Origin of Two Distinct Stress Relaxation Regimes in Shear Jammed Dense Suspensions.

Many dense particulate suspensions show a stress induced transformation from a liquidlike state to a solidlike shear jammed (SJ) state. However, the underlying particle-scale dynamics leading to such striking, reversible transition of the bulk remains unknown. Here, we study transient stress relaxation behaviour of SJ states formed by a well-characterized dense suspension under a step strain perturbation. We observe a strongly nonexponential relaxation that develops a sharp discontinuous stress drop at short time for high enough peak-stress values. High resolution boundary imaging and normal stress measurements confirm that such stress discontinuity originates from the localized plastic events, whereas system spanning dilation controls the slower relaxation process. We also find an intriguing correlation between the nature of transient relaxation and the steady-state shear jamming phase diagram obtained from the Wyart-Cates model.

Shear jamming and fragility in fractal suspensions under confinement.

Under applied stress, the viscosity of many dense particulate suspensions increases drastically, a response known as discontinuous shear-thickening (DST). In some cases, the applied stress can even transform the suspension into a solid-like shear jammed state. Although shear jamming (SJ) has been probed for dense suspensions with particles having well-defined shapes, such a phenomenon for fractal objects has not been explored. Here, using rheology and in situ optical imaging, we study the flow behaviour of ultra-dilute fractal suspensions of multi-walled carbon nanotubes (MWCNT) under confinement. We show a direct transition from flowing to SJ state without a precursory DST in fractal suspensions at an onset volume fraction, ϕ ∼ 0.5%, significantly lower than that of conventional dense suspensions (ϕ ∼ 55%). The ultra-low concentration enables us to demonstrate the fragility and associated contact dynamics of the SJ state, which remain experimentally unexplored in suspensions. Furthermore, using a generalized Wyart-Cates model, we propose a generic phase diagram for fractal suspensions that captures the possibility of SJ without prior DST over a wide range of shear stress and volume fractions.

Direct observation of dynamic shear jamming in dense suspensions.

Liquid-like at rest, dense suspensions of hard particles can undergo striking transformations in behaviour when agitated or sheared. These phenomena include solidification during rapid impact, as well as strong shear thickening characterized by discontinuous, orders-of-magnitude increases in suspension viscosity. Much of this highly non-Newtonian behaviour has recently been interpreted within the framework of a jamming transition. However, although jamming indeed induces solid-like rigidity, even a strongly shear-thickened state still flows and thus cannot be fully jammed. Furthermore, although suspensions are incompressible, the onset of rigidity in the standard jamming scenario requires an increase in particle density. Finally, whereas shear thickening occurs in the steady state, impact-induced solidification is transient. As a result, it has remained unclear how these dense suspension phenomena are related and how they are connected to jamming. Here we resolve this by systematically exploring both the steady-state and transient regimes with the same experimental system. We demonstrate that a fully jammed, solid-like state can be reached without compression and instead purely with shear, as recently proposed for dry granular systems. This state is created by transient shear-jamming fronts, which we track directly. We also show that shear stress, rather than shear rate, is the key control parameter. From these findings we map out a state diagram with particle density and shear stress as variables. We identify discontinuous shear thickening with a marginally jammed regime just below the onset of full, solid-like jamming. This state diagram provides a unifying framework, compatible with prior experimental and simulation results on dense suspensions, that connects steady-state and transient behaviour in terms of a dynamic shear-jamming process.

Inter-particle adhesion induced strong mechanical memory in a dense granular suspension.

Repeated/cyclic shearing can drive amorphous solids to a steady state encoding a memory of the applied strain amplitude. However, recent experiments find that the effect of such memory formation on the mechanical properties of the bulk material is rather weak. Here, we study the memory effect in a yield stress solid formed by a dense suspension of cornstarch particles in paraffin oil. Under cyclic shear, the system evolves toward a steady state showing training-induced strain stiffening and plasticity. A readout reveals that the system encodes a strong memory of the training amplitude (γT) as indicated by a large change in the differential shear modulus. We observe that memory can be encoded for a wide range of γT values both above and below the yielding albeit the strength of the memory decreases with increasing γT. In situ boundary imaging shows strain localization close to the shearing boundaries, while the bulk of the sample moves like a solid plug. In the steady state, the average particle velocity v inside the solid-like region slows down with respect to the moving plate as γ approaches γT; however, as the readout strain crosses γT, v suddenly increases. We demonstrate that inter-particle adhesive interaction is crucial for such a strong memory effect. Interestingly, our system can also remember more than one input only if the training strain with smaller amplitude is applied last.

Strain localization and yielding dynamics in disordered collagen networks.

Collagen is the most abundant extracellular-matrix protein found in mammals and the main structural and load-bearing element of connective tissues. Collagen networks show remarkable strain-stiffening, which tunes the mechanical functions of tissues and regulates cell behaviours. Linear and non-linear mechanics of in vitro disordered collagen networks have been widely studied using rheology for a range of self-assembly conditions in recent years. However, the correlation between the onset of macroscopic network failure and local deformations is not well understood in these systems. Here, using shear rheology and in situ high-resolution boundary imaging, we study the yielding dynamics of in vitro reconstituted networks of uncrosslinked type-I collagen. We find that in the non-linear regime, the differential shear modulus (K) of the network initially increases with applied strain and then begins to drop as the network starts to yield beyond a critical strain (yield strain). Measurement of the local velocity profile using colloidal tracer particles reveals that beyond the peak of K, strong strain-localization and slippage between the network and the rheometer plate sets in that eventually leads to a detachment. We generalize this observation for a range of collagen concentrations, applied strain ramp rates, as well as, different network architectures obtained by varying the polymerization temperature. Furthermore, using a continuum affine network model, we map out a state diagram showing the dependence of yield-stain and -stress on the microscopic network parameters. Our findings can have broad implications in tissue engineering and designing highly resilient biological scaffolds.

Actin filament alignment causes mechanical hysteresis in cross-linked networks.

Cells dynamically control their material properties through remodeling of the actin cytoskeleton, an assembly of cross-linked networks and bundles formed from the biopolymer actin. We recently found that cross-linked networks of actin filaments reconstituted in vitro can exhibit adaptive behavior and thus serve as a model system to understand the underlying mechanisms of mechanical adaptation of the cytoskeleton. In these networks, training, in the form of applied shear stress, can induce asymmetry in the nonlinear elasticity. Here, we explore control over this mechanical hysteresis by tuning the concentration and mechanical properties of cross-linking proteins in both experimental and simulated networks. We find that this effect depends on two conditions: the initial network must exhibit nonlinear strain stiffening, and filaments in the network must be able to reorient during training. Hysteresis depends strongly and non-monotonically on cross-linker concentration, with a peak at moderate concentrations. In contrast, at low concentrations, where the network does not strain stiffen, or at high concentrations, where filaments are less able to rearrange, there is little response to training. Additionally, we investigate the effect of changing cross-linker properties and find that longer or more flexible cross-linkers enhance hysteresis. Remarkably plotting hysteresis against alignment after training yields a single curve regardless of the physical properties or concentration of the cross-linkers.

Strain softening and stiffening responses of spider silk fibers probed using a Micro-Extension Rheometer.

Spider silk possesses unique mechanical properties like large extensibility, high tensile strength, super-contractility, etc. Understanding these mechanical responses requires characterization of the rheological properties of silk beyond the simple force-extension relations which are widely reported. Here we study the linear and non-linear viscoelastic properties of dragline silk obtained from social spider Stegodyphus sarasinorum using a Micro-Extension Rheometer that we have developed. Unlike continuous extension data, our technique allows for the probing of the viscoelastic response by applying small perturbations about sequentially increasing steady-state strain values. In addition, we extend our analysis to obtain the characteristic stress relaxation times and the frequency responses of the viscous and elastic moduli. Using these methods, we show that in a small strain regime (0-4%) dragline silk of social spiders shows a strain softening response followed by a strain stiffening response at higher strains (>4%). The stress relaxation time, on the other hand, increases monotonically with increasing strain for the entire range. We also show that the silk stiffens while ageing within the typical lifetime of a web. Our results demand the inclusion of the kinetics of domain unfolding and refolding in the existing models to account for the relaxation time behavior.

Mechanical hysteresis in actin networks.

Understanding the response of complex materials to external force is central to fields ranging from materials science to biology. Here, we describe a novel type of mechanical adaptation in cross-linked networks of F-actin, a ubiquitous protein found in eukaryotic cells. We show that shear stress changes the network's nonlinear mechanical response even long after that stress is removed. The duration, magnitude and direction of forcing history all change this mechanical response. While the mechanical hysteresis is long-lived, it can be simply erased by force application in the opposite direction. We further show that the observed mechanical adaptation is consistent with stress-dependent changes in the nematic order of the constituent filaments. Thus, this mechanical hysteresis arises from the changes in non-linear response that originates from stress-induced changes to filament orientation. This demonstrates that F-actin networks can exhibit analog read-write mechanical hysteretic properties, which can be used for adaptation to mechanical stimuli.

Discontinuous shear thickening in confined dilute carbon nanotube suspensions.

A monotonic decrease in viscosity with increasing shear stress is a known rheological response to shear flow in complex fluids in general and for flocculated suspensions in particular. Here we demonstrate a discontinuous shear-thickening transition on varying shear stress where the viscosity jumps sharply by four to six orders of magnitude in flocculated suspensions of multiwalled carbon nanotubes (MWNT) at very low weight fractions (approximately 0.5%). Rheooptical observations reveal the shear-thickened state as a percolated structure of MWNT flocs spanning the system size. We present a dynamic phase diagram of the non-Brownian MWNT dispersions revealing a starting jammed state followed by shear-thinning and shear-thickened states. The present study further suggests that the shear-thickened state obtained as a function of shear stress is likely to be a generic feature of fractal clusters under flow, albeit under confinement. An understanding of the shear-thickening phenomena in confined geometries is pertinent for flow-controlled fabrication techniques in enhancing the mechanical strength and transport properties of thin films and wires of nanostructured composites as well as in lubrication issues.

Network architecture dependent mechanical response in temperature responsive collagen-PNIPAM composites.

Collagen is the most abundant protein in the mammalian extracellular matrix. In-vitro collagen-based materials with specific mechanical properties are important for various bio-medical and tissue-engineering applications. Here, we study the reversible mechanical switching behaviour of a bio-compatible composite formed by collagen networks seeded with thermo-responsive poly(N-isopropylacrylamide) (PNIPAM) microgel particles, by exploiting the swelling/de-swelling of the particles across the lower critical solution temperature (LCST). Interestingly, we find that the shear modulus of the system reversibly enhances whenever the diameter of the microgel particles is changed from that corresponding to the polymerization temperature of the composite, irrespective of swelling or, de-swelling. However, the degree of such enhancement significantly depends on the temperature-dependent collagen network architecture quantified by the mesh size of the network. Furthermore, confocal imaging of the composite during the temperature switching reveals that the reversible clustering of microgel particles above LCST plays a crucial role in the observed switching response.

Global land subsidence mapping reveals widespread loss of aquifer storage capacity.

Groundwater overdraft gives rise to multiple adverse impacts including land subsidence and permanent groundwater storage loss. Existing methods are unable to characterize groundwater storage loss at the global scale with sufficient resolution to be relevant for local studies. Here we explore the interrelation between groundwater stress, aquifer depletion, and land subsidence using remote sensing and model-based datasets with a machine learning approach. The developed model predicts global land subsidence magnitude at high spatial resolution (~2 km), provides a first-order estimate of aquifer storage loss due to consolidation of ~17 km3/year globally, and quantifies key drivers of subsidence. Roughly 73% of the mapped subsidence occurs over cropland and urban areas, highlighting the need for sustainable groundwater management practices over these areas. The results of this study aid in assessing the spatial extents of subsidence in known subsiding areas, and in locating unknown groundwater stressed regions.

Evaluation of HbA1c from CGM traces in an Indian population.

Introduction: The development of continuous glucose monitoring (CGM) over the last decade has provided access to many consecutive glucose concentration measurements from patients. A standard method for estimating glycated hemoglobin (HbA1c), already established in the literature, is based on its relationship with the average blood glucose concentration (aBG). We showed that the estimates obtained using the standard method were not sufficiently reliable for an Indian population and suggested two new methods for estimating HbA1c. Methods: Two datasets providing a total of 128 CGM and their corresponding HbA1c levels were received from two centers: Health Centre, Savitribai Phule Pune University, Pune and Joshi Hospital, Pune, from patients already diagnosed with diabetes, non-diabetes, and pre-diabetes. We filtered 112 data-sufficient CGM traces, of which 80 traces were used to construct two models using linear regression. The first model estimates HbA1c directly from the average interstitial fluid glucose concentration (aISF) of the CGM trace and the second model proceeds in two steps: first, aISF is scaled to aBG, and then aBG is converted to HbA1c via the Nathan model. Our models were tested on the remaining 32 data- sufficient traces. We also provided 95% confidence and prediction intervals for HbA1c estimates. Results: The direct model (first model) for estimating HbA1c was HbA1cmmol/mol = 0.319 × aISFmg/dL + 16.73 and the adapted Nathan model (second model) for estimating HbA1c is HbA1cmmol/dL = 0.38 × (1.17 × ISFmg/dL) - 5.60. Discussion: Our results show that the new equations are likely to provide better estimates of HbA1c levels than the standard model at the population level, which is especially suited for clinical epidemiology in Indian populations.

Advancing remote sensing and machine learning-driven frameworks for groundwater withdrawal estimation in Arizona: Linking land subsidence to groundwater withdrawals.

Groundwater plays a crucial role in sustaining global food security but is being over-exploited in many basins of the world. Despite its importance and finite availability, local-scale monitoring of groundwater withdrawals required for sustainable water management practices is not carried out in most countries, including the United States. In this study, we combine publicly available datasets into a machine learning framework for estimating groundwater withdrawals over the state of Arizona. Here we include evapotranspiration, precipitation, crop coefficients, land use, annual discharge, well density, and watershed stress metrics for our predictions. We employ random forests to predict groundwater withdrawals from 2002 to 2020 at a 2 km spatial resolution using in situ groundwater withdrawal data available for Arizona Active Management Areas (AMA) and Irrigation Non-Expansion Areas (INA) from 2002 to 2009 for training and 2010-2020 for validating the model respectively. The results show high training ( R 2 ≈ 0.9 ) and good testing ( R 2 ≈ 0.7 ) scores with normalized mean absolute error (NMAE) ≈ 0.62 and normalized root mean square error (NRMSE) ≈ 2.34 for the AMA/INA region. Using this method, we spatially extrapolate the existing groundwater withdrawal estimates to the entire state and observe the co-occurrence of both groundwater withdrawals and land subsidence in South-Central and Southern Arizona. Our model predicts groundwater withdrawals in regions where production wells are present on agricultural lands and subsidence is observed from Interferometric Synthetic Aperture Radar (InSAR), but withdrawals are not monitored. By performing a comparative analysis over these regions using the predicted groundwater withdrawals and InSAR-based land subsidence estimates, we observe a varying degree of subsidence for similar volumes of withdrawals in different basins. The performance of our model on validation datasets and its favourable comparison with independent water use proxies such as InSAR demonstrate the effectiveness and extensibility of our combined remote sensing and machine learning-based approach.

Signature of jamming under steady shear in dense particulate suspensions.

Under an increasing applied shear stress ([Formula: see text]), the viscosity of many dense particulate suspensions increases drastically beyond a stress onset ([Formula: see text]), a phenomenon known as discontinuous shear-thickening. Recent studies point out that some suspensions can transform into a stress induced solid-like shear jammed (SJ) state at high particle volume fraction ([Formula: see text]). SJ state develops a finite yield stress and hence is distinct from a shear-thickened state. Here, we study the steady state shear-thickening behaviour of dense suspensions formed by dispersing colloidal polystyrene particles (PS) in polyethylene glycol (PEG). We find that for small [Formula: see text] values the viscosity of the suspensions as a function of [Formula: see text] can be well described by Krieger-Dougherty (KD) relation. However, for higher values of [Formula: see text] ([Formula: see text] [Formula: see text]), KD relation systematically overestimates the measured viscosity, particularly for higher [Formula: see text] values. This systematic deviation can be rationalized by the weakening of the sample due to flow induced failures of the solid-like SJ state. Using Wyart-Cates model, we propose a method to predict the SJ onset from the steady state rheology measurements. Our results are further supported by in situ optical imaging of the sample boundary under shear.

Spatiotemporal nematodynamics in wormlike micelles en route to rheochaos.

We show through polarized light scattering experiments the spatially inhomogeneous orientational dynamics for shear-thinning wormlike micellar gels (cetyltrimethylammonium tosylate+sodium chloride+H2O ) en route to rheochaos. For shear rates in the plateau of the flow curve, we see alternating bright and dark birefringent stripes stacked along the vorticity. The orientational order in adjacent bands is predominantly oriented at +45 degrees and -45 degrees to the flow (v) in the (v,nablav) plane, respectively. We have made an attempt to correlate the observed orientational ordering in terms of the two-dimensional Taylor-like velocity rolls in a gradient banding fluid. The bands show spatial motion along the vorticity, and the orientation dynamics of the interface delineating adjacent bands completely correlates with the temporal dynamics of the stress. Furthermore, the observed spatial dynamics of the interfaces of the rolls depends crucially on the gap width of the Couette cell.

Dynamic shear jamming in dense granular suspensions under extension.

Unlike dry granular materials, a dense granular suspension like cornstarch in water can strongly resist extensional flows. At low extension rates, such a suspension behaves like a viscous fluid, but rapid extension results in a response where stresses far exceed the predictions of lubrication hydrodynamics and capillarity. To understand this remarkable mechanical response, we experimentally measure the normal force imparted by a large bulk of the suspension on a plate moving vertically upward at a controlled velocity. We observe that, above a velocity threshold, the peak force increases by orders of magnitude. Using fast ultrasound imaging we map out the local velocity profiles inside the suspension, which reveal the formation of a growing jammed region under rapid extension. This region interacts with the rigid boundaries of the container through strong velocity gradients, suggesting a direct connection to the recently proposed shear-jamming mechanism.

Negative velocity fluctuations and non-equilibrium fluctuation relation for a driven high critical current vortex state.

Under the influence of a constant drive the moving vortex state in 2H-NbS2 superconductor exhibits a negative differential resistance (NDR) transition from a steady flow to an immobile state. This state possesses a high depinning current threshold ([Formula: see text]) with unconventional depinning characteristics. At currents well above [Formula: see text], the moving vortex state exhibits a multimodal velocity distribution which is characteristic of vortex flow instabilities in the NDR regime. However at lower currents which are just above [Formula: see text], the velocity distribution is non-Gaussian with a tail extending to significant negative velocity values. These unusual negative velocity events correspond to vortices drifting opposite to the driving force direction. We show that this distribution obeys the Gallavotti-Cohen Non-Equilibrium Fluctuation Relation (GC-NEFR). Just above [Formula: see text], we also find a high vortex density fluctuating driven state not obeying the conventional GC-NEFR. The GC-NEFR analysis provides a measure of an effective energy scale (E eff ) associated with the driven vortex state. The E eff corresponds to the average energy dissipated by the fluctuating vortex state above [Formula: see text]. We propose the high E eff value corresponds to the onset of high energy dynamic instabilities in this driven vortex state just above [Formula: see text].

Nonlinear viscoelasticity of entangled wormlike micellar fluid under large-amplitude oscillatory shear: role of elastic Taylor-Couette instability.

The role of elastic Taylor-Couette flow instabilities in the dynamic nonlinear viscoelastic response of an entangled wormlike micellar fluid is studied by large-amplitude oscillatory shear (LAOS) rheology and in situ polarized light scattering over a wide range of strain and angular frequency values, both above and below the linear crossover point. Well inside the nonlinear regime, higher harmonic decomposition of the resulting stress signal reveals that the normalized third harmonic I_{3}/I_{1} shows a power-law behavior with strain amplitude. In addition, I_{3}/I_{1} and the elastic component of stress amplitude σ_{0}{E} show a very prominent maximum at the strain value where the number density (n_{v}) of the Taylor vortices is maximum. A subsequent increase in applied strain (γ) results in the distortions of the vortices and a concomitant decrease in n_{v}, accompanied by a sharp drop in I_{3} and σ_{0}{E}. The peak position of the spatial correlation function of the scattered intensity along the vorticity direction also captures the crossover. Lissajous plots indicate an intracycle strain hardening for the values of γ corresponding to the peak of I_{3}, similar to that observed for hard-sphere glasses.

Statistical properties of entropy-consuming fluctuations in jammed states of laponite suspensions: Fluctuation relations and generalized Gumbel distribution.

We report a universal large deviation behavior of spatially averaged global injected power just before the rejuvenation of the jammed state formed by an aging suspension of laponite clay under an applied stress. The probability distribution function (PDF) of these entropy consuming strongly non-Gaussian fluctuations follow an universal large deviation functional form described by the generalized Gumbel (GG) distribution like many other equilibrium and nonequilibrium systems with high degree of correlations but do not obey the Gallavotti-Cohen steady-state fluctuation relation (SSFR). However, far from the unjamming transition (for smaller applied stresses) SSFR is satisfied for both Gaussian as well as non-Gaussian PDF. The observed slow variation of the mean shear rate with system size supports a recent theoretical prediction for observing GG distribution.

Universality and scaling behavior of injected power in elastic turbulence in wormlike micellar gel.

We study the statistical properties of spatially averaged global injected power fluctuations for Taylor-Couette flow of a wormlike micellar gel formed by surfactant cetyltrimethylammonium tosylate. At sufficiently high Weissenberg numbers the shear rate, and hence the injected power p(t), at a constant applied stress shows large irregular fluctuations in time. The nature of the probability distribution function (PDF) of p(t) and the power-law decay of its power spectrum are very similar to that observed in recent studies of elastic turbulence for polymer solutions. Remarkably, these non-Gaussian PDFs can be well described by a universal, large deviation functional form given by the generalized Gumbel distribution observed in the context of spatially averaged global measures in diverse classes of highly correlated systems. We show by in situ rheology and polarized light scattering experiments that in the elastic turbulent regime the flow is spatially smooth but random in time, in agreement with a recent hypothesis for elastic turbulence.