3.2. Microstructure
We analysed the contact networks of the suspension with
$\zeta _1=0.26$
at
$\phi =0.70$
to understand the changes in stress transmission resulting from the OD transition. In the layered structure (
$St=1.6$
), the contact force chains are sparse and weak (figure 4
a). More than
$90\,\%$
of the bond angles between the large–large particle contacts and the flow-vorticity plane (
$xz$
plane) fall within the range
$0^\circ$
–
$12^\circ$
(see supplementary material § 7), indicating that most large particles are aligned into layered ‘channels’ along the flow direction (
$x$
-axis). Small particles can move through these channels. The momentum is transferred mainly through hydrodynamic interactions, rather than collisions between particles. Occasional intra-layer large–large particle collisions and inter-layer large–small particle collisions lead to two principal stress orientations in the radial force distribution (in the
$xy$
plane, as shown in figure 4
c for
$St=1.0$
and
$1.6$
). The layered particles cannot elastically support infinitesimal loads above the critical shear rate. This entails shear-induced dissipative particle reorganisation from the ordered state to the disordered state. The contact network shifts from strongly aligned to almost percolated following the structural transformation, as evidenced by the more isotropic radial force distribution.
(a) Particle contacts are visualised as bonds before and after the viscosity jump;
$\phi =0.70$
,
$\zeta _1=0.26$
,
$N=9306$
. Red bonds indicate large–large particle contact; blue bonds indicate large–small particle contact; grey bonds indicate small–small particle contact. The width of the line segments represents the contact force magnitude. The forces are scaled in magnitude by the respective maximum values. For clarity, the width of the line segments in the right-hand image (
$St=2.0$
) is reduced by half. (b) Shear component of the fabric tensor
$A_{12}$
plotted against
$St$
for
$\zeta _1=0.26$
suspensions at different volume fractions
$\phi$
, and
$\zeta_1 =0.50$
suspensions at
$\phi =0.67$
. (c) Radial force distributions of contact forces in
$\zeta _1=0.26$
suspensions (
$\phi =0.70$
) at various
$St$
marked in (b).

Figure 4. Long description
The image contains three graphs. The first graph (a) visualizes particle contacts as bonds before and after a viscosity jump in granular suspensions. Red bonds indicate large particle contact, blue bonds indicate large-small particle contact, and grey bonds indicate small-small particle contact. The width of the line segments represents the contact force magnitude, scaled by the respective maximum values. The second graph (b) plots the shear component of the fabric tensor against St for suspensions at different volume fractions and suspensions at various values. The third graph (c) shows radial force distributions of contact forces in suspensions at different values marked in graph (b).
Figure 4(b) shows the variation in the
$xy$
component of the fabric tensor
$A_{12}$
at various
$\phi$
. A negative
$A_{12}$
represents the alignment of contacts along the compression axis (
$y=-x$
), and
$A_{12}=0$
indicates perfect isotropy. As large particles transition from ordered to disordered state,
$A_{12}$
moves closer to zero, which is consistent with the characteristic of a more isotropic contact network. In contrast, the change in
$A_{12}$
in the suspension that does not exhibit obvious structural transformation (
$\zeta _1=0.50$
) is more subtle (see the dashed line in figure 4
b), suggesting that the orientation of the contact network aligns consistently along the compression direction. Following the OD transition,
$A_{12}$
is almost rate-independent, especially at
$\phi$
approaching
$\phi _J$
. The average number of contacts with non-rattlers,
$Z^{\prime }$
, reflects the degree of dense packing in a system. In the
$d$
dimensions, a particle can be a rattler if it has fewer than
$d+1$
neighbours (Kumar et al. Reference Kulkarni and Morris2021). In the shear jammed state (
$St=50.0$
,
$\phi =0.70$
), the
$Z^{\prime }$
values for large and small particles reach
$\approx 23$
and
$\approx 4$
, respectively, indicating that small particles are near the jamming criteria above the isostatic condition
$Z^{\prime } \gt Z_{iso}^{\mu =\infty }=4$
for near-monodisperse systems (van Hecke Reference Tsai, Voth and Gollub2010; Singh et al. Reference Sierou and Brady2020). Such almost percolated particles result in system-spanning contact networks.
For polydisperse suspensions/granular matter, different types of particle contacts generally do not contribute equally to the increase in viscosity (Voivret et al. Reference Voivret, Radjai, Delenne and El Youssoufi2009; Guy et al. Reference Guy, Ness, Hermes, Sawiak, Sun and Poon2020). To understand their role in phase transition, we counted the average numbers of small-to-small (
$C_{11}$
), small-to-large (
$C_{12}$
), large-to-small (
$C_{21}$
) and large-to-large (
$C_{22}$
) contacts for the entire flow regimes, comparing the results of suspensions with and without phase transition (figure 5). Following the OD transition in the suspension with
$\zeta _1=0.26$
,
$Z$
increases suddenly by
$30.9\,\%$
, primarily owing to large-to-large and large-to-small contacts (see the inset of figure 5
a). The value of
$C_{22}$
remains approximately constant (
$C_{22}\approx 1.7$
) in the disordered state, indicating that large particles form a relatively stable contact network. For suspensions in which no apparent phase transition occurs during flow (
$\zeta _1=0.50$
), both
$Z$
and
$C_{ij}$
increase continuously in the thickening regime (figure 5
b), as expected. Note that in both
$\zeta _1=0.26$
and
$\zeta _1=0.50$
suspensions, the variation of
$C_{21}$
with increasing
$St$
is much more pronounced than that of
$C_{12}$
, where
$C_{21}$
and
$C_{12}$
represent the contacts between small and large particles normalised by different particle size classes. This is mainly due to the fact that the number of small particles is more than 40 times that of the large particles in both suspensions.
Simulated rate-dependent average number of particle–particle contacts
$Z$
(black solid lines with square symbols) and the partial mean coordination number of small-to-small (
$C_{11}$
), small-to-large (
$C_{12}$
), large-to-small (
$C_{21}$
) and large-to-large (
$C_{22}$
) contacts for (a)
$\zeta _1=0.26$
suspension (
$\phi =0.67$
) and (b)
$\zeta _1=0.50$
suspension (
$\phi =0.67$
).

Figure 5. Long description
The image contains two line graphs labeled (a) and (b), each showing the simulated rate-dependent average number of particle-particle contacts (black solid lines) and the partial mean coordination number of small-to-small, small-to-large, large-to-small, and large-to-large contacts. Graph (a) represents a suspension with a volume fraction of 0.26, while graph (b) represents a suspension with a volume fraction of 0.50. The x-axis on both graphs represents the Stokes number (St) on a logarithmic scale, ranging from 0.1 to 100. The left y-axis represents the average number of particle-particle contacts (Z), and the right y-axis represents the partial mean coordination number (C_ij). In graph (a), the black squares indicate the average number of particle-particle contacts, which increases with the Stokes number. The blue diamonds, red circles, purple triangles, and gray inverted triangles represent the partial mean coordination numbers for small-to-small, small-to-large, large-to-small, and large-to-large contacts, respectively. Similar trends are observed in graph (b), with the black squares showing an increase in the average number of particle-particle contacts with the Stokes number. The blue diamonds, red circles, purple triangles, and gray inverted triangles again represent the partial mean coordination numbers for the respective contacts. The insets in both graphs provide a zoomed-in view of the data for lower Stokes numbers. All values are approximated.
(a) Average forces of small–small (S–S), small–large (S–L) and large–large (L–L) contacts in
$\zeta _1=0.26$
and
$0.50$
suspensions (
$\phi =0.67$
) at
$St=0.2$
and
$St=50$
, as marked by the red circles in figure 5. (b) Contact networks corresponding to the models in (a). Red bonds indicate large–large particle contact; blue bonds indicate large–small particle contact; grey bonds indicate small–small particle contact. The width of the line segments represents the magnitude of the contact force. The forces are scaled in magnitude by the respective maximum values.

Figure 6. Long description
The image consists of two main parts. Part (a) features a bar graph that compares the average forces of small-small (S-S), small-large (S-L), and large-large (L-L) particle contacts in suspensions with different solid volume fractions (ζ1 = 0.26 and ζ1 = 0.50) and Stokes numbers (St = 0.2 and St = 50). The bars are color-coded, with yellow representing ζ1 = 0.26 and green representing ζ1 = 0.50. The graph shows significant differences in forces, with notable increases in the L-L contacts for higher Stokes numbers and solid volume fractions. Part (b) displays 3D visualizations of the contact networks corresponding to the conditions in part (a). The networks are color-coded: red bonds indicate large-large particle contacts, blue bonds indicate large-small particle contacts, and grey bonds indicate small-small particle contacts. The width of the line segments represents the magnitude of the contact force, scaled by the respective maximum values. The visualizations show how the contact networks change under different conditions, highlighting the complexity of particle interactions in dense granular suspensions.
Different types of particle contacts differ in their carrying forces, which constitute the heterogeneity of the contact network along with the varying number of contacts in polydisperse systems (Voivret et al. Reference Voivret, Radjai, Delenne and El Youssoufi2009; Desu & Annabattula Reference Desu and Annabattula2019). Figure 6(a) compares the average forces of different types of contact in
$\zeta _1=0.26$
and
$0.50$
suspensions before and after phase transition. The average forces, which are equal to the total force of a specific contact type divided by the number of occurrences of that contact type, are normalised by the maximum force for a
$2\,\%$
overlap of the small particle radius (
$0.02k_na_1$
). This value corresponds to the penalty parameters
$k_n$
and
$k_t$
in the monodisperse hard-sphere algorithm (Seto et al. Reference Seto, Mari, Morris and Denn2019). In the Newtonian regime (
$St=0.2$
), most particles are lubricated apart, as reflected in the extremely small magnitudes of the contact forces in both suspensions. The viscosity of the
$\zeta _1=0.26$
suspension, which has fewer particle contacts owing to the formation of a layered structure, is relatively lower.
The particles in both suspensions are close to being percolated at a high shear rate following phase transition (
$St=50$
). The contact force in the
$\zeta _1=0.26$
suspension is almost six times greater than that in the
$\zeta _1=0.50$
suspension. Consequently, the viscosity is approximately 140 % higher, although the average contact number
$Z$
is still lower. Fewer contacts do not naturally lead to higher contact forces; the elevated inter-particle contact forces in the layered structure stem from stress concentration on the remaining contacts. Under external shear, the applied stress in a disordered system is dispersed across a large number of random contacts, and transmitted through the particles along a principal axis opposing the shear flow. In the layered structure, however, the applied stress is redistributed and concentrated onto the limited intra-layer large–large particle contacts and inter-layer large–small particle contacts. Thus the contact forces are higher compared to those in a disordered structure. In summary, owing to the distinct thickening mechanisms, the suspensions with
$\zeta _1=0.26$
and
$0.50$
exhibit striking differences in their flow characteristics in terms of both the evolution of contact networks (figure 6
b) and the onset of shear thickening.
(a) Friction coefficient
$\mu$
as a function of the viscous number
$I_v$
for monodisperse and bidisperse suspensions at
$\phi \geq 0.55$
. Filled symbols indicate
$\zeta _1=0.26$
suspensions; semi-filled symbols indicate
$\zeta _1=0.10$
and
$0.50$
suspensions (the same symbols as in figure 2
d). Inset: shear stress
$\tau$
versus shear rate
$\dot {\gamma }$
for
$\zeta _1=0.26$
suspensions. (b) Variation in the contribution of the fluid to the total stress
$\sigma _{xy}^{F}/\sigma _{xy}$
. Inset:
$\sigma _{xy}^{F}/\sigma _{xy}$
versus Stokes number
$St$
for
$\zeta _1=0.26$
suspensions with different volume fractions
$\phi$
. The colour legend in (a) refers also to (b).

Figure 7. Long description
The image contains two graphs. The first graph (a) shows the friction coefficient as a function of the viscous number for monodisperse and bidisperse suspensions. Filled symbols represent suspensions, while semi-filled symbols indicate other types of suspensions. The inset in graph (a) displays shear stress versus shear rate for suspensions. The second graph (b) illustrates the variation in the contribution of the fluid to the total stress. The inset in graph (b) shows the ratio of fluid stress to total stress versus Stokes number for suspensions with different volume fractions. The color legend in graph (a) applies to both graphs.
3.3. Friction coefficient
The rheology of monodisperse suspensions and dry granular systems can be unified by the evolution of the macroscopic friction coefficient
$\mu$
(in simple shear,
$\mu \equiv \sigma /P_p$
, where
$P_p$
is a measure of the particle pressure) with the viscous number
$I_v \equiv \eta _f\dot {\gamma }/P_p$
(Boyer et al. Reference Boyer, Guazzelli and Pouliquen2011). We plotted
$\mu$
against
$I_v$
for all suspensions at
$\phi \geq 0.55$
(figure 7
a) to explore whether this governing law also applies to bidisperse suspensions with different PSDs, especially those that may undergo an OD transition. All data for suspensions in which no significant structural transformations occur during shear thickening (
$\zeta _1=0.10, 0.50$
, semi-solid symbols) collapse onto a single curve. The simulated data for monodisperse systems at different
$\phi$
and
$\dot {\gamma }$
also fall onto this curve. The friction coefficient is
$\mu \approx 0.3$
when
$I_v \to 0$
, and
$\mu$
increases with increasing
$I_v$
. This trend is qualitatively similar to that reported for dense suspensions containing monodisperse poly(methyl methacrylate) and polystyrene spheres (Boyer et al. Reference Boyer, Guazzelli and Pouliquen2011). The simulated
$\mu (I_v)$
data for suspensions with the theoretical optimal PSD (
$\zeta _1=0.26$
, solid symbols) at various
$\phi$
also collapse onto a single curve. However, the friction coefficient
$\mu$
is lower than that of the other suspensions, especially in the viscous regime in which a layered structure is formed. As discussed below, this can be attributed to the additional viscous contribution to the total shear stress.
At the onset of the viscous-to-inertial transition, the lubrication films between the particles rupture, initiating mechanical contact. As the particle inertia increases with increasing
$\dot {\gamma }$
, the contribution of the fluid to the total stress diminishes, as shown by the reduction in
$\sigma _{xy}^F/\sigma _{xy}$
in the inset of figure 7(b). Here,
$\sigma _{xy}^F/\sigma _{xy}$
can be generalised using
$I_v$
for both monodisperse and bidisperse suspensions without obvious phase transition during shear thickening. Consistent with a lower friction coefficient, the values of
$\sigma _{xy}^F/\sigma _{xy}$
for the suspensions with
$\zeta _1=0.26$
are slightly higher in the viscous regime. The layered structure that is formed in this regime reduces particle collisions as well as contact dissipation, in part because the particles maintain a relatively large average separation (Ackerson & Pusey Reference Ackerson and Pusey1988). Interestingly, the layered structure achieves an effect similar to that of a reduced
$\phi$
owing to the greater contribution of fluid to the stress (Huang et al. Reference Hsu, Ramakrishna, Zanini, Spencer and Isa2005).
4. Conclusion
Our numerical simulations provide evidence that in bidisperse granular suspensions with minor polydispersity in each particle size class, the shear-induced OD transition of large particles can cause a CST–DST transition in inertial flows. This counter-intuitive phenomenon, which occurs only at the theoretical optimal PSD (
$\zeta _1=0.26$
), arises from the competition between the entropic force and volume fraction effect. Under the depletion effect of large particles, the ordering becomes more pronounced at higher shear rates as
$\phi$
increases; as
$\phi$
approaches
$\phi _J$
, rapid shear jamming occurs, causing the suspension to transform into a solid-like disordered state at a diminishing critical shear rate. In contrast, bidisperse granular suspensions in the absence of a significant microstructural transition during flow exhibit the common viscous-to-inertial transition mode of shear thickening.
At the microscopic level, layered large particles facilitate the movement of small particles along the shear direction. Occasional intra-layer and inter-layer collisions cause two principal stress orientations in the radial force distribution. Following phase transition, the contact network shifts from strongly aligned to almost percolated, with decreased microstructural anisotropy. Large-to-large particle contacts play a dominant role in both stress transmission and phase transition, although they account for a small proportion of the total number of contacts. Statistics on the quantity and magnitude of different types of particle contacts aid in understanding the origin of stress partitioning in polydisperse systems (Voivret et al. Reference Voivret, Radjai, Delenne and El Youssoufi2009; Shire, O’Sullivan & Hanley Reference Shapiro and Probstein2016).
The rheology of monodisperse and bidisperse granular suspensions in which no significant structural transformations occur during shear thickening is completely determined by a friction law for the macroscopic friction coefficient as a function of the viscous number. The viscous-to-inertial transition can be well correlated with the emerging dominance of contact relative to the fluid stress (Huang et al. Reference Hsu, Ramakrishna, Zanini, Spencer and Isa2005; Ness & Sun Reference Ness, Seto and Mari2015). However, for bidisperse suspensions that undergo an OD phase transition, the layered structure in the viscous regime decreases the effective friction of the system owing to the increased contribution of the fluid to the total stress. This discrepancy between bidisperse suspensions with different PSDs increases the difficulty in establishing a unified framework for polydisperse suspension flows.
Although our study mainly focused on bidisperse suspensions at a fixed large-to-small particle size ratio
$\lambda =5$
, we expect the conclusions to be applicable to higher size ratios, as the close packings in both cases have common characteristics: both small and large particles are closely packed at the theoretical optimal PSD (Pednekar et al. Reference O’Hern, Silbert, Liu and Nagel2018). Most numerical studies on bidisperse suspensions to date have focused on models that comprise particles with a relatively narrow range of size distribution (
$\lambda \leq 4$
) (Pednekar et al. Reference O’Hern, Silbert, Liu and Nagel2018; Guy et al. Reference Guy, Ness, Hermes, Sawiak, Sun and Poon2020; Malbranche et al. Reference Luan2023; Singh et al. Reference Singh, Ness, Seto, de Pablo and Jaeger2024). Establishing a realistic polydisperse suspension model with a broad PSD (industrial dispersions typically have size distributions with
$s\geq 100\,\%$
) remains quite challenging owing to the requirement of a large number of particles to ensure statistical representativity and highly advanced neighbour-listing algorithms to improve the computational efficiency (Li et al. Reference Lerner, Düring and Wyart2024).
Our findings are relevant to a wide class of polydisperse suspensions in which phase transitions in the flow are essential, such as oppositely charged colloidal particles (Yuan, Takae & Tanaka Reference Yuan, Takae and Tanaka2022) and metallic glass (Luan et al. Reference Li, Royer and Ness2022). Repulsive or attractive inter-particle interactions caused by colloidal forces can have a strong influence on the macroscopic flow behaviour of dense suspensions comprising tiny particles (
$d \ll 1 \ {\unicode{x03BC}}\text{m}$
). Additional research is warranted to explore whether the DST in a diverse range of polydisperse suspensions has the characteristics of a phase transition.
Supplementary material
Supplementary material is available at http://doi.org/10.1017/jfm.2026.11717.
Acknowledgements
We appreciate stimulating discussions with L. Ju, S. Yang and S. Zhang.
Funding
This work was supported by the National Natural Science Foundation of China (Y.L., grant no. 12202007), the Natural Science Foundation of Henan Province (X.F., grant no. 252300420885) and the Key Scientific Research Project of Colleges and Universities in Henan Province (X.F., grant no. 25A130005).
Declaration of interests
The authors report no conflict of interest.
Data availability statement
Codes and script necessary to reproduce the results reported in this paper are available on request.




ζ1=0.10,0.26,0.50
ϕ=0.55
λ=5
seff=10%
ηr
St
ζ1=0.10
ζ1=0.50
ζ1=0.26
ϕ
λ=5
seff=10%
Stv→i
St
ηr/ηr0(St→0)
St/Stv→i
0
1
d=4.65
ηf=11,20,50,86mPa⋅s
Stv→i
ζ1=0.10
0.50
ϕ
ηr
γ˙t
ϕ=0.70
ρ1
ρ2
y
γ˙t=20
St=1.6
γ˙t=175
St=1.6
γ˙t=100
St=2.0
ρ1
ρ2
ζ1=0.10
ϕ=0.64
ζ1=0.50
ϕ=0.68
ϕ=0.70
ζ1=0.26
N=9306
St=2.0
A12
St
ζ1=0.26
ϕ
ζ1=0.50
ϕ=0.67
ζ1=0.26
ϕ=0.70
St
Z
C11
C12
C21
C22
ζ1=0.26
ϕ=0.67
ζ1=0.50
ϕ=0.67
ζ1=0.26
0.50
ϕ=0.67
St=0.2
St=50
μ
Iv
ϕ≥0.55
ζ1=0.26
ζ1=0.10
0.50
τ
γ˙
ζ1=0.26
σxyF/σxy
σxyF/σxy
St
ζ1=0.26
ϕ