We review thixotropy, its attributes, and accompanying rheological phenomena, such as yielding, hysteresis in shear-rate ramps, the influence of rest time and viscosity bifurcation, and the prevalence and importance of thixotropy in common fluids. While older work is reviewed in brief, the major emphasis is on recent developments, including nonmonotonic responses of stress to changes in strain rate, viscosity bifurcation, shear banding, and kinematic hardening. The major categories of phenomenological constitutive models are reviewed; these can include viscoelasticity and aging, plasticity, kinematic hardening, and thixotropy; and distinctions between these phenomena and thixotropy are discussed. A few available microstructural models are also reviewed, including population balance models and mesoscopic simulations. We end by highlighting important future work that is needed, including further development of microscopic models and their connection to phenomenological constitutive equations, detailed measurements of microstructures and flow fields with bands, and the investigation of flows other than simple shear.

The concept of thixotropy was introduced a century ago by Peterfi [1], but its study was soon thereafter overshadowed by an explosion of interest in linear and nonlinear viscoelasticity, especially of polymeric fluids. While the stresses in both viscoelastic and thixotropic fluids depend on their past deformation history, viscoelastic fluids are characterized by elasticity, whereas thixotropic fluids are characterized by the slow time dependence of their viscosity or yield stress. Long polymers deform elastically without breaking and produce viscoelasticity. Particle clusters connected by inextensible, fragile, bonds can break reversibly under stress, temporarily reducing viscosity, but not storing much elastic energy, leading to thixotropy. While constitutive theories for polymeric fluids have long been grounded in their microstructural physics of polymer deformation and relaxation, until recently, most constitutive equations for thixotropic materials have been phenomenological. In recent years, however, thixotropy has received increasing attention, since its importance and prevalence (see below), and its relative underdevelopment, have become increasingly recognized. It is thus time to review what has been accomplished, especially in recent years, and to lay out an agenda for future research in thixotropic phenomena.

Multiple excellent reviews of thixotropy are already available; namely, those of Bauer and Collins [2], Mewis [3], Barnes [4], Mujumdar et al. [5], Mewis and Wagner [6], and de Souza Mendes and Thompson [7]. Barnes’s review [4] focuses on the historical development of the topic from its earliest years, the definitions of thixotropy that have been given, its distinction from viscoelasticity, the typical behavior associated with thixotropy, a tabulation of publications describing various thixotropic materials, and a listing of the then-common models of thixotropy. The review of Mewis [3] defines thixotropy and its characteristics, lists materials commonly showing thixotropy, and then reviews constitutive equations based on the inelastic Reiner-Rivlin fluid, including integral generalizations, as well as viscoelastic constitutive equations to which thixotropy has been added. Mewis and Wagner [6] update this with a careful distinction between thixotropy and viscoelasticity and show typical rheological tests that display viscoelastic characteristics, along with a summary of models. Mujumdar et al. [5] nicely tabulate rheological phenomena associated with thixotropy, as well as functional forms used in constitutive equations for thixotropy. The review of de Souza Mendes and Thompson [7] focuses especially on the combination of thixotropy with elasticity and plasticity, which is a subject of growing interest. They also categorize thixotropic equations, for example, distinguishing ones that start with a viscoplastic stress equation, and add elasticity and thixotropy, from those that start with a viscoelastic equation, to which plasticity and thixotropy are introduced. De Souza Mendes and Thompson argue that the latter are superior and favor making the evolution of thixotropic structure dependent on stress rather than on strain rate. We discuss these options in more detail later.

This new review summarizes the most important aspects covered in the previous reviews, but then focuses attention on new developments and on recommended future directions. Readers are encouraged to read previous reviews to obtain a more complete picture of this complex topic.

The scope of this review is determined by the definition of what is, and is not, “thixotropy.” As noted by Mewis and Wagner [6], the name is derived from the Greek words θíξις (thixis: stirring, shaking) and τρéπω (trepo: turning or changing) and originally referred to a mechanically induced sol-gel transition. Since then, “thixotropy” has come to be generalized beyond a flow-induced solid-to-liquid transition to flow-induced changes in viscosity more generally. A number of more precise definitions have been given, including that by the IUPAC [8], which defines thixotropy as “the continuous decrease of viscosity with time when flow is applied to a sample that has been previously at rest, and the subsequent recovery of viscosity when flow is discontinued.” (This definition could easily be extended to the reverse phenomenon of “anti-thixotropy,” in which flow causes a reversible increase in viscosity.) As noted by Mewis [3], a focus merely on a flow-induced decrease in viscosity does not clearly distinguish “thixotropy” from nonlinear viscoelasticity, which, like thixotropy, includes shear thinning. To distinguish “thixotropy” from viscoelasticity, it is of value to define “pure” or “ideal” thixotropy [9], even though few, or even no, fluids are purely thixotropic. Recent terminology including the designation “Thixotropic Elasto-Visco-Plastic” or “TEVP” fluids [10–13] is nonredundant only if the adjective “thixotropic” is something other than some combination of elasticity, viscosity, and plasticity. Below, we make a few comments to clarify our preferred definition of thixotropy and thereby also define the scope of this review. We also discuss simple models that can show thixotropy, viscoelasticity, and more general forms of “aging” that might be relevant for glasses and soft “glassy” materials.

Microstructured materials can show various responses to various deformation history that are called “viscoelasticity,” “plasticity,” “thixotropy,” “aging,” “jamming,” “kinematic hardening,” or “elastoplastic,” “thixotropic elasto-viscoplastic,” etc. Individuals or communities focusing on different classes of materials (such as polymers, glasses, colloids, and gels) have to some degree evolved different choices of terminology that can lead to confusion. While attempting to enforce precise definitions across all disciplines would be futile, some degree of clarity is required to avoid a complete muddle. As described in the next paragraph, the rheological taxonomy used here is based on ideal, distinctive, stress-strain history relationships.

We take rheological terms to describe “ideal” responses, which are only approximated by real materials under restricted flow conditions. This is in keeping with the well-known observation that even a “solid” or a “simple liquid” such as a glass or water shows, respectively, fluidlike or solidlike responses under suitable conditions. Rheological terms are therefore most precisely deployed in constitutive equations that reflect ideal behavior. It is a matter of pragmatic judgment whether a real material’s behavior is “close enough” to the ideal to warrant a particular terminology. Whether or not a “yield stress” truly exists in real materials, it clearly does exist within various useful constitutive equations. Likewise, no material truly meets our definition of “ideal thixotropy,” but many constitutive equations clearly do.

To maintain clear distinctions, we avoid using different rheological terms to describe the same phenomenon, unless they are explicitly recognized as synonyms. Thus, we restrict the term “thixotropy” to nearly inelastic behavior so that it is not confused with “nonlinear viscoelasticity” or “viscoelastic aging.”

We take rheological nomenclature to be descriptive of responses to various homogeneous flow histories, regardless of the microstructure. Thus, “thixotropy” can describe microstructurally different materials, such as gels, colloids, and waxy oils. The restriction to “homogeneous” deformations is required because a material that becomes inhomogeneous macroscopically, for example, by banding, slipping at the wall, inertial effects, sedimentation, or transition to turbulent flow, can produce time-dependent stresses on rheometer surfaces that, without this restriction, might be called “thixotropic.” When such inhomogeneities are unavoidable, the rheology of the material under a hypothetically homogeneous deformation must be inferred, sometimes by hypothesizing an appropriate constitutive equation that, along with boundary conditions, predicts the inhomogeneous response.

While the above falls far short of resolving all issues with terminology and may not be universally accepted, at least it should help the readers understand the definitions and distinctions used here.

Viscoelasticity includes continuous, reversible, time-dependent increases and decreases in viscosity upon start-up and cessation of flow. To distinguish viscoelasticity from thixotropy, it might be appropriate to define thixotropy as “a reversible, inelastic, time dependence of the viscosity or yield stress during and after flow.” The emphasis on inelastic, or viscous, behavior separates thixotropy from viscoelasticity. Thixotropy, then, is not associated with recoverable elastic strain. While most fluids regarded as “thixotropic” possess some elasticity, a fluid can nevertheless be regarded as “thixotropic” if the elasticity is small or occurs over a much shorter time scale than the thixotropic response. The most typical thixotropic response is a slow decline of shear viscosity over hundreds of strain units, with recovery of viscosity when the shear is slowed or halted. This thixotropic response is often accompanied by a much faster viscoelastic response on start-up or cessation of flow that can be recognized as viscoelastic by either its fast, but finite, rate of stress decay on cessation of flow or by the presence of recoil, or strain recovery, on removal of stress.

Figure 1, which is from Mewis and Wagner [6], illustrates nicely, for a sudden decrease in shear rate depicted in (a), the distinction between (b) a viscoelastic response and (c) a thixotropic response. Figure 1(d) shows a combination of viscoelastic and thixotropic responses. Figure 2 [14] shows this combination in a real material: Note that after a step-down in shear rate, the stress decreases rapidly but continuously—a typical viscoelastic response to the preceding shearing. This is followed by a much slower increase of stress, which is evidently caused by the rebuilding of suspension structure once the flow rate has become slow enough to make this possible. To make clear the distinction between thixotropy and viscoelasticity, Larson [9] has defined an “ideal” thixotropic fluid as one that possess a time-dependent viscous stress only, with no elasticity or strain recovery; a similar definition of “purely dissipative thixotropic materials” was proposed earlier by Goddard [15]. In this respect, “thixotropy” is similar to essentially all other rheological properties in that rarely, if ever, does it appear in ideal form in real materials.

FIG. 1.

Distinction between viscoelasticity and thixotropy in step-down of steady shear. (a) Illustration of step-down shear-rate history; illustration of (b) viscoelastic; (c) inelastic thixotropic (aka “ideal thixotropic”); and (d) combination of viscoelastic and thixotropic responses [used with permission from Mewis and Wagner, Adv. Colloid Interface Sci. 147–148, 214–227 (2009)].

FIG. 1.

Distinction between viscoelasticity and thixotropy in step-down of steady shear. (a) Illustration of step-down shear-rate history; illustration of (b) viscoelastic; (c) inelastic thixotropic (aka “ideal thixotropic”); and (d) combination of viscoelastic and thixotropic responses [used with permission from Mewis and Wagner, Adv. Colloid Interface Sci. 147–148, 214–227 (2009)].

Close modal
FIG. 2.

Illustration of early-time viscoelastic response (before 1 s) followed by late-time thixotropic response in 2.9 vol. % fumed silica suspension after a step-down from a shear rate of 1 s−1 to the shear rates shown in the legend. Lines are model predictions [used with permission from Dullaert and Mewis, J. Nonnewton. Fluid Mech. 139, 21–30 (2006)].

FIG. 2.

Illustration of early-time viscoelastic response (before 1 s) followed by late-time thixotropic response in 2.9 vol. % fumed silica suspension after a step-down from a shear rate of 1 s−1 to the shear rates shown in the legend. Lines are model predictions [used with permission from Dullaert and Mewis, J. Nonnewton. Fluid Mech. 139, 21–30 (2006)].

Close modal

While it might be reasonable to argue that any gradual change in viscosity with time under steady flow must be associated with a deformed microstructure that retains some viscoelasticity, “thixotropy” is an appropriate term when this elasticity is “small.” As mentioned in Sec. I, this most commonly occurs when relatively rigid aggregates of particles, wax crystals, or other particles break down gradually under prolonged strain and build up again at rest. It might be of value to define more precisely how “small” the elastic response must be to allow the term “thixotropy” to be applied. We therefore tentatively propose that behavior be considered “thixotropic” if, after stress is removed, elastic recovery of less than 0.1 strain units is obtained after application of more than 10 units of strain at a rate high enough to decrease the viscosity by a factor of two or more from its value at rest or during a previous shear at a lower rate. A related requirement is that after this strain has been applied and flow is suddenly halted rather than stress removed, 90% of the stress relaxes in a time less than 10% as long as was required to impose the deformation. If both of these requirements are satisfied, then behavior commonly recognized as “nonlinear viscoelastic” would have little danger of being confounded with thixotropy. Of course, even if these conditions are not completely met by some real materials, there may be pragmatic reasons to model the material as “thixotropic” nonetheless, using an appropriate constitutive equation.

Thixotropy should also be distinguished from viscoelastic aging, such as the one that occurs in glasses. Such aging is characterized by a slow-down in relaxation during rest, which can be reversed under flow as the glass is “rejuvenated.” This response should not be regarded as “thixotropic,” for two reasons. First, viscoelastic aging occurs in an underlying viscoelastic spectrum, wherein the relaxation times themselves change with time, either increasing under rest conditions or decreasing under flow. If thixotropy is to be understood as a viscous phenomenon, then relaxation processes and their time constants are not pertinent to it. As discussed in Sec. II A, one could use the criteria of significant elastic recoil after stress removal and/or a rate of stress relaxation after cessation of flow that is comparable to or slower than the rate of change of stress after start-up of flow to determine that a material’s response is viscoelastic rather than thixotropic. If it is viscoelastic, then any aging of the material would be “viscoelastic aging” rather than thixotropic. Second, in deeply quenched glasses, viscoelastic aging occurs over an indefinite period, or, more precisely, over time scales that extend beyond practical measurement times. After deformation ceases, an aging viscoelastic fluid will relax stress very gradually and may even hold a residual stress at arbitrarily long times. A thixotropic fluid can require a long time to reach a steady-state stress after start-up of flow or change in the flow rate, but loses that stress quickly upon flow cessation. Figure 3 illustrates idealized differences among (a) viscoelastic, (b) viscoelastic aging, (c) viscous, and (d) thixotropic behavior in start-up and cessation of shearing.

FIG. 3.

Illustration of idealized forms of (a) viscoelastic, (b) viscoelastic aging, (c) viscous, and (d) thixotropic responses in a shear start-up test ( γ ˙ instantly jumps to γ ˙ 0 at t = 0 ) followed by a stress relaxation test ( γ ˙ instantly jumps to 0).

FIG. 3.

Illustration of idealized forms of (a) viscoelastic, (b) viscoelastic aging, (c) viscous, and (d) thixotropic responses in a shear start-up test ( γ ˙ instantly jumps to γ ˙ 0 at t = 0 ) followed by a stress relaxation test ( γ ˙ instantly jumps to 0).

Close modal

Note that the response shown in Fig. 3(b) as illustrative of “viscoelastic aging” might also be seen in a nonlinear viscoelastic material or an elastoviscoplastic one. Additional flow histories would be needed to determine the best rheological description of such a material. In addition, it is quite possible that multiple constitutive equations, some allowing “viscoelastic aging,” and some not, might equally well describe the material, especially if the “aging” eventually ceases.

Note that we have been careful to use the term “viscoelastic aging” to describe gradual changes in relaxation time in response to flow or its cessation. Common usage suggests that the bare term “aging” could describe any gradual change: in viscosity, modulus, or relaxation time. When it is the viscosity that ages, with relaxation times being much shorter than the time over which the viscosity changes, this can be termed “thixotropy.”

Conventional glasses as well as pastes and gels, and other materials falling under the rubric of “soft glassy” materials, need not display a well-defined rest state [16] and have usually been considered to be aging, rather than thixotropic materials. However, we will see that materials commonly regarded as thixotropic can also lack a well-defined rest state. A recent review of experimental and theoretical studies on aging can be found in Joshi and Petekidis [17]. Joshi [18] also recently developed a relatively simple free-energy-based soft glassy model with a relaxation time that can age either faster than, or slower than, the progress of time itself. In the former case, a time-dependent yield stress can develop a situation that Joshi refers to as “thixotropic.” For reasons we now discuss, we would not call this model “thixotropic” except in the limit of a relaxation time that remains short. Phenomenologically, both thixotropy and aging are characterized by one or more structure parameters that change under flow and relax at least to some extent upon flow cessation. The key difference between traditional “thixotropic” materials and “viscoelastic aging” ones such as glasses is that in the former, the relaxation time, if present at all, is short and the effects of the structure parameter on viscosity and yield stress are dominant, while in the latter, the primary influence on stress is through the relaxation time, which, if it grows rapidly enough, can produce a yield stress. In the viscoelastic aging model of Radhakrishnan et al. [19], when the Maxwellian viscoelastic relaxation time ( G 0 / η 0 ) becomes much smaller than the inverse of the structure aging time, and the shear rate remains much less than the inverse relaxation time, the model begins to resemble that of an ideal thixotropic fluid [see Eqs. (3) and (4) in [19] and Eqs. (17), (18), and (21) in Sec. V B 2]. Thus, the same model can encompass behavior ranging from nearly ideally thixotropic to viscoelastic aging. Phenomenologically, however, the key distinction we would like to maintain is that the relaxation of stress after flow cessation is slow and continues to get slower for materials that undergo viscoelastic aging, but is rapid or nearly instantaneous for a thixotropic fluid.

There are, in addition, macroscopically amorphous solids, including hard metallic glasses, and some soft pastes, whose response to stress is to yield locally either in shear bands or in local plastic zones, allowing macroscopic flow, but then freeze-in these local structures on unloading [20–23]. Such materials can behave differently in each subsequent deformation cycle, no matter how much rest time is allowed in between. The lack of change during rest disqualifies these materials from being “aging” materials, and yet the lack of a reproducible rest state makes it inappropriate to describe their time dependence as “thixotropic.” Models for such materials have been developed, including the “kinetic elastoplastic” (KEP) model of Bocquet et al. [22,23] and the “shear transformation zone” (STZ) model of Langer and co-workers [20,21].

Thixotropy is often accompanied by plasticity, i.e., a yield stress that must be exceeded to produce flow. The yield stress, how it is defined and measured either statically or dynamically, and its relationship to microstructure and to thixotropy, are discussed in a recent thorough review by Bonn et al. [24]. Recent work by Grenard et al. [25] describes time scales associated with yield stress in carbon black suspensions. Here, we simply note that when both plasticity and thixotropy are present, the yield stress is frequently sensitive to prior flow history, typically diminishing because of prior flow, but recovering a higher value after sufficient rest time. Thus, both the viscosity η and the yield stress σy of a thixotropic fluid depend on time under flow, where the viscosity augments the stress from any yield stress present. We can refer to these two manifestations of thixotropy as, respectively, thixoviscous and thixoplastic behavior. The early model of Moore [26] is a typical thixoviscous model, while the model of Nguyen and Boger [27] and the recent model of Dimitriou and McKinley [28] are examples of thixoplastic models. Most thixotropy models are both thixoviscous and thixoplastic. Real thixotropic materials typically show a yield stress, while anti-thixotropic materials are often flowable fluids at low stress that become more viscous or even solid-like during and after flow. We shall see some examples of the latter shortly.

Thixotropy is often characterized by performing transient rheological experiments in which the shear rate or stress undergoes a “step” or ideally instantaneous change. The initial fast transient response to this is usually dominated by inertial effects from the measuring instrument and testing fluid which should not be attributed to the constitutive response of the material tested. For example, in stress-start-up experiments with a Newtonian fluid, the shear rate accelerates gradually due to inertia and therefore the apparent viscosity decreases—which can be mistaken for thixotropy if care is not taken. Although some modern rheometers can make compensation for inertial effects [29], it is important to be aware of this issue.

Thixotropy has been identified in a very wide range of structured fluids, lists of which, along with references to the relevant publications, can be found in [3,6,30]. As Mewis and Wagner [6] pointed out, the term “thixotropy” is often used in a general sense to describe time-dependent shear-thinning behavior and the buildup of viscosity, yield stress, or modulus after cessation of shear flow, and some recent works still follow this convention. Thus, some of the materials described as “thixotropic” might, in fact, be better thought of as nonlinearly elastic or viscoelastic aging materials. With this caveat in mind, below is a list of fluids identified by various authors as thixotropic, drawn from the reviews described earlier:

  • Colloidal suspensions: paints, coatings, inks, clay slurries, pharmaceuticals, cosmetics, agricultural chemicals, magnetic coatings, drilling muds, metal suspensions.

  • Slurries: coal/lignite, mining slurries.

  • Nanoparticle suspensions: asphaltene-containing crude oil.

  • Emulsions: personal care products.

  • Foams: mousses.

  • Crystalline systems: waxy crude oils, waxes, butter/margarine, chocolate.

  • Polymers: associating solutions/melts, starch/gums, sauces, unsaturated polyesters, nanocomposites.

  • Fibrous suspensions: tomato ketchup, fruit pulps.

  • Biological systems: fermentation broths, sewage sludges, bloods.

Table I updates the examples given in these earlier reviews by including some new examples presented since 2010.

TABLE I.

Recent examples of thixotropic materials.

Materials Reference Remarks
Colloidal dispersions, suspensions, and gels 
Polyethylene glycol-silica gel  [31 The differentiation of stem cells can be regulated by controlling the yield stress of the thixotropic gel 
Fumed silica suspended in paraffin oil  [14,32–34 A model thixotropic fluid developed by Dullaert and Mewis [32] whose rheological behavior has been studied intensively. Several quantitative models have been proposed and compared to experimental data for this fluid 
Alumina colloidal gel  [35 A material for 3D printing 
Nanoparticle gel  [36 Shear-induced structural anisotropy gives a unique signature in large amplitude oscillatory shear (LAOS) tests 
Laponite suspension  [37 One of the few studies on squeeze flow of thixotropic suspensions 
Microgels 
Block copolymer microgel  [38 An oil-based 3D-printing support medium 
Carbopol gel  [39,40 Mostly used as a model simple yield stress fluid with no significant thixotropy. A recent study [40], however, shows that strong mechanical agitation during preparation can change its rheological behavior, suggesting that it shows thixotropy 
Emulsions 
Silicon oil-water emulsion loaded with bentonite clay  [41 The loaded emulsion is a thixotropic fluid while the normal emulsion without bentonite is a simple yield-stress fluid. The thixotropic and normal emulsions show different shear-localization behaviors 
Acrylic emulsion paint  [42 For exterior wall coatings 
Water-in-crude-oil emulsions  [43 The formation of emulsions significantly changes the rheology of crude oil, which is a challenge in drilling, producing, transporting, and processing of crude oils 
Polymeric materials 
Xanthan gum gel  [44 Used as an electrolyte in dye-sensitized solar cells 
Other examples 
Foams  [45,46 Thixotropy is important in foam stability 
Waxy crude oil  [28,47 Combined experimental and modeling studies 
Drilling mud  [48 A review on thixotropic modeling of drilling mud and crude oil 
Peptide-based organogel  [49 Self-healing material 
Cementitious materials  [50 Microstructural origin of thixotropy in cement pastes is explored 
Food products  [51–55 Examples include ketchup, mayonnaise, gums, chocolate, purees, sauces 
Human blood  [56,57 Red blood cells aggregate and form weak structures that break down under shear flow 
Grease  [58 Hydroxystearate forms large aggregates in mineral oil 
Fuels  [59 Fumed silica is mixed with propellant to form a thixotropic gelled fuel 
Materials Reference Remarks
Colloidal dispersions, suspensions, and gels 
Polyethylene glycol-silica gel  [31 The differentiation of stem cells can be regulated by controlling the yield stress of the thixotropic gel 
Fumed silica suspended in paraffin oil  [14,32–34 A model thixotropic fluid developed by Dullaert and Mewis [32] whose rheological behavior has been studied intensively. Several quantitative models have been proposed and compared to experimental data for this fluid 
Alumina colloidal gel  [35 A material for 3D printing 
Nanoparticle gel  [36 Shear-induced structural anisotropy gives a unique signature in large amplitude oscillatory shear (LAOS) tests 
Laponite suspension  [37 One of the few studies on squeeze flow of thixotropic suspensions 
Microgels 
Block copolymer microgel  [38 An oil-based 3D-printing support medium 
Carbopol gel  [39,40 Mostly used as a model simple yield stress fluid with no significant thixotropy. A recent study [40], however, shows that strong mechanical agitation during preparation can change its rheological behavior, suggesting that it shows thixotropy 
Emulsions 
Silicon oil-water emulsion loaded with bentonite clay  [41 The loaded emulsion is a thixotropic fluid while the normal emulsion without bentonite is a simple yield-stress fluid. The thixotropic and normal emulsions show different shear-localization behaviors 
Acrylic emulsion paint  [42 For exterior wall coatings 
Water-in-crude-oil emulsions  [43 The formation of emulsions significantly changes the rheology of crude oil, which is a challenge in drilling, producing, transporting, and processing of crude oils 
Polymeric materials 
Xanthan gum gel  [44 Used as an electrolyte in dye-sensitized solar cells 
Other examples 
Foams  [45,46 Thixotropy is important in foam stability 
Waxy crude oil  [28,47 Combined experimental and modeling studies 
Drilling mud  [48 A review on thixotropic modeling of drilling mud and crude oil 
Peptide-based organogel  [49 Self-healing material 
Cementitious materials  [50 Microstructural origin of thixotropy in cement pastes is explored 
Food products  [51–55 Examples include ketchup, mayonnaise, gums, chocolate, purees, sauces 
Human blood  [56,57 Red blood cells aggregate and form weak structures that break down under shear flow 
Grease  [58 Hydroxystearate forms large aggregates in mineral oil 
Fuels  [59 Fumed silica is mixed with propellant to form a thixotropic gelled fuel 

Comprehensive rheological data sets are very important in the studies of thixotropy and its modeling. In Table II, we list several representative works that provide well-defined data sets that can be used to examine constitutive models. To be included in this table, the data sets need to contain at least a steady-state flow curve, multiple transient tests such as shear-rate-jump tests, and at least one of the following features:

  1. flow protocols covering a wide range of shear histories;

  2. data in easily accessible forms;

  3. test fluids formulated in multiple compositions;

  4. different temperatures; and

  5. rheology with simultaneous local velocimetry.

TABLE II.

A summary of several representative data sets.

Materials Rheological tests References Remarks
Fumed silica suspension  Steady-state flow curve
Shear-rate jump
Multiple rate jumps
Shear reversal 
Dullaert et al. [14,32–34 Multiple formulations 
Fumed silica suspension  Steady-state flow curve
Shear rate jump
Frequency sweep
LAOS
Shear rate ramp
Shear reversal 
Armstrong et al. [60 Single formulation
Data easily accessible 
Fumed silica suspension  Steady-state flow curve
Shear-rate jump
Multiple rate jumps
Stress jump
Shear-rate ramp
Shear reversal 
Wei et al. [13,61 Single formulation
Data easily accessible 
Carbon black suspension  Steady-state flow curve
Shear-rate jump
Frequency sweep
Shear reversal
Shear-rate ramp 
Armstrong et al. [62 Single formulation 
Waxy crude oil  steady-state flow curve
Shear rate jump
LAOS 
Dimitriou and McKinley [28 Local velocimetry 
Waxy crude oil  Steady-state flow curve
Shear-rate jump 
Geri et al. [47 Multiple formulations
Multiple temperatures 
Emulsion  Steady-state flow curve
Stress jump 
Paredes et al. [41 Multiple formulations
Local velocimetry 
Carbopol gel  Steady-state flow curve
Shear rate jump 
Paredes et al. [41 Multiple formulations
Local velocimetry measurements 
Blood  Steady-state flow curve
Shear-rate jump
Frequency sweep
Shear-rate ramp 
Thurston [63], Bureau et al. [63,64 Multiple samples 
Materials Rheological tests References Remarks
Fumed silica suspension  Steady-state flow curve
Shear-rate jump
Multiple rate jumps
Shear reversal 
Dullaert et al. [14,32–34 Multiple formulations 
Fumed silica suspension  Steady-state flow curve
Shear rate jump
Frequency sweep
LAOS
Shear rate ramp
Shear reversal 
Armstrong et al. [60 Single formulation
Data easily accessible 
Fumed silica suspension  Steady-state flow curve
Shear-rate jump
Multiple rate jumps
Stress jump
Shear-rate ramp
Shear reversal 
Wei et al. [13,61 Single formulation
Data easily accessible 
Carbon black suspension  Steady-state flow curve
Shear-rate jump
Frequency sweep
Shear reversal
Shear-rate ramp 
Armstrong et al. [62 Single formulation 
Waxy crude oil  steady-state flow curve
Shear rate jump
LAOS 
Dimitriou and McKinley [28 Local velocimetry 
Waxy crude oil  Steady-state flow curve
Shear-rate jump 
Geri et al. [47 Multiple formulations
Multiple temperatures 
Emulsion  Steady-state flow curve
Stress jump 
Paredes et al. [41 Multiple formulations
Local velocimetry 
Carbopol gel  Steady-state flow curve
Shear rate jump 
Paredes et al. [41 Multiple formulations
Local velocimetry measurements 
Blood  Steady-state flow curve
Shear-rate jump
Frequency sweep
Shear-rate ramp 
Thurston [63], Bureau et al. [63,64 Multiple samples 

The microstructures and their re-arrangements under flow that lead to “thixotropy” are nicely described by Jamali et al. [12], in the context of a broad class of fluids that they designate as “thixotropic elastoviscoplastic” or “TEVP” fluids. This microstructural description not only helps identify the causes of thixotropy, but also helps distinguish thixotropy from other, accompanying, rheological phenomena. Jamali et al. [12] envision a TEVP fluid as one in which a microstructural network exists at rest, that deforms and then yields upon start-up of flow. The stresses produced prior to yielding justify the prefix “elasto” in the TEVP designation; the yielding corresponds to the “plastic” adjective; and the viscous resistance during flow justifies the designation “viscous” [65]. For some fluids, there is no need to add the further designation “thixotropic.” However, if the network breakdown under flow does not lead quickly to a final steady-state structure, but instead there are gradual changes in structure due to further breakdown or recombination of network fragments, and/or the development of spatial heterogeneities in structure, such that the macroscopic viscosity can change gradually over prolonged time periods, this warrants the additional appellation “thixotropic.” If the change in structure leads to a prolonged stress relaxation on cessation of flow and significant recoverable strain, then the term “viscoelastic aging” might be more appropriate than “thixotropic.”

Most definitions of thixotropy require that the shear-induced changes in viscosity be reversible, implying that, after a sufficient time after flow ceases, the fluid recovers a well-defined “rest state.” More precisely, the requirement is that after a long enough resting period, subsequent rheological measurements are the same as those obtained after any earlier resting period. (Since relaxation processes frequently show exponentially long tails, this requirement must be interpreted in the asymptotic sense that the difference between repeated measurements decays exponentially with prolonged rest time.) It is questionable whether real thixotropic fluids commonly satisfy this requirement. For waxy crude oils, for example, it has been suggested that changes in the fluid structure introduced by a high shear rate may be irreversible: The fluid will “remember” indefinitely the highest shear rate it has experienced [47]. For waxy crude oils, this “permanent” memory can be erased by raising the temperature to the melting point of the wax crystals, and a repeatable initial structure can then be attained by quenching under a well-defined thermal and shearing protocol [47]. Other thixotropic fluids, such as suspensions of colloidal particles, usually cannot be rejuvenated this way, and rheological results for such fluids might have significant variations in behavior from batch to batch or from one loading in the rheometer to another. In fact, one might suspect that the yield stress itself might resist the changes needed to bring the fluid back to a well-defined rest state. However, it is observed that upon rest, yield stress can build up with time suggesting that some re-arrangement of the structure is possible even when the material is below the stress needed for macroscopic flow [66]. The reproducibility of thixotropic fluids to repeated measurements or repeated preparation of the fluid from its constituents has not much been reported on, although rheological “lore” suggests that problems are common. A careful study of the reproducibility of common thixotropic fluids to repeat measurements, and repeat formulations, in the same, and different laboratories, would be a worthwhile project. In practice, lack of a rest state is often dealt with by subjecting the material to a prolonged (often hours-long) preshear to “erase” the prior loading and flow histories, prior to any rheological measurements.

As discussed elsewhere [9], it is not necessary for real materials to meet the definition of an ideally thixotropic material for the concept of thixotropy to be of value, as long as the thixotropic aspects of the fluid’s rheology can be identified. Thus, a gradual, shear-induced, change in a fluid’s viscosity that is at least partially reversed during a rest period could meaningfully be referred to as a “thixotropic” response. The lack of a complete recovery to a well-defined rest state could be attributed to other phenomena that accompany thixotropy, such as “eternal aging.” Such would be in keeping with conventional treatment of other rheological phenomena, including the concepts of “fluid” and “solid,” which are idealizations that do not exhaustively describe the rheology of any real material.

Anti-thixotropy refers to a gradual increase in the viscosity of a fluid under shear, rather than the more typical decrease. An example is shown in Fig. 4 of the viscosity as a function of time following start-up of shearing at a constant stress of 2.74 Pa for a partially hydrolyzed polyacrylamide solution in a water/glycerine mixture, studied by Buitenhuis and Springer [67]. Note that, after the initial rise in viscosity at short times up to 5 s, which is due presumably to viscoelasticity, a much later second rise occurs over the period of 20–50 s, before a modest decrease. Since strain can be calculated from the stress and viscosity, we infer that the second rise in viscosity occurs over a period of 60–150 strain units, too many to be attributed to ordinary viscoelasticity. If both the early-time viscosity, after the initial fast increase, and the long-time viscosity, after the second rise and overshoot, are plotted together for various concentrations of polyacrylamide, one obtains the results shown in Fig. 5. Note the critical shear stress above which the second, higher, viscosity first appears. This increase of stress, reflecting a flow-induced build-up rather than breakdown of structure, justifies the term “anti-thixotropic” for this fluid. The molecular origins of the flow-induced build-up of the network structure of these polymers remain mysterious. Note that this form of “thixotropy” is not accompanied by a yield stress; the viscosity does not appear to diverge at low shear stress in Fig. 5. (Or if it does diverge, it is with a very weak power law.) The gradualness of the build-up of viscosity, in units of strain, distinguishes anti-thixotropy from “jamming,” which is a more sudden shear thickening, which is sometimes discontinuous when plotted against strain rate or stress [68–71].

FIG. 4.

Viscosity against time for 1997 ppm partially hydrolyzed polyacrylamide in water/glycerine [used with permission from Buitenhuis and Springer, Colloid Polym. Sci. 281, 260–266 (2003)].

FIG. 4.

Viscosity against time for 1997 ppm partially hydrolyzed polyacrylamide in water/glycerine [used with permission from Buitenhuis and Springer, Colloid Polym. Sci. 281, 260–266 (2003)].

Close modal
FIG. 5.

Viscosity plateau values after the first (squares) and second (circles) viscosity increase versus shear stress as a function of creep stress [used with permission from Buitenhuis and Springer, Colloid Polym. Sci. 281, 260–266 (2003)].

FIG. 5.

Viscosity plateau values after the first (squares) and second (circles) viscosity increase versus shear stress as a function of creep stress [used with permission from Buitenhuis and Springer, Colloid Polym. Sci. 281, 260–266 (2003)].

Close modal

Coussot et al. [72] observed in bentonite clay suspensions the viscosity bifurcation phenomenon shown in Fig. 6. For shear stresses of 20 Pa or higher, the shear rate rises with time, a typical thixotropic response. For lower shear stresses, 12 Pa or less, the shear rate eventually collapses toward zero, either monotonically or after a period of rising shear rate. Thus, there is a minimum shear stress required for continuous flow; i.e., a yield stress. However, in contrast with simple plasticity, this yield stress depends on the rest time following a previous flow; the same applied stress can lead to either continuous flow or eventual cessation of flow, depending on the rest time [72]. Moreover, there are stresses for which the material seems to “change its mind,” initially showing an accelerating shear rate, but then collapsing to a zero shear rate. All of this is evidence of structures within the material that gradually heal at rest or are under a slow flow and can break when the flow is fast enough. This nonmonotonic behavior could possibly be explained by structures at multiple levels, some of which continue to heal even as others are breaking down during shearing at intermediate rates. As thixotropic yield stress materials are prone to banding, further studies are needed to examine the impact of shear bands on the bulk rheological response.

FIG. 6.

Shear rate versus time at the shear stresses shown for a 4.5% industrial grade bentonite suspension after a rest period of 20 s following preshearing (27 Pa, 60 s) [redrawn with permission from Coussot et al., J. Rheol. 46, 573–589 (2002)].

FIG. 6.

Shear rate versus time at the shear stresses shown for a 4.5% industrial grade bentonite suspension after a rest period of 20 s following preshearing (27 Pa, 60 s) [redrawn with permission from Coussot et al., J. Rheol. 46, 573–589 (2002)].

Close modal

Coussot et al. [72] proposed that such materials have nonmonotonic flow curves, as illustrated in Fig. 7. At a constant stress above a critical value (which itself depends on shear histories), for different initial conditions, the system either evolves toward the stable portion on the flow curve and flows continuously or evolves toward the unstable portion, which leads to flow stoppage. If structures at multiple levels are present, evolutions toward opposite directions might be present, which is likely to result in the observed nonmonotonic response of the shear rate.

FIG. 7.

Flow curve for a thixotropic yield-stress fluid, contrasted with that for an “ideal” nonthixotropic yield stress fluid [redrawn with permission from Coussot et al., J. Rheol. 46, 573–589 (2002)].

FIG. 7.

Flow curve for a thixotropic yield-stress fluid, contrasted with that for an “ideal” nonthixotropic yield stress fluid [redrawn with permission from Coussot et al., J. Rheol. 46, 573–589 (2002)].

Close modal

Viscosity bifurcations are also seen in other thixotropic fluids, such as waxy crude oils, where a viscosity bifurcation was observed by Tarcha et al. [73]. These authors found that a critical strain better characterizes the condition for structural breakdown than does a critical stress, at least for their material.

A commonly observed phenomenon associated with thixotropy and anti-thixotropy is hysteresis in curves of shear stress versus shear rate, upon ramping up the shear rate and then ramping it down, at a prescribed rate. The first report of such a hysteresis loop in viscosity appears to be that of Weltman [74]. An example of a fumed silica suspension is shown in Fig. 8 [75]. This figure shows that the stress is higher on increasing the shear rate than on the shear-rate-reduction part of the cycle. This is consistent with ordinary thixotropy, in which shear breaks down structures, leading to a reduced viscosity that does not have time to recover before the second half of the cycle occurs.

FIG. 8.

Hysteresis loops of viscosity versus shear rate of a 3% by weight suspension of fumed silica in poly(dimethylsiloxane), of viscosity 125 P at 30 °C. In each run, the shear rate was first increased up to a maximum shear rate γ ˙ max located at the arrow and then decreased. After a rest of 23 h, another run was made, with a different γ ˙ max , thus producing the series of curves shown (redrawn with permission from Ziegelbaur and Caruthers, J. Nonnewton. Fluid Mech. 17, 45–68 (1985)].

FIG. 8.

Hysteresis loops of viscosity versus shear rate of a 3% by weight suspension of fumed silica in poly(dimethylsiloxane), of viscosity 125 P at 30 °C. In each run, the shear rate was first increased up to a maximum shear rate γ ˙ max located at the arrow and then decreased. After a rest of 23 h, another run was made, with a different γ ˙ max , thus producing the series of curves shown (redrawn with permission from Ziegelbaur and Caruthers, J. Nonnewton. Fluid Mech. 17, 45–68 (1985)].

Close modal

Another example (Fig. 9), from the work of Krystyjan et al. [76], illustrates both thixotropy and apparent “anti-thixotropy” in waxy potato starch pastes. In these pastes, the stress is initially lower when the shear rate begins to decrease, but eventually is higher than that in the first half of the cycle. Thus, in this case, the shear has built up the viscosity rather than reducing it. This change in behavior occurs at the cross-over point of the shear-rate-rising and shear-rate-falling curves in Fig. 9. A similar behavior has been observed by Radhakrishnan et al. [19] and captured in a model that includes significant viscoelasticity. Thus, this behavior may be the result of viscoelasticity, rather than “anti-thixotropy.” The behavior reflects the complexity of starch, which contains associating molecules that are organized into granules that can swell, and interact with each other. The preparation of the starch, or the degree to which it has been pasted, affects the thixotropic characteristics and presumably also contributions of viscoelasticity. Note the lack of any obvious yield stress in these results, whether the fluid is thixotropic or anti-thixotropic, indicating that thixotropy need not be accompanied by a yield stress. A review of hysteresis loops in thixotropic fluids can be found in Mujumdar et al. [5].

FIG. 9.

Hysteretic flow curves for 2–5% waxy potato starch pastes prepared at 80 °C. The shear rate first increases (up-pointing arrow) and then decreases (down-pointing arrow) (redrawn with permission from Krystyjan et al., Carbohydr. Polym. 141, 126–134 (2016)].

FIG. 9.

Hysteretic flow curves for 2–5% waxy potato starch pastes prepared at 80 °C. The shear rate first increases (up-pointing arrow) and then decreases (down-pointing arrow) (redrawn with permission from Krystyjan et al., Carbohydr. Polym. 141, 126–134 (2016)].

Close modal

Thixotropic materials often show shear banding [41], in which an initially homogeneous fluid separates into layers of different shear rates under an imposed shear flow. Shear banding greatly alters the local shear histories and impacts the interpretation of the bulk rheological properties. Shear banding also potentially has a major influence on industrial applications that involve processing flows of thixotropic fluids. Fielding and co-workers [77–80] have made intensive theoretical studies of the onset and evolution of shear bands in time-dependent flows including shear start-up, step stress, rapid strain ramp, and large amplitude oscillatory shear; see [81,82] for two good reviews. Puisto et al. [83] have shown banding and stress hysteresis in down-and-up shear-rate ramps in both viscoelastic and purely viscous (i.e., thixotropic) fluids with time-dependent viscosity. A review of experimental work on banding in polymers and soft glass materials can be found in Divoux et al. [84]. Transient shear banding has been found to be a general consequence of stress overshoots on start-up or step-up of shearing [77].

A critical value of shear rate below which shear banding occurs has been reported in several materials. Paredes et al. [41] studied the banding behavior of a thixotropic emulsion and a normal emulsion, the latter of which was a simple yield stress material without thixotropy. The authors found that when wall-slip was suppressed by roughening the geometry surface, the normal emulsion did not exhibit shear banding while the thixotropic emulsion formed a banded flow when sheared below a critical shear rate. Martin and Hu [85] found such a critical shear rate in Laponite suspensions and reported that aged Laponite suspensions show transient shear banding—bands that grow shortly after shear start-up and then disappear as the fluid evolves toward a uniform shear rate. Dimitriou and McKinley [28] confirmed the existence of a critical shear rate for banded flow in waxy crude oils, below which shear bands and wall-slip velocity fluctuate irregularly at a constant overall shear rate. The recent theoretical study of Jain et al. [86] showed that inertia plays an important role in both the short-term banding dynamics in shear start-up experiments and the shear bands at steady states. In shear start-up experiments, inertia seeds heterogeneity which further grows due to inhomogeneous aging and rejuvenation. The critical shear rate determined from the constitutive flow curve alone was found to be an insufficient criterion for steady-state banding.

The study of Divoux et al. [87] provides insights into the relationship between time scales of rheology and of shear banding. The authors measured the flow curve and local velocity profile of several soft materials including both simple yield stress fluids and thixotropic fluids. In their flow protocol, the shear rate was first swept down from 10 3 to 10 3 s 1 in 90 logarithmically spaced steps of duration δ t and then swept up over the same range. Divoux et al. [87] found that both the hysteresis area in the flow curves ( A σ ) and the overall degree of banding ( A v ) depend strongly on δ t . For thixotropic materials such as laponite suspensions, A σ and A v exhibit a maximum at a critical value of δ t , as shown in Figs. 10(b) and 10(c). The authors also observed this phenomenon in mayonnaise and carbon black suspensions. This robust maximum indicates that both the bulk rheology and the banding dynamics depend strongly on an intrinsic material restructuring time. (For simple yield stress fluids such as Carbopol microgel, this time scale is very small; therefore, A σ and A v decrease monotonically as δ t increases.)

FIG. 10.

(a) Hysteretic flow curves of a 2.5 wt. % laponite suspension obtained by first decreasing the shear rate from 103 to 10−3 s−1 in 90 logarithmically spaced steps of duration 15.5 s and then increasing over the same range. Inset: velocity profile in a Couette geometry. (b) Hysteresis loop area ( A σ ) versus δ t . (c) Overall degree of banding ( A v ) versus δ t . [Used with permission from Radhakrishnan et al., Soft Matter 13, 1834–1852 (2017). Data were initially reported in Divoux et al., Phys. Rev. Lett. 110, 018304 (2013).]

FIG. 10.

(a) Hysteretic flow curves of a 2.5 wt. % laponite suspension obtained by first decreasing the shear rate from 103 to 10−3 s−1 in 90 logarithmically spaced steps of duration 15.5 s and then increasing over the same range. Inset: velocity profile in a Couette geometry. (b) Hysteresis loop area ( A σ ) versus δ t . (c) Overall degree of banding ( A v ) versus δ t . [Used with permission from Radhakrishnan et al., Soft Matter 13, 1834–1852 (2017). Data were initially reported in Divoux et al., Phys. Rev. Lett. 110, 018304 (2013).]

Close modal

Recently, Radhakrishnan et al. [19] studied this phenomenon theoretically based on the fluidity models and the soft glassy rheology model [82], which qualitatively capture the dependence of A σ and A v on δ t . According to the models, this phenomenon is triggered by the nonmonotonic underlying stationary constitutive curve and the strongly time-dependent thixotropic response.

In another recent contribution, Garcia-Sandoval et al. [88] modeled band formation in worm-like micellar solutions using a viscoelastic (upper-convected Maxwell) constitutive equation whose relaxation time and viscosity are controlled by a fluidity parameter analogous to an inverse structure parameter 1 / λ . The evolution of the fluidity is governed by relaxation and breakdown terms, similar to those in standard thixotropy models, as well as a diffusion term that penalizes gradients in fluidity. The resulting theory predicts formation and migration of bands after start-up of shear.

Very recent work by O’Bryan et al. [38] has shown that while “normal” Carbopol suspensions are simple yield-stress fluids, when stirred for a long time they can become thixotropic, and then display both banding and hysteresis in shear-rate ramps. A simple purely viscous fluidity model [similar to Eq. (18)] was able to predict the observed hysteresis.

1. Simple rate-controlled model

We start by presenting one of the simplest thixotropic constitutive equations, both in scalar and in tensor forms. For the former, we can write
(1)
Here, both the yield stress σ y ( λ ) and the plastic viscosity η ( λ ) depend on a “structure parameter” λ , whose evolution is given by a kinetic equation. The basic form of thixotropic kinetic equations was initially proposed by Goodeve and Whitfield [89]
(2)
Here, there are two kinetic coefficients, k + and k , which might depend on the strain rate, but in the simplest form are just constants. λ is usually interpreted as a conceptual measure of the degree of aggregation, bonding, or jamming. In Eq. (2), k + ( 1 λ ) accounts for the structural formation and k γ ˙ λ the breakage of internal structures. While Eq. (2) is the basic form of structure kinetics models, more complicated forms are often used for quantitative predictions of experimental data. We refer readers to previous reviews [4,6] for summaries of kinetic equations of λ . As we discuss at the end of Sec. V, some microstructure models take different approaches to model thixotropy.
The constant 1 / k + can be considered a thixotropic time constant τ thix , whose value determines how long one must wait to reach steady state after start-up of flow, or to reach a unique rest state after cessation of flow. The product Th k γ ˙ / k + = k τ thix γ ˙ is the “thixotropy number” that controls the strength of the thixotropic response in flow, with low values of Th implying weak thixotropy [5]. The solution to Eq. (2) in start-up of steady shear is
(3)
There is also a “thixotropic strain” γ thix 1 / k that must be imposed before a significant change in stress occurs. The ratio γ / γ thix therefore controls the onset of thixotropy. The ratio γ / γ thix is thus the counterpart to similar rescaled strains governing the onset of a nonlinear response in purely elastic materials, such as γ / γ e . However, in viscoelasticity, the characteristic elastic strain γ e is usually a few strain units while γ thix can be many strain units, hundreds or more.
The equation relating stress and strain rate follows the form, Eq. (1), used for plasticity. If the yield stress is exceeded, Eq. (1) can be rewritten as
(4)
However, the above form does not lend itself as well to tensor form as does Eq. (1). In the simplest case in which the yield stress and viscosity are both proportional to λ , namely, σ y ( λ ) = λ σ y 0 ; η ( λ ) = λ η 0 , a formula for the stress is easily obtained by substituting Eq. (3) into Eq. (4). A typical response to start-up of steady flow, given by these equations, is plotted in Fig. 11.
FIG. 11.

Simple thixotropic response to steady shearing as given in Eq. (4).

FIG. 11.

Simple thixotropic response to steady shearing as given in Eq. (4).

Close modal
A convenient tensor form of simple thixotropy, which is an obvious generalization of Eq. (1), is
(5)
Here, D , σ , and δ denote, respectively, the rate of deformation tensor [ D = 1 2 ( v + v T ) ], the stress tensor, and the unit tensor. σ ¯ is a scalar stress invariant that reduces to σ used in the scalar equations and is defined as
(6)
where the “:” denotes the scalar product (or double dot product) of two tensors. Also, in the above, λ satisfies an evolution equation such as Eq. (2), where γ ˙ appearing in this equation must be taken as an invariant of the rate of deformation tensor, typically given by a form analogous to Eq. (6), namely, γ ˙ 2 D : D .

2. Rate- and stress-controlled models

An important distinction in thixotropic modeling is between the strain-rate-controlled structure, in which the structure parameter λ is controlled by γ ˙ , and the stress-controlled structure, in which it is controlled by σ . For either case
(7)
where the control parameter ϕ is either γ ˙ or σ . de Souza Mendes and Thompson [7] argue that it is more reasonable to assume that the stress, rather than the strain rate, controls the structure evolution since stress is needed to break bonds in the microstructure. While the same steady-state flow curve could be obtained from either stress- or strain-rate-controlled equations, the evolution toward steady states will be different between them.
Of course, the evolution equation for λ might depend on both stress and strain rate and can in general be written as given in Eq. (8), where the first term on the right (representing “perikinetic” or Brownian motion-induced aggregation) is the relaxation term allowing the structure to rebuild in the absence of flow, the second (the “orthokinetic” term) depends on flow-induced collisions, while the third term is the flow-induced rupture term. Various forms for these terms, given in the literature, are tabulated in the review of Mewis and Wagner [6],
(8)

3. Viscosity bifurcation

The models discussed above are able to predict the “viscosity bifurcation” defined by Coussot et al. [72] and discussed above. For a fluid with a monotonically increasing stress as a function of shear rate, such as shown in Fig. 7 for the “ideal yield-stress fluid,” a viscosity bifurcation requires that the yield stress σ y ( λ ) decreases with decreasing λ . In this case, a presheared sample will flow continuously if sheared at a stress above the fully aged yield stress σ y 0 and will flow only temporarily and ultimately stop when the imposed stress is between σ y ( λ ( t = 0 ) ) and σ y 0 where t = 0 at the start of the resumption of flow. For the monotonic flow curve, the critical stress that separates continuous flow from flow that ultimately stops is independent of the resting time after preshear. If the flow curve is nonmonotonic, however, the critical stress separating continuous flow from flow that eventually stops is dependent on the rest time and the previous shear rate. The simplest thixotropic model, given in Eqs. (1)–(4), with σ y ( λ ) = λ m σ y 0 ; η ( λ ) = λ n η 0 , gives the following result for the slope of the steady-state stress with respect to shear rate,
(9)
where λ ss = 1 + ( k / k + ) γ ˙ 1 at steady state. Depending on the values chosen for the parameters, Eq. (9) can show a change in sign from positive to negative, yielding a flow curve with a negative slope in some region, which produces a critical stress for viscosity bifurcation that depends on shear history and rest time. Nonmonotonicity in the flow curve also produces shear banding along with a history-dependent viscosity bifurcation.

Coussot et al. [72] provided a very simple thixotropic model, similar to Eqs. (1)–(4), with constant coefficients, that shows a viscosity bifurcation and banding. All that is required is that the sample be insufficiently aged so that a low enough shear stress is able to allow the sample to continue to age so that its yield stress eventually exceeds the applied stress, and flow then stops. If the stress is high enough to prevent aging, then flow continues indefinitely. However, the simple thixotropic model of Coussot et al. [72] was unable to show the nonmonotonic shear rate shown in Fig. 6. A nonmonotonic shear rate under a constant shear stress could presumably be obtained if the viscosity and yield stress dependent differently on λ so that at some shear stresses the viscosity drops but the yield stress rises. This would allow the shear rate to increase initially due to the decreasing viscosity, but eventually the yield stress would exceed the applied stress and flow would stop. Perhaps, a physically more realistic way of obtaining a nonmonotonic viscosity bifurcation would be by the use of more than one thixotropy parameter, as we now discuss.

4. Models with multiple structural parameters

The above models rely on a single structural parameter λ to encode all structural information needed for rheological prediction. As might be expected, this assumption is a gross over-simplification. Just as typical viscoelastic relaxation phenomena are only crudely captured by a single relaxation time τ and a corresponding single modulus G, typical thixotropic behavior is only crudely captured by a single λ . Accurate description of viscoelasticity usually requires multiple relaxation times τ i and their corresponding weights or moduli G i , reflecting relaxation occurring on multiple structural scales. A similar consideration applies to thixotropic phenomena. The existence of multiple viscoelastic relaxation times can be revealed through a nonmonotonic response to a multiple rate-jump test, and the same test can reveal multiple thixotropic structural parameters [61] (Fig. 12). Mewis and co-workers showed that thixotropic responses to single-step-rate jumps can be represented by a stretched exponential relaxation of the structural parameter λ . They modeled this phenomenon by adding a time-dependent prefactor, t α , to the kinetic equation of λ . Their model predicts the stretched exponential thixotropic evolution in step-shear-rate tests but is not applicable in arbitrary shear histories due to the inclusion of a time-dependent prefactor t α which violates the time-invariance symmetry. In addition, this model fails to predict the nonmonotonic response following multiple jumps of shear rates because it has only a single thixotropic structure parameter.

FIG. 12.

Experimental results (symbols) and predictions of the multi-lambda ML-IKH model [lines in (b) and (c)] for the responses to multiple shear rate jumps as shown in (a). σ ( t ) denotes the stress response and σ denotes the steady-state value of σ ( t ) at γ ˙ = 5 s 1 . The value of β in the ML-IKH model is set to 0.65 in (b) and unity in (c). The dotted oval in (b) and (c) encloses the region of nonmonotonic thixotropic relaxation. Adapted from Wei et al., J. Rheol. 62, 321–342 (2018).

FIG. 12.

Experimental results (symbols) and predictions of the multi-lambda ML-IKH model [lines in (b) and (c)] for the responses to multiple shear rate jumps as shown in (a). σ ( t ) denotes the stress response and σ denotes the steady-state value of σ ( t ) at γ ˙ = 5 s 1 . The value of β in the ML-IKH model is set to 0.65 in (b) and unity in (c). The dotted oval in (b) and (c) encloses the region of nonmonotonic thixotropic relaxation. Adapted from Wei et al., J. Rheol. 62, 321–342 (2018).

Close modal
Wei et al. [61], on the other hand, assume that changes in an overall value of λ can be decomposed into a set of sub-structure parameters λ i according to
(10)
where C i is the weight coefficient corresponding to λ i , where C i is analogous to the modulus coefficient G i in a multi-mode description of viscoelasticity. The evolution equation for each λ i is
(11)
where D i is the rate coefficient of λ i , roughly analogous to the inverse relaxation time 1 / τ i of viscoelasticity, and the specific forms of f ( ϕ ) and g ( ϕ ) need to be further defined. Equation (11) guarantees that all λ i s have the same value at steady state but their time derivatives differ by the factor D i . Wei et al. [61] further chose the distribution of the thixotropic relaxation rates to approximate a stretched exponential and therefore, for a given number N of thixotropic modes used in the approximation, C i and D i are related through
(12)
where β is the stretching exponent and s is a dummy time variable. A method of finding the optimized values of C i , D i , and N for a given value of β was given by Wei et al. [61]. The important point is that, for a given level of approximation N, β is the only additional model parameter that one needs to convert a single-structure parameter model to a multiple model. When β = 1 , Eqs. (10) and (11) reduce to Eq. (7).

Figure 12 shows the rheological response of a fumed silica suspension after two jumps in shear rate separated by a time interval Δ t and the corresponding predictions of a multi-lambda model, the ML-IKH model (see Table IV for its full form, which includes elasticity and complex plasticity described later). For intermediate values of Δ t , experiments show nonmonotonic stress transients at time scales around 10 s. The ML-IKH model captures these nonmonotonic transients only when β is less than unity.

TABLE IV.

Summary of four representative scalar TEVP models.

ML-IKH model [13]: 
σ = η m γ ˙ + σ s , G σ ˙ s + max 0 , | σ eff | λ k y | σ eff | σ eff λ η thi = γ ˙ , σ eff = σ s σ back , σ back = k h A , A ˙ = γ ˙ p q A | γ ˙ p | ,  
γ ˙ p = sign ( σ eff ) max 0 , | σ eff | λ σ y λ η thi , λ = i = 1 N C i λ i , exp ( t β ) i = 1 N C i ( β ) e D i t  
d λ i d t = D i [ k 1 ϕ a λ i n + k 2 ϕ 0.5 ( 1 λ i ) + k 3 ( 1 λ i ) ] , ϕ = λ η thi | γ ˙ p |  
Model parameters : a , β , η m , η thi , G , k 1 , k 2 , k 3 , k h , n , q , σ y  
ML model [61]:
Setting G 1 and k h to zero in the ML-IKH model. The evolution equation for A ˙ is therefore absent 
IKH-V model [28]:
Setting k 2 = 0 , β , a, n, m = 1 , and replacing ( λ η thi ) with ( λ η thi + η m ) in the MK-IKH model 
MDT model [60]: 
γ = γ e + γ p , γ ˙ e = γ ˙ p ( γ e | γ ˙ p | ) / γ max , γ max = min ( γ CO / λ m , 1 ) , γ CO = σ y 0 / G 0 G ˙ f = k G ( G f λ G 0 ) , λ ˙ = k Brown [ λ | t ^ r 1 γ ˙ p | a + ( 1 λ ) ( 1 + | t ^ r 2 γ ˙ p | d ) ] , σ = G f γ e + ( λ K ST | γ ˙ p | n 2 + K | γ ˙ p | n 1 ) sign ( γ ˙ p ) Model parameters : m , G 0 , σ y 0 , k G , k Brown , t ^ r 1 , t ^ r 2 , a , d , n 1 , n 2 , K ST , K  
ML-IKH model [13]: 
σ = η m γ ˙ + σ s , G σ ˙ s + max 0 , | σ eff | λ k y | σ eff | σ eff λ η thi = γ ˙ , σ eff = σ s σ back , σ back = k h A , A ˙ = γ ˙ p q A | γ ˙ p | ,  
γ ˙ p = sign ( σ eff ) max 0 , | σ eff | λ σ y λ η thi , λ = i = 1 N C i λ i , exp ( t β ) i = 1 N C i ( β ) e D i t  
d λ i d t = D i [ k 1 ϕ a λ i n + k 2 ϕ 0.5 ( 1 λ i ) + k 3 ( 1 λ i ) ] , ϕ = λ η thi | γ ˙ p |  
Model parameters : a , β , η m , η thi , G , k 1 , k 2 , k 3 , k h , n , q , σ y  
ML model [61]:
Setting G 1 and k h to zero in the ML-IKH model. The evolution equation for A ˙ is therefore absent 
IKH-V model [28]:
Setting k 2 = 0 , β , a, n, m = 1 , and replacing ( λ η thi ) with ( λ η thi + η m ) in the MK-IKH model 
MDT model [60]: 
γ = γ e + γ p , γ ˙ e = γ ˙ p ( γ e | γ ˙ p | ) / γ max , γ max = min ( γ CO / λ m , 1 ) , γ CO = σ y 0 / G 0 G ˙ f = k G ( G f λ G 0 ) , λ ˙ = k Brown [ λ | t ^ r 1 γ ˙ p | a + ( 1 λ ) ( 1 + | t ^ r 2 γ ˙ p | d ) ] , σ = G f γ e + ( λ K ST | γ ˙ p | n 2 + K | γ ˙ p | n 1 ) sign ( γ ˙ p ) Model parameters : m , G 0 , σ y 0 , k G , k Brown , t ^ r 1 , t ^ r 2 , a , d , n 1 , n 2 , K ST , K  
A summary of key components in the four models. “Y” stands for present and “—” absent. 
Elasticity Yield stress Kinematic hardening Multiple thixotropic time scales
ML-IKH 
ML  —  — 
IKH-V  — 
MDT  —  — 
A summary of key components in the four models. “Y” stands for present and “—” absent. 
Elasticity Yield stress Kinematic hardening Multiple thixotropic time scales
ML-IKH 
ML  —  — 
IKH-V  — 
MDT  —  — 

1. Type I and Type II viscoelastic thixotropic models

de Souza Mendes and Thompson [7] described two basic methods of incorporating viscoelasticity into thixotropic viscoplastic models. In Type I models, one starts with the Bingham model, but with the yield stress written as the product of an elastic modulus and an elastic strain. One then introduces evolution equations for the elastic strain and viscosity. Some models [60] also include an evolution equation of the elastic modulus.

An example of a type I model is that of Mujumdar et al. [5]
(13)
where the evolution equation for γ e is defined as
(14)
The evolution equation for λ has a similar form as Eq. (2) with a slight modification to account for the elastic response prior to yielding
(15)
The simplest Type I models thus generalize the basic rate-controlled thixotropic viscoplastic model given in Sec. V A 1, by inserting an elastic strain prior to yielding.

In Type II models, one starts instead with a viscoelastic stress equation, such as the Jeffreys model, to which plasticity and thixotropy are introduced by replacing the model parameters with some functional forms that depend on the structural state. Figure 13 shows the mechanical analog of a family of thixotropic viscoelastic models that are based on the Jeffreys model. de Souza Mendes and Thompson [7] show an analogous schematic for Type I models. Type II models are able to incorporate a yield stress by allowing the viscosity η s ( λ ) to become unbounded at a critical level of structure η s ( λ ) . Joshi and Petekidis [17] have explored models that build up a yield stress in this way.

FIG. 13.

Type II model, according to de Souza Mendes and Thompson [7] [used with permission from de Souza Mendes and Thompson J. Nonnewton. Fluid Mech. 187–188, 8–15 (2012)].

FIG. 13.

Type II model, according to de Souza Mendes and Thompson [7] [used with permission from de Souza Mendes and Thompson J. Nonnewton. Fluid Mech. 187–188, 8–15 (2012)].

Close modal
Although in the simplest form, Type I and Type II models are distinct, either version can be expanded upon so that in more complex versions, the clear distinctions between them disappear. We can develop a unified representation for both types of models by replacing G s ( λ ) , η s ( λ ) , and η in Type II models (Fig. 13) with, respectively, G A ( s ) , η A ( s ) , and η B ( s ) , where s = ( γ e , λ ) is a vector that contains information about the structural state, namely, γ e , the elastic deformation, and λ , the overall level of the internal structure. Converting the model of Mujumdar et al. [5], Eq. (13), into this form gives
(16)
The evolution equations for γ e and λ are the same as those in Eqs. (14) and (15) for Type I models. A yield stress is introduced through Eq. (14); before yielding, γ ˙ e = γ ˙ and η A are infinite. We remind the reader of our view that if the viscoelastic elements of these models become dominant, and the thixotropic element is weak or has a time 1 / k + comparable to or shorter than the viscoelastic time constant η s ( λ ) / G s ( λ ) , then the models are better thought of as nonlinear viscoelastic models, or as “aging” viscoelastic fluids, than as thixotropic ones. We illustrate this point in more detail below by discussing “viscoelastic aging models” and the limits in which such models become “thixotropic.”

2. Viscoelastic aging models

As discussed in Sec. II B, the concept of “aging” is frequently invoked to describe slowly changing rheological properties, particularly in the field of glasses and “soft glassy” materials. In Sec. II B, we suggested that “aging” be considered as a general term that can refer to slow changes in modulus, yield stress, viscosity, or viscoelastic relaxation time. Under that definition, thixotropy would be a form of “aging” in which it is primarily the viscosity or yield stress that changes, with little, or ideally, no, elasticity present. Thus, aging of a viscoelastic material can be called “viscoelastic aging” to distinguish it from thixotropy. “Aging” can be subcategorized as “thixoviscous aging” (growth of viscosity), “thixoplastic aging” (growth of yield stress), and “viscoelastic aging” (growth of viscoelastic relaxation time). The first two of the above can be considered as forms of “thixotropy,” while the third one should not be, in our view. An additional distinction can be made between aging that finally ceases, and “eternal aging,” which does not, and for which there is no rest state. “Ideal” thixotropic materials do not age forever and have a rest state, although this situation may not be very common. If an otherwise thixotropic material lacks a rest state, it may be sensible to refer to it as an “eternally aging thixotropic” material. Under prolonged aging a material may become significantly viscoelastic, in which case we believe it would be better to call it a material with “viscoelastic aging” rather than “thixotropic.”

To illustrate this, we leave aside yield stress and discuss a simple viscoelastic Maxwell model with aging of a “Type II” form (see Sec. V B 1), motivated by a similar model in Radhakrishnan et al. [19], and show how it approaches several of the simple limits shown earlier in Fig. 3 depending on the structure and flow conditions.

Consider a simple viscoelastic model whose stress σ evolves according to
(17)
(18)
Here, τ ( λ ) = λ τ s and τ s = η / G , where η and G are constants. The evolution of λ follows Eq. (18), which is the same as Eq. (2) given earlier. This model departs from “ideal thixotropy” in that it has a finite viscoelastic relaxation time τ ( λ ) . The Weissenberg number can be defined as Wi = λ γ ˙ τ s . In the following, we define the steady-state values of λ , σ , and Wi at shear rate γ ˙ = γ ˙ 0 as λ 0 , σ 0 , and W i 0 , respectively. In a shear start-up test where γ ˙ instantly jumps to γ ˙ 0 at t = 0 , λ evolves from unity to 1 / ( 1 + T h 0 ) following Eq. (18), where again, Th k γ ˙ / k + and T h 0 k γ ˙ 0 / k + . For small T h 0 , λ remains unity and Eq. (17) reduces to a Maxwell equation
(19)
The model in this limit therefore shows a viscoelastic response as illustrated in Fig. 3(a). In this case, σ follows
(20)
where γ = γ ˙ 0 t is the strain and W i 0 = γ ˙ 0 τ s is the Weissenberg number at steady state γ ˙ 0 . Note that σ reaches its steady-state value when γ W i 0 . Consequently, as W i 0 approaches zero, σ appears to jump instantly to σ 0 , which is a viscous response, as displayed in Fig. 3(c).
For large T h 0 , the evolution of λ is significant, and Wi gradually decreases after start-up of steady shearing. Thus, the evolution of σ is then no longer a simple exponential. σ first increases and then gradually decreases with time, as depicted in Fig. 3(b). Since λ is bounded, if γ ˙ 0 τ s is 1 , Wi remains small and Eq. (17) has a pseudo-steady-state solution,
(21)
indicating an inelastic, thixotropic, response, as illustrated in Fig. 3(d).
After attaining steady state, at t = t 0 , we let γ ˙ instantly drop to zero from the previous steady-state rate γ ˙ 0 . Then, λ builds up the following simple exponential:
(22)
Along with the growth of λ , σ relaxes toward zero and the viscoelastic relaxation time, λ τ s , increases. The coupling between viscoelastic relaxation and build-up of λ results in viscoelastic aging. According to Eqs. (17) and (18), σ follows
(23)
where Θ = γ ˙ 0 ( t t 0 ) and K = k + τ s . This response, for both Wi0 and Th0 large, indicates viscoelastic aging. We do not consider this to be a “thixotropic” response since it is highly viscoelastic. T h 0 in this case can be considered to be an “aging” number. If T h 0 is small, but Wi0 is not, Eq. (23) reduces to a simple exponential
(24)
indicating a viscoelastic response, with no aging. If W i 0 and Th0 are small, σ appears to instantly jump to zero, indicating a viscous response. Thus, the model given in Eqs. (17) and (18) encompasses, in different limits, viscous, viscoelastic, thixotropic, and viscoelastic aging responses, as depicted in Fig. 3.
Because in this model, λ and therefore λ τ s are bounded, σ can fully relax. Eternal aging can be introduced by allowing λ to build up indefinitely when γ ˙ = 0 . For example,
(25)
Here, f ( γ ˙ ) is a general function that satisfies the following constraints: (1) f ( γ ˙ ) = f ( γ ˙ ) , (2) f ( 0 ) = 0 , and (3) f ( γ ˙ ) is a positive and monotonically increasing function of γ ˙ . The modification introduced in the first term of Eq. (25), dropping the factor of ( 1 λ ) , allows λ to grow indefinitely when γ ˙ = 0 . The thixotropy number can now be defined as Th f ( γ ˙ ) / k + . At a steady state, λ 0 ( γ ˙ 0 ) = 1 / T h 0 . Note that if T h 0 1 , and therefore λ 0 ( γ ˙ 0 ) 1 , the value of λ 0 is insensitive to whether the factor of ( 1 λ ) has been dropped or not. The solution for σ in this model in a stress relaxation test is
(26)
which is a power-law relaxation exhibiting a long tail. Note that if T h 0 1 and Θ is finite, Eq. (23) approaches Eq. (26), indicating that after shearing at a high thixotropic number, finite aging cannot be distinguished from eternal aging if the observation window is much shorter than the time scale of thixotropic build-up.

An eternally aging material defined in Eqs. (17) and (26) will, if one waits long enough, eventually become viscoelastic, since the relaxation time defined by τ ( λ ) = λ τ s eventually becomes large no matter how small τ s is. Thus, a material following these equations, with eternal aging, may behave as a nearly ideally thixotropic material for a long time, but eventually ages into a viscoelastic one. As we have already emphasized, pragmatic considerations, rather than fundamental ones, generally determine whether a real material should be considered a “thixotropic” or a “viscoelastic aging” one.

The above analysis indicates that even for simple models that include both viscoelasticity and aging, a wide range of responses can be obtained during start-up and cessation of shearing, making it difficult, in general, to distinguish viscoelasticity, viscoelastic aging, and thixotropy except in the limits of small or large parameter values. It was noted in earlier work [9] that nonlinear viscoelasticity can often encompass a relaxation time that grows with time following cessation of flow. For example, a simple dilute solution of nearly fully extended polymers relaxes with a relaxation time that increases with time as the polymers relax. It is questionable whether this should be called “aging,” and even more questionable to call it “thixotropy.” The above discussion did not even introduce plasticity or yield stress, which can further complicate the discussion. For example, a yield stress might be generated in a suspension containing little viscoelasticity, or in a fluid whose viscoelastic relaxation time ages nonlinearly and reaches infinity in finite time, thus leading to a solid-like response after a finite time. In the former case, the yield stresses, if dependent on prior shear, might be called “thixotropic,” while the latter might be considered as a form of “viscoelastic aging.”

Given the complexities and overlaps that easily occur in the use of rheological terms, we believe it is best to be guided by the ideal limits of the various phenomena. “Ideal” thixotropy is purely viscous or plastic, with no elasticity or recoverable strain, and eventually recovers a rest state after cessation of flow. “Ideal” viscoelasticity shows prolonged stress relaxation after cessation of flow and elastic recoil on stress removal, but the relaxation time itself (or the spectrum of relaxation times) remains constant. “Ideal” viscoelastic aging displays a relaxation rate that slows on time scales much longer than the relaxation time itself, in principle continuing to slow indefinitely. And, of course, “ideal” viscous fluids show instantaneous attainment of steady stress after start-up of shear, instantaneous loss of stress after cessation of shear, and no elastic recovery on stress removal. These four ideal responses are illustrated in Fig. 3. Real materials often at best only approximate these behaviors, and sometimes do so only for limited ranges of strain rates and times. Hence, it may be better to refer to viscoelastic or thixotropic “responses” rather than “materials,” as the same material may display quite different behavior depending on conditions of the experiment. To avoid confusion or redundancy in terminology, we believe it is important to hold firmly to the definition of an “ideal” thixotropic material as one that is completely inelastic, although time dependent. Even if real materials refuse to comply with this definition, at least we can be guided by a clear definition of the ideal case. And even if viscoelasticity inevitably accompanies thixotropy, there are pragmatic reasons one might want in some situations to model only the thixotropic aspects of the response and ignore the viscoelastic. For one, nonlinear viscoelasticity is notoriously difficult to model, and thixotropy comparatively easy, especially in three-dimensional flows.

Earlier, we defined “ideal thixotropy” as a flow-history dependence of viscosity and yield stress, but without any elasticity, and illustrated it with a simple constitutive equation involving a Bingham yield stress. The Bingham law of plasticity, even when we allow for a yield strain as described in “Type I” models in Sec. V B 1, is typically too simple to describe in detail the plastic response of real materials, especially in complex flow histories. So, to go beyond both “ideal thixotropy” and “Type I” and “Type II” models of TEVP materials, we will first describe briefly more advanced concepts from the theory of plasticity, including the Bauschinger effect and kinematic hardening, and then show how these can be incorporated into more realistic constitutive equations for thixotropic materials. Inevitably, the introduction of advanced concepts of plasticity will bring consideration of elastic effects, which will lead us to beyond “ideal thixotropy” to equations describing TEVP fluids. Note that kinematic hardening is an important subject of study in the plasticity field that mainly focuses on compressive and tensile deformation of metallic materials. Dimitriou et al. [28,90] showed that kinematic hardening is also an important rheological response in soft TEVP materials under shear deformation and the previous scalar kinematic hardening equations can be conveniently used in shear flows. The recent simulation studies by Fraggedakis et al. [91,92] demonstrate the necessity of sophisticated TEVP models in flows with complex kinematics.

The Bauschinger effect is the change in the yield stress as a result of strain history. Perhaps, the most common example is the decrease in the compressive yield stress of a material as a result of an increase in the tensile yield stress due to a prior tensile strain; see Fig. 14. The increase in yield stress in the original straining direction with a consequent decrease in the opposite direction is known as kinematic hardening [93]. (In isotropic hardening, the yield stress increases in all directions upon straining in one direction.) Thus, kinematic hardening is a shift of the yield surface in the direction of the most recent straining, so that when the strain is reversed, the yield stress in the opposite direction is temporarily reduced. Upon continued straining in the opposite direction, hardening eventually occurs in that direction as well. This phenomenon was discovered in polydomain solids, such as metals, for which strain-induced orientation of grains leads to an increase in yield stress in the direction of the straining, but a decrease in the opposite direction, which is revealed once the strain direction is reversed.

FIG. 14.

Illustration of “Bauschinger effect” wherein the yield stress magnitude changes upon reversal of shearing. Upon shear start-up, a first yield point is reached at σ y , followed by a continued rise in stress, post-yield, due to “hardening,” or an increase of the yield stress. This increase in yield stress in the flow direction, usually denoted as σ back , is revealed to be direction dependent when the strain direction is reversed, and the yield stress in opposite is found to be smaller in magnitude than σ y .

FIG. 14.

Illustration of “Bauschinger effect” wherein the yield stress magnitude changes upon reversal of shearing. Upon shear start-up, a first yield point is reached at σ y , followed by a continued rise in stress, post-yield, due to “hardening,” or an increase of the yield stress. This increase in yield stress in the flow direction, usually denoted as σ back , is revealed to be direction dependent when the strain direction is reversed, and the yield stress in opposite is found to be smaller in magnitude than σ y .

Close modal

1. Modeling of kinematic hardening

A simple scalar model that accounts for this phenomenon, taken from the Fredericks-Armstrong model [94], is given below
(27)
where σ eff = σ σ back and γ ˙ p is the so-called plastic strain rate, which differs from the total strain rate by the elastic strain rate, γ ˙ p γ ˙ γ ˙ e . (“Strain rate” should be replaced with “shear rate” in simple shear flows.) Here, σ back is the additional direction-dependent back-stress needed to overcome the yield stress during straining. A simple elastic constitutive equation for the back stress is the linear relationship
(28)
where A is the “back strain” and C is therefore the modulus associated with the back strain. A simple constitutive equation for the back strain is
(29)
The first term in the above produces a linear growth of A with the plastic strain γ p , while the second leads to a negative exponential approach to saturation; i.e., A = [ 1 exp ( q γ p ) ] / q . If we neglect the elastic strain γ e , then under a constant strain rate γ ˙ , the stress according to the above model is given by
(30)
where σ y and η would depend upon λ if thixotropy were to be included in the model.

Figure 15 shows mechanical models that include the yield stress, back stress, and an elastic stress, in various combinations, but that omit the viscous stress η γ ˙ p (Table III). The behavior of each of these models in periodic reversing shear flow is shown in Fig. 16. The behavior of Eq. (30) (with η  = 0), namely, C [ 1 exp ( q γ p ) ] / q + σ y , is represented by the initial start-up segment of Fig. 16(c), beginning at zero strain and stress σ y and continuing onto the plateau region σ y + C / q .

FIG. 15.

Schematics of four simple elastoplastic models constructed by setting selected parameters of the model in Table III to be zero: (a) C , η = 0 ; (b) σ y , η = 0 ; (c) G 1 , η = 0 ; (d) η = 0 .

FIG. 15.

Schematics of four simple elastoplastic models constructed by setting selected parameters of the model in Table III to be zero: (a) C , η = 0 ; (b) σ y , η = 0 ; (c) G 1 , η = 0 ; (d) η = 0 .

Close modal
FIG. 16.

Rheological responses of the four models shown in Fig. 15 under periodic reversal shear flows.

FIG. 16.

Rheological responses of the four models shown in Fig. 15 under periodic reversal shear flows.

Close modal
TABLE III.

Summary of an elastoviscoplastic model.

Equations Remarks
σ ˙ G + max 0 , | σ eff | σ y | σ eff | σ eff η = γ ˙   Maxwell-type equation for stress evolution 
σ eff = σ σ back   Effective stress that drives plastic flow 
σ back = C A   Definition of back stress 
γ ˙ p = sign ( σ eff ) max 0 , | σ eff | σ y η   Flow rule for the plastic shear rate 
A ˙ = γ ˙ p q | γ ˙ p | A   Evolution equation for A 
Model parameters: G, η , σ y , C, q  
Equations Remarks
σ ˙ G + max 0 , | σ eff | σ y | σ eff | σ eff η = γ ˙   Maxwell-type equation for stress evolution 
σ eff = σ σ back   Effective stress that drives plastic flow 
σ back = C A   Definition of back stress 
γ ˙ p = sign ( σ eff ) max 0 , | σ eff | σ y η   Flow rule for the plastic shear rate 
A ˙ = γ ˙ p q | γ ˙ p | A   Evolution equation for A 
Model parameters: G, η , σ y , C, q  

Note that the back stress introduces a dependence of stress on “plastic strain” γ p . We put “plastic strain” in quotes because this dependence on strain introduces elasticity into the equation. This can be seen by suddenly reversing the direction of shearing flow in the above model. If the strain prior to this was small enough to use the linearized version of Eq. (30) (for small γ p ) , then the stress will remain initially positive when γ ˙ p changes sign (as long as γ ˙ p is smaller in magnitude than σ y / η ), as γ p then gradually decreases in magnitude. The decreasing positive stress during reverse straining is a recoil phenomenon from which work might be extracted, unless it is blocked by the yield stress. Hence, the back strain is a form of elasticity, despite the label “plastic” attached to the strain γ p . The nonlinearity within the general expression 1 exp ( q γ p ) is not elastic, as it arises from the term q A | γ ˙ p | in Eq. (29), which is irreversible owing to the dependence on the absolute value of the strain rate. Thus, kinematic hardening introduces elasticity into plasticity theory and should be considered as a theory of elastoplasticity, rather than of plasticity alone.

A particularly simple case to consider is that of negligible yield stress σ y and negligible viscous stress η γ ˙ p either because of small-strain rate or small viscosity. In this case, the resulting hysteretic stress-strain relationship is shown in Fig. 16(b). This limit shows that the back stress contribution stores elastic energy, which can be partially extracted upon flow reversal. Figure 16 also shows the effect of inclusion of a yield stress σ y to the shear and reversal predictions, both without a yield strain [Fig. 16(c)], and with it [Fig. 16(d)]. The corresponding mechanical models are shown in Figs. 15(c) and 15(d). Note that the inclusion of a high enough yield stress (without a yield strain) changes the slope of the stress-strain curve during flow reversal from finite [Fig. 16(b)] to infinite [Fig. 16(c)], implying that the recovery of elastic work in Fig. 16(b) is lost when the yield stress is high, as in Fig. 16(c).

In addition to the elasticity arising from kinematic hardening, which reveals itself after plastic flow begins, there is normally at least a small elastic response prior to yield. For solids, this is typically expressed as a reversible Hookean stress-strain relationship, producing fully recoverable strain γ e if the yield stress is not reached. If this Hookean elastic stress with a maximum yield strain γ y is added in series to the Bingham viscous model (as in “Type I” models discussed in Sec. V B 1), a simple elastoplastic constitutive equation results, whose recoverable strain beyond the yield point is just the yield strain. This is shown in the mechanical model in Fig. 15(a), and the corresponding cyclic stress-strain curve is shown in Fig. 16(a). [When the back stress is also added, the model and its stress-strain curves are shown in Figs. 15(d) and 16(d).] The stress can be made to relax if it is governed by a Maxwellian form [95]
(31)

2. Demonstrating kinematic hardening in thixotropic fluids

The existence of kinematic hardening in thixotropic suspensions is demonstrated in reversing flows, the simplest of which is a reversal in the direction of steady shear after steady state has been attained in unidirectional shear. Figure 17 shows the stress evolution after such a reversal for a fumed silica suspension for a range of shear rates, where the straining prior to reversal is arbitrarily taken to be in the negative direction so that the final shear direction is positive. Figure 17 should be compared with the left-most leg of the schematic stress-strain curve in Fig. 16(d), where the negative straining direction is suddenly reversed to straining in a positive direction. Thus, the steep part of the curve with slope G and negative stress in Fig. 16(d) corresponds to the steep initial portion of the curve in Fig. 17, with negative stress. The portion with positive stress and a less steep slope in Fig. 16(d) corresponds to the portion of the curves in Fig. 17 with positive stress. In Fig. 17, the response at small strains after reversal is thus primarily elastic, with the negative stress from the initial shearing transitioning to positive stress as the small amount of elastic strain (<0.1, or <10%) is removed from the sample. [This small-strain elasticity is described in Eq. (31).] Shortly thereafter, a “knee” appears in the response, corresponding roughly to the point of yield of the sample in the positive direction, after which the stress initially grows more slowly with strain. This yield stress after reversal is lower in magnitude than the yield stress required to initiate plastic strain upon start-up after a long period of rest, consistent with a combination of a reduced isotropic yield stress and a shift of the yield surface toward the direction of the previous strain. That the yield surface has indeed shifted is indicated by the significant rise in the slope of the stress versus log strain at a strain of around unity, consistent with a reversal of the back strain from a negative value creating by the prior flow to a positive one created by the continued straining in the positive direction. [This rise in slope after the knee shows up when stress is plotted against log strain; when plotted against linear strain, the result is shown in the inset of Fig. 17 and resembles closely the left leg of the stress-strain cycle in Fig. 16(d).] Once the back strain has reversed sign and come to steady state, it ceases to increase, and the stress quickly levels off to a constant value (albeit higher than in the absence of kinematic hardening), consistent with the attainment of a steady-state back stress. From a microstructural point of view, back strain represents an orientation of elements of the material, causing resistance to yielding to increase. By the same token, this orientation stores elastic energy that might be partially recovered, depending on the magnitude of the viscosity and yield stress. We emphasize that the existence of kinematic hardening in the thixotropic fluid described in Fig. 17 is clearly revealed in the shape of the stress-strain curve (i.e., the “double plateau” on a semilog plot, the first due to yielding and the second to kinematic hardening) after reversal of the straining direction.

FIG. 17.

Stress-strain relationship during first flow reversal in a fumed silica suspension. Symbols, experimental results; lines, predictions of four TEVP models labeled in the figure and listed in Table IV. Inset shows the experimental data for the first three strain units on linear-linear axes, where the contributions to the stress from the yield stress (2 σ y ) and from kinematic hardening (C/q) are identified [redrawn from Wei et al., J. Rheol. 62, 321–342 (2018)].

FIG. 17.

Stress-strain relationship during first flow reversal in a fumed silica suspension. Symbols, experimental results; lines, predictions of four TEVP models labeled in the figure and listed in Table IV. Inset shows the experimental data for the first three strain units on linear-linear axes, where the contributions to the stress from the yield stress (2 σ y ) and from kinematic hardening (C/q) are identified [redrawn from Wei et al., J. Rheol. 62, 321–342 (2018)].

Close modal

We note that addition of details such as back stress greatly complicates the modeling of thixotropy, especially in full tensor theories, and the improvement thereby gained is mainly in providing better predictions in more complex flow histories at relatively small accumulated strain following changes in the flow direction. In many cases of industrial importance, the improved predictions (which are still by no means quantitative) may not be worth the greatly increased complexity of the equations and the numerical expense of solving them. Still, with increasing computer power, inclusion of more accurate modeling of plasticity may become increasingly common, even for industrial applications. We also note that full tensor forms of Eqs. (27)–(31) are available in the literature [13,90], but not presented here, owing to their complexity. Table IV provides a summary of the scalar models used for the predictions in Fig. 17.

1. Populational balance models

Thixotropy is caused by reversible structural breakage under flow and its buildup when flow decreases or stops. Structural kinetics models (SKMs) described above capture these physics phenomenologically through one or more structure parameters and corresponding evolution equations. While some models of this kind predict experimental data well, they provide no clear information about the microstructures; the structure parameter is only conceptually related to the microscopic structural state. Population balance models (PBMs), however, take account of the flow-induced changes of the size distribution of microstructures and the impact of these changes on the bulk rheology. PBMs have long been used to model aggregation and fragmentation kinetics in colloidal dispersions. Many PBMs belong to the category of ideal thixotropic models but they focus mainly on the dynamics of aggregate mass distribution instead of the rheological properties. Recent years have seen growing interest in constructing quantitative thixotropic constitutive models from PBMs [96,97]. Here, we briefly review the framework of PBMs and discuss their connections with SKMs.

In suspensions, colloidal particles aggregate and form fractal structures over a wide range of length scales. PBMs take a mean-field description of the structural state by considering only the number density distribution of aggregates of different mass. PBMs are constructed based on the principle of mass conservation—a floc of mass x can stick to one of mass y and form a larger floc of mass x + y . (Following conventions, the primary particle or cluster has unit mass.) This process can be represented as x , y x + y . The rate of this coagulation process is assumed to be proportional to the number density of flocs of mass x and y, n ( x , t ) and n ( y , t ) . The rate coefficient is often described by a collision kernel K ( x , y ) that is a positive and symmetric function of x and y. The collision kernel accounts for the effects of flow, the Brownian motion, and other interactions among particles. PBMs usually do not consider coagulation events that involve the simultaneous collision of three or more flocs.

Large aggregates can break into smaller ones under flow, which can be represented as x y , x y . This rate of this breakage is usually assumed to be proportional to n ( x ) , with a rate coefficient B ( x ) determined by x, the flow condition, the fractal dimension, and other parameters. A breakage distribution function P ( y / x ) that depends only on the ratio of the final to the starting floc size y / x is usually included to describe the mass distribution of the fragments. A simple example is the binary breakage—a larger aggregate always breaks into two smaller flocs of equal size:
(32)
where δ ( x ) is the Dirac delta function.
Reactions of the forms x y , y x and x + y x , y lead to an increase of n ( x , t ) and reactions of the form x , y x + y and x y , x y lead to its decrease. The evolution equation for n ( x , t ) therefore can be written as
(33)
To evaluate Eq. (33), one needs the functional forms of K ( x , y ) , B ( x ) , P ( a ) , n ( x , t ) , and the relationship between n ( x , t ) and some bulk rheological properties such as the viscosity η ( t ) . K ( x , y ) is usually additively decomposed as K ( x , y ) = K B ( x , y ) + K S ( x , y ) , where K B ( x , y ) and K S ( x , y ) account, respectively, for the aggregation induced by the Brownian motion and for shear flow. There are two well-accepted forms for K B ( x , y ) . According to Smoluchowski [98],
(34)
where k B is the Boltzmann constant, T is the temperature, η 0 is the medium viscosity, W is the Fuchs stability ratio, α is an exponent, and D f is now recognized as the fractal dimension. When W = 1 and α = 0 , Eq. (34) reduces to the diffusion-limited aggregation kernel. The power of 1 / D f appears here because the characteristic of fractal aggregates is proportional to d p x 1 / D f , where d p is the diameter of primary particles.
A widely used functional form for the shear-induced aggregation kernel K S ( x , y ) [98] is
(35)
where r p is the radius of the primary particle or cluster, κ is the collision coefficient, and γ ˙ is the shear rate.
The breakage kernel B ( x ) is usually assumed to be a decreasing function of D f and an increasing function of x and the flow intensity. (Aggregates with larger size and under more intensive flows break more easily. Aggregates with smaller D f are more porous and thus break more easily.) The breakage kernel usually takes an exponential or power-law functional form [99–105]. For example, in the work of Barthelmes et al. [105],
(36)
where b 0 is the breakage rate coefficient, σ 0 is the characteristic stress, and q is the exponent. PBMs as applied to thixotropic fluids have generally been limited to mostly ideal thixotropic models in which
(37)
where ϕ tot is the effective total volume fraction of the aggregates,
(38)
η ( ϕ tot ) usually takes a similar empirical functional form as dense colloidal suspensions. For example, in the work of Quemada [106],
(39)
where ϕ m is the volume fraction at which the viscosity diverges to infinity.

As discussed previously, to evaluate Eq. (33), one needs the functional form of n ( x , t ) , which describes the mass distribution of aggregates as a function of time. Such descriptions rarely have an analytic form and a precise numerical description is mostly impractical as the aggregates contain an enormous number of primary particles. A widely used technique to cope with this complexity is to discretize the aggregate mass distribution into as many bins as is convenient according to, for example, a geometric progression, and to replace the integrals with summations. Equation (33) is thus converted to a system of differential equations. Figure 18, adapted from the work of Barthelmes et al. [105], shows an example of such sectional PBMs. This study does not consider Brownian aggregation. The growth of clusters is due to the shear flow.

FIG. 18.

Prediction of a PBM: evolutions of (a) the relative viscosity and (b) aggregate size distribution at a constant shear rate (10 s−1) from a fully unstructured state. (a) shows the predictions for three different values of volume fraction of primary particles. (b) shows the results for ϕ 0 = 0.01 only. Adapted with permission from Barthelmes et al., Chem. Eng. Sci. 58, 2893–2902 (2003).

FIG. 18.

Prediction of a PBM: evolutions of (a) the relative viscosity and (b) aggregate size distribution at a constant shear rate (10 s−1) from a fully unstructured state. (a) shows the predictions for three different values of volume fraction of primary particles. (b) shows the results for ϕ 0 = 0.01 only. Adapted with permission from Barthelmes et al., Chem. Eng. Sci. 58, 2893–2902 (2003).

Close modal

Figure 18(a) shows the simulation results for the evolution of relative viscosity, η r , for three suspensions of different levels of primary particle volume fractions, ϕ 0 , in constant shear-rate tests ( γ ˙ = 10 s 1 ) starting from a fully unstructured state. η r ( t ) exhibits a sharp “S-shaped” form, where the sharp upturn of η r ( t ) is due to the appearance of large aggregates, as shown in Fig. 18(b). Thus, Fig. 18 deals with shear-induced structure build-up, leading to a shear-induced increase in the viscosity. The modeling could readily be extended to include Brownian motion and shear-induced structure breakdown, which is a more typical thixotropic phenomenon.

Another technique to simplify PBMs is to coarse-grain Eq. (33) and derive evolution equations for a few dynamical variables that are quantitatively related to the aggregate size distribution. The work of Azikri De Deus and Dupim [96] and that of Mwasame et al. [97] are two representative examples. They use the k th moment ( k = 3 in [96] and 0 in [97]) of n ( x , t ) as the structure parameter and derive its evolution equation based on the aggregation and fragmentation kinetics. Coarse-graining greatly reduces the computational requirements of PBMs at the cost of losing information about the aggregate mass distribution. The coarse-grained PBMs are mathematically similar to the “lambda-type” SKM thixotropic models described earlier but they are constructed based on a quantitative physical description of the microstructures. Another major advantage of PBMs over SKMs is that PBMs, once parameterized for a suspension at a certain concentration of particles, are applicable at different particle fractions. SKMs, however, need to be reparameterized when the suspension contents are changed.

One major challenge of constructing constitutive models from PBMs is to predict quantitatively the complex rheological response of thixotropic fluids which involves viscoelasticity, kinematic hardening, isotropic softening, etc. Information about the elastic deformation and orientation of aggregates must be incorporated in PBMs to quantitatively capture the TEVP rheology. The recent work of Mwasame et al. [97] is such an example where the authors adopt similar approaches as those in SKMs to incorporate elasticity and yield stress. Still lacking is a TEVP model that is based on a microstructural description of the deformation, orientation, and size distribution of aggregates.

In summary, thixotropic materials show complex rheological properties due to rich dynamics of the internal structures. Under flow, the microstructures deform, break, align, or grow. PBMs adopt a mean-field approach to describe the dynamics of aggregate mass distribution and its impact on rheological properties. Most PBMs focus mainly on the dynamics of aggregate size distribution instead of rheological properties. Constructing quantitative rheological models based on PBMs is a promising approach to develop microstructural thixotropic models.

2. Simulations of thixotropic response

As far as we are aware, the only microstructural simulation of a thixotropic response so far is the recent dissipative particle dynamics (DPD) simulations of the response of a particulate gel suspension to shearing flow, by Jamali et al. [12]. The response of this gel to shearing flow is illustrated in Fig. 19, which shows the shear component and the trace of the “fabric tensor” Z, which is the average of the dyad formed by the unit vectors connecting neighboring bonded particles in the structure. The trace of Z, trZ, is the average coordination number of the network, while the shear component gives the anisotropy in the x-y plane, where x and y denote the flow and gradient directions, respectively. Note that the network structure under shear can be both enhanced (increased trZ) and degraded (decreased trZ) depending on the shear rate and strain level and that the changes in the network structure occur over large strains, up to 100 strain units and beyond. The large strains over which changes continue to occur is a hallmark of a thixotropic response, as opposed to a viscoelastic one for which changes are generally confined to a few, or at most a few tens of strain units, before steady state is reached.

FIG. 19.

(a) Shear component and (b) trace of the fabric tensor (equal to particle coordination number) in flow start-up simulations, for different shear rates. Insets show the representative microstructures in different flow regimes [used with permission from Jamali et al., Phys. Rev. Lett. 118, 048003 (2017)].

FIG. 19.

(a) Shear component and (b) trace of the fabric tensor (equal to particle coordination number) in flow start-up simulations, for different shear rates. Insets show the representative microstructures in different flow regimes [used with permission from Jamali et al., Phys. Rev. Lett. 118, 048003 (2017)].

Close modal

We have reviewed the experimental, theoretical, and computational literature on thixotropic fluids, especially recent developments. Thixotropic phenomena in their simplest form are purely viscous and can be described by a model with a viscosity and yield stress that are functions of a phenomenological “structure parameter” λ , whose evolution is controlled by strain rate and time. While such models have existed for 50 years, and capture thixotropy at its most basic level, there are several major limitations. First, the basic model is purely phenomenological and can only be specified by fits to simple flow histories, such as shear step-up, step-down, and reversing. While fits may work for these histories, drastic deviations may occur outside of the range for which fits were obtained. Second, the basic model is a scalar theory. Although it can be extended to a three-dimensional description by use of simple invariants in place of shear stress and strain rate, the almost complete absence of rheological measurements for flows other than shear make such extensions untested and of doubtful reliability. If the constitutive equation were based on a realistic microstructural model, one might have some confidence that extension to general flows would be reasonable, but with only phenomenology and shear data as guidance, the success of any such extension would be fortuitous.

A third limitation of the simple ideal models is in their dependence on a single scalar structure parameter, relaxing exponentially to equilibrium when flow ceases. Real materials typically show multi-exponential behavior, sometimes well represented by a stretched exponential. A fourth limitation is the over-simplicity of the Bingham yield law, which lacks dependence on the orientation of the current flow direction relative to past flow directions, and thus an inability to capture kinematic hardening. A fifth limitation is the neglect of elastic effects, such as recoil or stress relaxation after flow cessation. A sixth limitation is its assumption of relaxation to a well-defined rest state after cessation of flow. Thixotropic materials are often dependent on the use of preshear, heating and quenching, re-loading fresh samples, and other methods of restoring a well-defined starting state for rheological measurements.

Some of these limitations have now been addressed in recent thixotropic models, especially the recent TEVP models. These typically combine more complex plasticity models as well as viscoelasticity, with thixotropy, to describe complex rheological phenomena, including kinematic hardening, finite yield strain, and stress relaxation, with history-dependent viscosity and yield stress. In addition, the use of multiple structural parameters λ i , for example, based on a stretched exponential structural relaxation, allows the models to capture significantly more complex rheological phenomena, such as nonmonotonic response to step-up or step-down flow histories.

Despite this dramatically rapid progress in recent years, yawning chasms in understanding remain. These include the shortage of comprehensive data sets, lack of cross-evaluation of available models against various data sets, and the rarity of measurement of velocity profiles during rheometry. Most rheological studies focus on a very limited range of shear histories, formulations, and test conditions such as temperature. Most models are only examined against the data from a single fluid, despite the recent efforts [13,60,62,97] that involve thorough comparisons of multiple models. Besides, most studies present only bulk rheological data while recent results indicate that many, and perhaps even most, thixotropic fluids do not shear homogeneously, and not only do shear bands form, but these bands migrate and even disappear and re-appear. Such behavior, if common, means that many rheological measurements of thixotropic phenomena are incomplete or even misleading, since they represent at best an average rheological response, and do not necessarily apply to local fluid elements. Moreover, such banding behavior, if realized in commercial processing flows, would mean that the fluid may become highly nonhomogeneous in its flow history and hence in its structure, with implications for product quality.

Another huge gap is the almost complete lack of data in nonviscometric (i.e., non-shear) flows. Without extensional or mixed flows, we remain ignorant of thixotropic behavior in anything other than various versions of shearing flow. Yet another severe deficiency is the primitive state of microstructural models, which could make the study of thixotropy less phenomenological and more physical. The beginnings of microstructural modeling are underway, with the development of PBMs of thixotropic suspension structures, and with simulations of such structures using mesoscale models such as DPD just emerging. But testing and improving such models require comparing predicted with measured microstructures, and this seems yet to begin in earnest.

Thus, the greatest gaps, and the greatest priorities, for future work are in the measurements of thixotropic behavior in nonviscometric flows, the imaging and quantification of flow fields simultaneously with rheological measurements, the development of simulations of thixotropic microstructural and rheological responses using population balance and mesoscale simulations, and comparison of both these against experiments.

Not surprisingly, the highest priorities are in the most difficult areas; namely, in measurements of structures and flow fields, including nonviscometric ones, and in advanced simulations. Thixotropic constitutive equations are now developed to a point that a surge on the experimental and computational fronts is necessary for further progress. Most needed now are the data to test, invalidate, and improve the models already available, before there might be good reasons to develop new ones. A prime reason for the complexity of the problem is that thixotropy rarely appears in isolation from other complex phenomena, such as plasticity, viscoelasticity, and aging. While this complexity creates great challenges, it also means that the study of thixotropic phenomena remains an exciting frontier even a century after its inception.

The authors gratefully acknowledge the careful reading and many helpful comments by Suzanne Fielding as well as by Yogesh Joshi. R.G.L. is grateful for funding from the National Science Foundation (NSF) under Grant No. CDS&E-1602183. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

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