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REVIEW 4 major objections 5 minor 59 references

Tuning the Viscosity and Jamming Point in Dense Active non-Brownian Suspensions

T0 review · 4 major / 5 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read Run-and-tumble activity fluidizes dense frictional suspensions and shifts their jamming point toward random close packing.

desk verdict A plausible DEM study that makes a credible case for activity fluidizing dense frictional suspensions and shifting jamming, but the quantitative scaffolding needs error bars, convergence checks, and less retrofitted scaling before the exponents can be trusted. read the letter →

arxiv 2506.13316 v1 pith:KIYJD43I submitted 2025-06-16 cond-mat.soft cond-mat.stat-mech

Bhanu Prasad Bhowmik This is my paper · ORCID
classification cond-mat.softcond-mat.stat-mech
keywords activesuspensionsrun-and-tumbleparticlesshearjammingviscosityreductionfrictionalcontactsnon-Browniandiscreteelementmethodsuspensiontemperature
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper argues that adding run-and-tumble active particles to a dense, non-Brownian frictional suspension can lower its viscosity by an order of magnitude and push the shear-jamming volume fraction up to random close packing. The mechanism is microscopic: activity breaks existing frictional contacts and prevents new ones from forming, shortening and isotropizing the force-chain network. The effect is strong for frictional particles and nearly absent for frictionless ones, and a larger active force is needed to unjam an already jammed state than to keep an unjammed state flowing. The paper closes with a new constitutive law based on the suspension temperature that collapses active and passive rheology onto a single curve.

What carries the argument

The central object is the frictional contact network, quantified by the mean number of frictional contacts per particle, $n_{fc}$. In passive dense suspensions, $n_{fc}$ grows sharply with volume fraction, producing long, anisotropic force chains whose proliferation drives the viscosity divergence and shear jamming. Run-and-tumble activity acts as local random driving: active particles push their neighbours, breaking existing contacts and preventing new ones, which lowers $n_{fc}$, shortens force chains, and isotropizes the contact network. The paper introduces an effective temperature $T_{\mathrm{eff}} \sim F_a^4 \tau_p$ to collapse viscosity data at small activity (rather than the usual $F_a^2\tau_p$), and a constitutive law built on the suspension temperature $\Theta_s = \eta_f \delta u / a P$: $\mu^{1.65}\Theta_s = \gamma F(J)$, where $\mu$ is macroscopic friction, $J$ the viscous number, and $\gamma$ distinguishes active ($\gamma=1$) from passive ($\gamma=2$) systems.

What would settle it

Run the same shear protocol with a different lubrication cutoff, for example regularizing the gap at $10^{-4}a'$ instead of $10^{-3}a'$, or with contact stiffness $k_n=k_t=10^5$; if the order-of-magnitude viscosity drop and the shift of $\phi_J^{\mu_p}$ toward $\phi_{\mathrm{RCP}}$ disappear or change sign, the reported activity effect is controlled by the truncation. Alternatively, measure the relative viscosity of a dense frictional suspension ($\phi$ near 0.55) seeded with a few percent of self-propelled Janus colloids: the claim predicts a drop of at least a factor of several compared with the passive suspension at the same $\phi$.

Watch

Extended reading notes

Core claim

Using discrete-element simulations of bidisperse non-Brownian spheres with contact and lubrication forces, the author shows that run-and-tumble activity—parameterized by active fraction $C_a$, active force $F_a$, and persistence time $\tau_p$—systematically reduces the relative viscosity $\eta_r$ of dense frictional suspensions, by more than an order of magnitude at the highest volume fractions studied. The reduction is monotonic in $C_a$ but non-monotonic in $F_a$ and $\tau_p$: $\eta_r$ first falls to a volume-fraction-dependent minimum $\eta_r^m$ at optimal values $F_a^m$ and $\tau_p^m$, then rises again because strong activity enhances diffusion. Both $F_a^m$ and $\eta_r^m$ diverge as $\phi$ approaches $\phi_{\mathrm{RCP}}$, and the shear-jamming volume fraction $\phi_J^{\mu_p}$ increases with activity, reaching $\phi_{\mathrm{RCP}}$ for full activity. Microscopically, the mean number of frictional contacts $n_{fc}$ tracks the viscosity curve, and force chains become shorter and more isotropic with a reduced velocity-correlation length. The author also finds that unjamming a pre-jammed state requires a larger active force than preventing jamming from the start, and that standard $\mu$–$J$ rheology fails for active suspensions while the generalized law $\mu^{1.65}\Theta_s = \gamma F(J)$, with $\gamma=1$ for active and $\gamma=2$ for passive systems, collapses the data.

Load-bearing premise

The results depend on the simulation's choices for when lubrication forces are truncated and regularized (switched off for gaps larger than half a small-particle radius and capped at one-thousandth of that radius) and for contact stiffness; if those cutoffs bias how many frictional contacts form in active versus passive systems, the viscosity reduction and jamming shift could be model artifacts rather than robust physics.

Editorial extensions

If this is right

  • Dense frictional suspensions can be fluidized without changing their composition or applying external mechanical agitation: adding a modest fraction of active particles lowers viscosity by up to an order of magnitude near jamming.
  • The shear-jamming volume fraction becomes tunable in situ by adjusting active fraction, force, or persistence time; at full activity it moves from $\phi_J^{\mu_p=1}\approx0.58$ to $\phi_{\mathrm{RCP}}\approx0.636$.
  • Jammed states respond differently from unjammed ones: a modest active force keeps an unjammed suspension flowing, but a jammed suspension needs a substantially larger force to break its force chains.
  • The standard $\mu$–$J$ rheology does not hold for active suspensions; the suspension-temperature law $\mu^{1.65}\Theta_s = \gamma F(J)$ provides a unified description for active and passive systems.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The author leaves implicit that this viscosity-reduction mechanism may be generic: any local, momentum-neutral agitation that breaks frictional contacts—such as cyclic orthogonal deformation or acoustic forcing—could produce the same fluidization and jamming shift as run-and-tumble activity.
  • A testable extension is to map the optimal persistence time $\tau_p^m$ onto the local structural relaxation time of the passive suspension; the data hint that activity tunes viscosity most efficiently when its reorientation time matches local rearrangement timescales.
  • If contact breaking is the whole story, the same tenfold viscosity drop should be observable in experiments with a small fraction of self-propelled colloids in a dense frictional suspension, which would confirm that activity is a practical rheological control knob.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The manuscript reports DEM simulations of dense non-Brownian suspensions containing a fraction of run-and-tumble active particles. It studies how the active force F_a, persistence time τ_p, and active fraction C_a affect the relative viscosity η_r, the mean number of frictional contacts n_fc, the force-chain microstructure, and the shear-jamming volume fraction. The main claims are that activity reduces the viscosity by up to an order of magnitude, that this reduction arises from a decrease in the number of frictional contacts and a shortening/isotropization of force chains, and that for frictional particles the shear-jamming volume fraction can be shifted toward random close packing. The paper also proposes an effective temperature T_eff ~ F_a^4 τ_p and a constitutive law μ^{1.65} Θ_s = γ F(J) that is intended to unify active and passive data.

Significance. If the central mechanisms hold, the work would establish a practical route to fluidize dense frictional suspensions using run-and-tumble activity and to tune the shear-jamming point, with relevance to active colloids, bacterial suspensions, and industrial dense slurries. The contrast between frictional and frictionless systems in Fig. 4 is internally consistent, and the use of n_fc as a microscopic observable is appropriate. The distinction between preventing force-chain formation and breaking an already jammed force-chain network is a valuable conceptual point. However, the quantitative claims rest on several fitted exponents and on simulation parameters that are not tested for robustness, and the paper does not report ensemble statistics. These gaps currently limit the strength of the conclusions.

major comments (4)
  1. [Simulation details; Tuning the viscosity using active particles] No ensemble averaging or error bars are reported anywhere in the manuscript. In particular, Figs. 1, 2(b), and 3(a) present data that appear to come from a single run per parameter set, so the divergence exponents α = 2.04 and β = 2.64 and the collapses shown in Fig. 2(b) have no quantified statistical uncertainty. This is load-bearing because the central claims about the existence of a minimum in η_r and about the functional forms F_1(ϕ) and F_2(ϕ) depend on identifying minima and divergences accurately. The authors should report the number of independent runs, standard errors, or at least state why single runs are sufficient for the reported observables.
  2. [Simulation details; Microscopic understanding of viscosity reduction] The contact and lubrication truncations are not tested for convergence. The lubrication force is set to zero for gaps h_ij > a'/2 and regularized at h_ij = 10^{-3} a', and contact stiffnesses are set to k_n = k_t = 10^4. Because the paper's central mechanism is that activity reduces the number of frictional contacts n_fc, and n_fc depends directly on the numerical rules for when contacts form and how long they persist, the reported viscosity reduction and the shift in ϕ_J could be artifacts of these cutoffs rather than robust physics. The authors should vary the lubrication cutoff, the regularization scale, and the contact stiffnesses for at least the key curves in Fig. 3(a) and Fig. 4(a) and show that the trends are unchanged.
  3. [Tuning the viscosity using active particles; Constitutive law] The effective temperature is first defined as T_eff ~ F_a^2 τ_p, and when this fails to collapse the data at small values, the manuscript adopts T_eff ~ F_a^4 τ_p with the explicit statement that the microscopic origin of the exponent 4 is not studied. Similarly, the constitutive law μ^{1.65} Θ_s = γ F(J) uses an exponent 1.65 that is fitted to the same active and passive data it then describes, without a quantitative collapse metric or an independent test. As presented, these are fitted descriptors rather than validated organizing laws. The paper would be materially strengthened by testing the proposed forms on parameter combinations not used in the fit and by reporting a quantitative measure of collapse quality.
  4. [Tuning the jamming volume fraction] The claim that activity can push ϕ_J to ϕ_RCP is supported only by visual inspection of Fig. 4(a): the text says that the data for F_a = 3 and 90 'suggest' this shift, but no fitted values of ϕ_J for the active systems, no divergence analyses, and no error bars are provided. Since the shift of the jamming point toward ϕ_RCP is a headline conclusion, the authors should determine ϕ_J for each active system using the same divergence procedure as in Fig. 2(b) and report the resulting values, along with the numerical value used for ϕ_RCP.
minor comments (5)
  1. [Figure 1 caption] The figure caption does not define the symbols used in panels (f) and (g), and the meaning of the green dotted lines as 'the coordinate of the minimum' is ambiguous for panels where both F_a and τ_p vary; please clarify.
  2. [Tuning the jamming volume fraction] In the text, 'the η_r−γ curve starts to approach that of the passive system' appears to refer to the η_r–ϕ data in Fig. 4(a); the notation should be corrected to η_r–ϕ.
  3. [Figure 4 caption] The caption labels panels (c), (d), and (e) as μ(J), Θ_s(J), and μ/Θ_s(J), but the text refers to Fig. 4(d), (e), and (f) for these quantities; the panel numbering is inconsistent and should be fixed.
  4. [Simulation details] The simulation units are not stated explicitly. The text says that values are reported in raw dimensional form, but the units of F_a and τ_p are never defined; please specify the unit system (e.g., in terms of a, k_n a, and γ̇) in the Simulation details section.
  5. [Constitutive law] The symbol γ is used both for the shear strain in the jamming–unjamming section and for the prefactor in the constitutive law μ^{1.65} Θ_s = γ F(J); this overloading is confusing and should be resolved by renaming one of them.

Circularity Check

3 steps flagged · score 4.0 of 10

Core viscosity/jamming mechanism is independently evidenced, but three fitted rescaling laws (Teff exponent, mu^1.65 Theta_s law, divergence exponents) are post-hoc fits presented as organizing laws.

  1. fitted input called prediction [Section 'Tuning the viscosity using active particles', Fig. 1(f)-(g), effective-temperature passage]
    "To account for this, we introduce a new definition of the effective temperature: Teff∼ F 4 aτp. The dependence of ηr on F 4 aτp is shown in (f), which successfully collapses the data in the small-value regime. However, the microscopic origin of this form of effective temperature with an exponent 4 is not studied here."

    The exponent 4 is not derived; it is adopted precisely because it collapses the same η_r(F_a, τ_p) data that the standard exponent-2 form failed to collapse. The preceding paragraph frames Teff as a variable that should make different (F_a, τ_p) combinations give the same η_r, and the new definition is chosen until that criterion is met. Thus the 'effective temperature' is a fit parameter selected by the data it is then used to organize, not an independent variable from which η_r is predicted. The author's admission that the microscopic origin of the exponent is unstudied confirms that this is a phenomenological rescaling rather than a derivation.

  2. fitted input called prediction [Section 'Constitutive law', Fig. 4(f), proposed law μ^1.65 Θ_s = γF(J)]
    "In (f), µ, appropriately scaled by Θs, is plotted as a function of J. The quality of the data collapse suggests a new constitutive law, µ1.65Θs =γF(J), for the rheology of active dense suspensions where F(J) is the scaling function, and γ = 1 for active systems and 2 for passive systems."

    The exponent 1.65 and the factor γ=2 for the passive branch are chosen by the collapse shown in the same panel; they are not obtained from an independent data set or from the μ-J constitutive framework that was just rejected for active systems. The success of the law is therefore the very criterion used to select its parameters, so the law is a post-hoc fit to the curves it is claimed to unify. It does not make an out-of-sample prediction. The passive branch is also calibrated on the passive data in the same figure, so 'holds for both passive and active suspensions' restates the fit rather than testing it.

1 more flagged steps
  1. fitted input called prediction [Section 'Tuning the viscosity using active particles', Fig. 2(b) and inset, scaling functions F1(φ) and F2(φ)]
    "Both Fm a and ηm r increase with ϕ and diverge close to ϕRCP as shown in Fig. 2(b) where green and red solid lines represent the functional forms Fm a (ϕ,τp) = F1(ϕ)∼ (ϕJ−ϕ)−α and ηm r (ϕ,τp) =F2(ϕ)∼ (ϕJ−ϕ)−β, respectively, with α = 2.04, β = 2.64, and ϕJ = 0.636. The Inset of (b) shows the collapse of data presented in (a) by scaling Fa andηr usingF1(ϕ) andF2(ϕ)."

    The parameters α, β, and φ_J are fitted to the same η_r(F_a) data shown in Fig. 2(a); the inset collapse is the optimization target, not an independent check. Hence the claim that F_m^a and η_m^r diverge as φ→φ_RCP is a fitted power-law description of the measured minima, not a prediction of a divergence from a separate argument. This does not invalidate the measured trend, but it should be read as a curve fit rather than a derived scaling law.

full rationale

The core physical result — activity reduces viscosity and shifts the jamming point by lowering the mean number of frictional contacts and shortening/isotropizing force chains — is not circular. The quantities n_fc, force-chain geometry, and η_r are measured independently in the simulation; the viscosity reduction is traced to a separately measured drop in contact stress, and the φ_J shift is read off the η_r(φ) curves. The contact-count mechanism does not reduce to any of the fitted parameters. The fitted 'organizing laws' (the F^4τ_p effective temperature, the μ^1.65Θ_s=γF(J) constitutive law, and the (φ_J-φ)^-α / ^-β divergence fits) are post-hoc fits because their exponents are chosen to collapse the very data they are then said to describe; these are the flagged circular-adjacent steps, but they are not load-bearing for the central viscosity/jamming mechanism. The self-citations for Θ_s (Refs. [58,59]) are not treated as circular: Θ_s is a parameter-free local quantity with an independent definition, and no uniqueness theorem is imported from those papers. Numerical-truncation concerns (lubrication cutoff a'/2, regularization at 10^-3a', contact stiffness 10^4) are correctness and robustness risks, not circularity, and do not enter the circularity score.

Assumptions & free parameters 6 free parameters · 5 assumptions · 1 invented entities

The main quantitative outputs depend on several fitted exponents and on the simulation's domain assumptions. The contact-breaking mechanism itself is not axiomatic, but the scaling laws, the effective temperature, and the constitutive relation are empirical fits rather than parameter-free derivations.

free parameters (6)
  • phi_J (jamming volume fraction in divergence fits) = 0.636
    Used in F1(phi) ~ (phi_J - phi)^-alpha and F2(phi) ~ (phi_J - phi)^-beta; treated as the isotropic RCP value without an independent measurement for this bidisperse composition.
  • alpha = 2.04
    Fitted exponent for the active force at minimum viscosity, F^m_a(phi) ~ (phi_J - phi)^-alpha.
  • beta = 2.64
    Fitted exponent for the minimum viscosity, eta^m_r(phi) ~ (phi_J - phi)^-beta.
  • effective temperature exponent n in Teff ~ F_a^n tau_p = n = 4
    Chosen after n = 2 failed to collapse the data; no microscopic derivation is provided.
  • constitutive exponent in mu^1.65 Theta_s = gamma F(J) = 1.65
    Fitted to produce the collapse shown in Fig. 4(f).
  • gamma prefactor in constitutive law = 1 for active, 2 for passive
    Set by hand to align the two branches of the collapse.
assumptions (5)
  • domain assumption Lubrication interactions can be cut off at h_ij > a'/2 and regularized at h_ij = 10^-3 a' without changing the contact-rheology mechanism.
    Invoked in the simulation details; the number of frictional contacts is the central observable, so this cutoff directly shapes the result.
  • domain assumption The shear rate gamma_dot = 10^-3 places the system in the rate-independent regime, and run-and-tumble active stress averages to zero in the measurement window.
    Stated in the simulation details; if residual ordering or rate dependence appears, eta_r would mix activity with inertial or rate effects.
  • domain assumption Mean frictional contact number n_fc > 4 marks shear jamming in these suspensions.
    Used in the jamming section to connect force-chain anisotropy and the jamming volume fraction.
  • ad hoc to paper The suspension temperature Theta_s = eta_f delta u / (a P) is a sufficient state variable to collapse active and passive rheology.
    The constitutive law in the final section is built on this choice; no derivation is given, only a curve collapse.
  • standard math The Cundall-Strack contact law with Coulomb friction and tangential displacement history is valid for dense non-Brownian frictional suspensions.
    Domain-standard DEM model, cited as Ref. [46].
invented entities (1)
  • Effective temperature Teff ~ F_a^4 tau_p
    purpose: To collapse viscosity data for different combinations of active force and persistence time.
    Introduced ad hoc after Teff ~ F_a^2 tau_p failed to collapse the data; the exponent 4 has no microscopic derivation and no independent falsifiable handle.

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Cite this review

Pith. "Pith review of Tuning the Viscosity and Jamming Point in Dense Active non-Brownian Suspensions." pith.science (2026). https://pith.science/paper/KIYJD43I

@misc{pith2026250613316,
  author       = {Pith},
  title        = {Pith review of: Tuning the Viscosity and Jamming Point in Dense Active non-Brownian Suspensions},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KIYJD43I}},
  note         = {Machine review of arXiv:2506.13316}
}
read the original abstract

Using numerical simulations, we study the rheological response of dense non-Brownian suspensions containing active particles. The active particles are modelled as run-and-tumble particles with three controlling parameters: the fraction of active particles in the system, an active force applied to the particles, and a persistence time after which the direction of the active force changes randomly. Our simulations reveal that the presence of activity can reduce the viscosity (by an order of magnitude) by decreasing the number of frictional contacts, which also shifts the jamming point to a higher volume fraction. Moreover, the microscopic structure of force chains in the presence of activity is qualitatively different from that in the passive system, showing reduced anisotropy. We also find that while the presence of activity drives the system away from jamming by preventing the formation of force chains, unjamming an already jammed state by breaking existing force chains requires a higher activity strength. Finally, we propose a new constitutive law to describe the rheology of dense active non-Brownian suspensions.

Figures

Figures reproduced from arXiv: 2506.13316 by the authors.

Figure 1
Figure 1. FIG. 1. Tuning the viscosity by varying different parameters of active particles. Shown is the variation of relative viscosity [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. (a) Relative viscosity [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3. Microscopic mechanism underlying the reduction of [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: FIG. 4. Tuning the shear jamming volume fraction using [PITH_FULL_IMAGE:figures/full_fig_p005_4.png]

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Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.