Abstract
This manuscript is based on an oral contribution to the TMS 2020 annual meeting and is dedicated to Prof. Peter Liaw, who for decades has shown great interest in serrated plastic flow. Here we will focus on the case of bulk metallic glasses, and begin with briefly summarizing some aspects of serrated and nonserrated inhomogeneous flow—a phenomenon that has perplexed materials scientists for decades. Four directions of research are identified that emerged out of the desire to fundamentally understand the intermittent inhomogeneous flow response. These research directions gear away from the phenomenological stress–strain behavior but put the underlying shear defect into focus. Unsolved problems and future research topics are discussed.
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1 Introduction
In the early two thousands, the topic of serrated versus nonserrated flow in bulk metallic glasses (BMGs) experienced a second wave of interest following the remarkable initial work by Kimura and Masumoto presented more than 20 years earlier.[1,2,3] Kimura and Masumoto recognized that the appearance of plastic flow in BMGs at low homologous temperatures (the inhomogeneous deformation regime) can be either smooth or intermittent, depending on the applied deformation rate and/or deformation temperature. In essence, this is phenomenologically very similar to dynamic strain aging of, for example, steels[4] or AlMg alloys,[5] where the interplay between depinning of dislocations and the retrapping of them by solutes gives rise to the socalled jerky flow curves for particular combinations of the deformation rate and testing temperature. In fact, our recent efforts suggest that intermittent singlecrystal microplasticity is another manifestation of a rather generic coupling between the farfield rate and some underlying deformation kinetics.[6] In this latter case, crystallographic slip is governed by the collective dislocation velocity during the dynamic (also referred to as an avalanche) deformation phase. Whilst the macroscopic emergence of the stress–strain response has some similarities in all these cases (metallic glasses, dynamic strain aging, single crystal microplasticity), the underlying physics is clearly different.
Kimura and Masumoto established via tearing, bending, and compression testing of BMGs across different temperatures that two regimes appear in an extension rate vs. \( 1/T \) representation. At constant applied deformation rate, serrated flow was observed at higher temperatures, and at lower temperatures nonserrated flow occurred. The border between the regimes decreased in temperature with decreasing applied rate, and a simple Arrhenius relationship captured this trend, with effective barrier energies that were alloy specific and in the range of 0.3 to 0.5 eV. These efforts did not only reveal the thermallyactivated nature of inhomogeneous flow of metallic glasses, but also included a detailed mechanical understanding on how both sample and mechanical compliances affect the serration amplitude.[3]
About 25 years later and driven by the desire to fundamentally understand the (micro)structural mechanisms during strain localization (shear banding) of metallic glasses, the transition from serrated to nonserrated flow received renewed attention. With the vision of finding structural parameters or properties that potentially could improve the plastic strain prior to failure, fundamental work focused on questions related to shearband nucleation dynamics,[7,8,9] how shear advances (front propagation or sheardisplacement jump),[10] the duration of shearband propagation,[11,12,13,14] or heat generation and dissipation during shearband propagation.[15,16] Gaining deeper and fundamental insight into these topics imposed significant experimental challenges, due to the nanoscopic damage localization in a disordered material and the short timescales of shear banding.
An important contribution to both the speed at which shear bands operate and the corresponding heating from plastic work was made by Wright et al.[11] Using strain gauges directly mounted on the sample, it was convincingly demonstrated that the duration of a shear event is of the order of a millisecond, resulting in shearband velocities orders of magnitude smaller than the shearwave speed (~ km/s). This insight lead to significant corrections of earlier proposed shearband heating models that relied on shear durations in the range of 10^{−10} to 10^{−6} seconds,[17,18,19] and which resulted in local temperature excursions up to the glass transition temperature \( \left( {T_{g} } \right) \) or even exceeding several thousand Kelvin.
With shear durations in the millisecond regime, it became possible to directly trace the spatiotemporal profile of shearband dynamics when using measurement systems with sufficiently short electronic and mechanical response times. We pursued this route and began to trace the timeresolved shearband dynamics across temperature and various metallic glass alloys.[20,21,22] One of the central outcomes of this effort was that the logarithm of the average shearband velocity, as derived from a simple linearization of the underlying displacement jump and by adopting a sheardisplacement jump mechanism, scaled linearly when graphed vs. \( 1/T \). Clearly, this represented nothing else than the two decades earlier mapped transition between serrated and nonserrated flow by Kimura and Masumoto. However, now their “deformation map” and the derived effective barrier energy, \( E_{\text{eff}} \), was directly linked to the propagation speed (sliding) of the shear defect itself. Furthermore, the transition from serrated to nonserrated flow could be explained as a result of competing velocities: as long as the shearband velocity \( \left( {v_{\text{SB}} } \right) \) remained larger than the resolved crosshead velocity \( \left( {v_{\text{XH}} } \right) \) of the testing machine, serrated flow occurred. When both velocities become equal, the transition to nonserrated inhomogeneous flow begins. Beyond this point, the \( v_{\text{SB}} \) is slower than \( v_{\text{XH}} \) and the measured shear velocity will always equate to the resolved crosshead velocity. Thus, the transition temperature, \( T_{\text{crit}} \), is sensitive to \( v_{\text{XH}} \) for one and the same alloy. Figure 1 summarizes this finding schematically.
From the perspective of the shearband material, the result embodied in Figure 1 can be understood in terms of a competition between a material and temperaturedependent relaxation rate and a (athermal) disordering rate imparted by the shear deformation. Since these rates are shown to sensitively depend on small variations of the external temperature, internal temperature excursions and thus shearband heating must indeed be small. Stateoftheart thermal imaging supports this conclusion.[23,24] The thermalactivation framework of serrated flow can be expanded when considering a less recognized insight gained from our shearband dynamics work, namely that shearband aging (structural relaxation) proceeds during the elastic loading segments \( \left( {v_{\text{SB}} \ll v_{\text{XH}} } \right) \) inbetween individual serrations.[25] Similar to the shearband propagation phenomenon, thermal activation with its distinct energy scale can be shown to govern shearband aging. Structural relaxation during the nominally elastic segments between stress drops give thus the shearband material the ability to recover. With the absence of any other internal damage mechanisms, this shearband aging response should allow a number of serrationcycles that mainly (ignoring moments due to lateral shear) is limited by the physical dimension of the specimen. Final fracture after a small number of serrations must therefore be promoted by other damage processes, such as internal microcracking,[26,27] than shear itself. Another consequence of an increasing \( v_{\text{XH}} \) is therefore that the aging time during reloading shortens, thereby reducing the serration stressamplitude towards \( T_{\text{crit}} \) (negative strainrate sensitivity). This sequence of sliding \( \left( {v_{\text{SB}} \gg v_{\text{XH}} } \right) \) followed by arrest \( \left( {v_{\text{SB}} \ll v_{\text{XH}} } \right) \) can be well described with the characteristics of a stickslip system, where mechanical energy storage is followed by a release of elastic energy. As evident from the machine equation used to describe stickslip systems, the slip phase is depending on the compliance, which in the case of the mechanical testing experiment includes both the sample and the machine. This needs to be kept in mid, as the property \( v_{\text{SB}} \) is consequently not intrinsic to the material. However, our understanding is that the Arrhenius construct offers a pathway to assess an intrinsic property of the slip phase (shearband propagation), namely \( E_{\text{eff}} \). In view of the field’s central vision to design metallic glasses with large intrinsic ductility, this intrinsic \( E_{\text{eff}} \) becomes an interesting quantity as it seems to govern both shearresistance and shearband recovery. This will be discussed in more detail later.
The afore summarized findings should be viewed as a brief introduction to the central question of this article: What research questions come beyond serrated flow in metallic glasses? Based on a contribution to a symposium in honor of Prof. Peter Liaw at the TMS 2020 annual meeting, I discuss this question nonexhaustively by identifying the following four main research areas:

A.
the statistical signature of serrated flow,

B.
the value of \( E_{\text{eff}} \) as a structural parameter that possibly quantifies ductility,

C.
the structural length scale, and

D.
the structure of the shear defect underlying inhomogeneous deformation.
Without doubt, continued efforts in these areas will greatly enhance our understanding of inhomogeneous plasticity in metallic glasses and will lead us closer to the visionary goal of designing ductile metallic glasses.
I write this article as a viewpoint and in tribute to Prof. Liaw’s leadership in the community and his never ceasing interest in serrated flow.
2 Beyond Serrated Flow in Bulk Metallic Glasses
Nine years have now passed since the finding schematically summarized on Figure 1, and five since we summarized the full body of shearband dynamics work.[22] As of today, the body of literature on serrated flow continues to grow for metallic glasses, and also finds renewed interested in the novel area of multiprinciple element alloys.[28,29,30] In contrast, our own continued efforts departed from the stress–strain signature of serrated flow, targeting fundamentals of strain localization in metallic glasses, some of which are contained in the following subsections that are organized according to the identified research areas A to D.
2.1 Statistical Signature of Serrated Flow
The generic feature of plastic discontinuities in a stress–strain response of structural materials has recently attracted the statistical physics community[31] and was subject of our review on microplasticity.[32] Central to these works is the attempt to describe fluctuations in plasticity (or simply the discrete displacement increment, often referred to as a (slip)avalanche) via analytical models that rely on little or no microstructural details. Such models propose powerlaw scaling of the form \( D\left( S \right)\sim S^{  \alpha } \), with \( S \) being the event size and where a numerically identical and trivial scaling exponent \( \alpha \) can give the attribute “universal” to such distribution functions \( D\left( S \right) \). Prior to successfully applying this approach to metallic glasses, other intermittently deforming materials had been demonstrated to follow scalefree like universal statistics, including for example single crystal plasticity[33] and slip of granular media.[34] These developments are somewhat at odds with our classical approach to plasticity that implicitly relies on welldefined means and scales. Indeed, truncated powerlaw scaling, and therefore scalefree (like) behavior was found for several BMGcompositions.[35,36,37] Other compositions seem to yield serrated flow statistics with scaledependent distributions.[38] Noteworthy is the finding that experimental tuning parameters, such as strain rate, determine the size of the largest observed shear events,[39] which in fact is very much in agreement with the earlier discussed shearband aging and related reduction in stressdrop magnitude with increasing rate. Consequently, similar trends are expected upon decreasing the temperature.
The discrepancy between different reports as to whether a monolithic metallic glass exhibits scalefree intermittent flow and therefore can be framed into the context of critical phenomenon remains a puzzling topic. This can nicely be demonstrated by the work of Sun et al.,[35] who tested a series of compositions, including the same alloy in different annealing states. Figure 2(a) displays data from Reference 35 that evidences powerlaw scaling of a density distribution with an exponent of approx. 1.5 for Cu_{47.5}Zr_{47.5}Al_{5}. A similar exponent was found for a subset of the tested alloys, all of which exhibited the largest strains at failure (> 10 pct) during compressive loading.
Yet another subset of alloys yielded stressdrop distributions that were referred to as chaotic, which simply indicates no scalefree signature even though the functional form of the distribution was not specifically evaluated. Interestingly, an alloy from this group was subjected to mechanical preloading, after which the stressdrop magnitudedistribution became scalefree. In agreement with the other alloys that revealed powerlaw distribution, a large plastic strain was also reported. This difference in statistical signature is linked to the number of shear bands and their interaction during plastic flow. Only alloys with a denseshear band structure are admitting sufficiently large numbers of small stressdrops (serrations) that can promote scalefree scaling. Since aspect ratio and sample alignment significantly determine strain at failure,[40,41] one could conclude that the manifestation of different serration statistics may merely be results of boundary conditions that cause inhomogeneous stress states. It is noted that the above mentioned mechanically preloaded alloy is such a case.
However, the situation is not so clear. Our own work on Zr_{65}Cu_{25}Al_{10} revealed that significant changes in boundary conditions (from uncontrolled constrained to unconstrained) only shifted the serrationmagnitude histogram (Figure 2(b)). At the same time, the plastic strains were in both cases largely exceeding 10 pct. Furthermore, a variation of aspect ratio between 2:1 and 1:2 (height:diameter) did not show any powerlaw scaling.[42] Since an aspectratio reduction of a malleable BMG constitutes the extreme case of shearband interaction due to an insufficient distance between free surfaces for unconstrained systemspanning shearband formation, one may have expected a powerlaw scaling if the introduction of inhomogeneous stress fields is the sole factor determining the serration statistics. This does, however, not seem to be the case. There is thus a structural component in monolithic BMGs that contributes to the scaling as shown in Figure 2(a) that so far remains fully undefined. This is much different to the case of metallic–glass matrix composites, where the statistics of stress–strain instabilities changes towards smaller event sizes[43,44]—a result that naturally emerges due to the introduction of internal microstructural length scales where crystallites lead to shearband deflection and arrest.[45] In fact, some first evidence has been provided that even the scaling exponent \( \alpha \) directly scales with the volume fraction and average size of the crystalline phase.[45] Such clear findings are lacking in the case of monolithic metallic glasses. Instead, the small amount of published work, the challenge of properly determining the distribution forms, and the unassessed effects of testing parameters, render the emergence of powerlaw (like) scaling of serrated flow in the monolithic case at most phenomenologically understood. In addition, an inherent conflict surfaces when considering that one essential message from the agreement between scalefree statistical models with universal exponents is the insensitivity to microstructural details, whereas the above discussion suggests at least some structural dependencies for monolithic glasses. Furthermore, scaleinvariance of plasticity entails some underlying mechanism with longrange coupling and correlated structural activity. Why this may be the case in some monolithic glassy alloys, whereas in others not, remains unsolved. This unsatisfactory situation reminds us strongly about crystalline microplasticity[32] that initially found strong agreement with universal scalinglaws across numerous microstructure, whereas we first now begin to understand the opportunities hidden in the microstructurally sensitive statistical scaling laws of plastic fluctuations.[46,47] With enough careful continued research efforts, the same may eventually be concluded for metallic glasses, which interestingly would imply the presence of unexpectedly large structuredependent internal length scales in monolithic metallic glasses.
2.2 Effective Barrier Energies Across Numerous Alloy Systems
The slope of the data in Figure 1 determines an effective barrier energy \( E_{\text{eff}} \) that can be seen as a measure of the resistance to shear. This is better understood when acknowledging that data sets for numerous different alloys seem to converge at \( 1/T = 0 \). Extrapolating to this point at high temperatures, the shearband velocity attains a value of km/s that is not much different than the sound velocity. Given a converging intersection point on the ordinate, a larger value of \( E_{\text{eff}} \) means that shear is much slower at a fixed temperature than for a smaller \( E_{\text{eff}} \). Figure 3 demonstrates this for the Zr_{x}Cu_{90−x}Al_{10} system, where approximately an order of magnitude difference in shear–velocity is observed at ca. 0.00425 K^{−1} (− 40 °C). Consequently, the alloy with 65 at. pct Zr has the slowest and most stable shear response at this temperature, which translates to the highest plastic strain at failure at room temperature.[38] It is noted that Reference 48 covers a larger temperature window than shown in Figure 3, which leads to slightly different \( E_{\text{eff}} \)values after fitting to an Arrhenius model. Whilst the data in Figure 3 is only an observation for one alloy system, one may naturally ask if this is a finding of potential general validity.
To expand the findings contained in Figure 3 to a broader class of alloys is an experimental task of considerable effort, which we will report on in a forthcoming manuscript.[49] However, a simple literature study will reveal a series of effective barrier energies that are listed in Table I. This summary of values ranges from 0.26 to 0.48 eV, and I find it worthwhile to think about the fundamental structural parameters that may govern the value of \( E_{\text{eff}} \). This is of particular interest, since we hypothesize based on the data in Figure 3 that the shear stability of a metallic glass will largely depend on \( E_{\text{eff}} \), and that the final strain at failure at room temperature may grow (or find a maximum) with increasing \( E_{\text{eff}} \).
The typically constructed scaling of characteristic BMGproperties, such as a mechanical property with \( T_{g} \), are insufficient to rationalized the trend of \( E_{\text{eff}} \) in Figure 3 and Table I, which was discussed in Reference 51. This directs focus to the chemical and topological details of the alloy structure and one can begin with considering the nearest neighbor shell and the resistance it may have against disruption (Figure 4). Hypothesizing that the \( E_{\text{eff}} \) is a measure of the barrier for diffusive jumps that are species dependent (here Cu, Zr, Al), it is as a first step instructive to identify the fastest diffusing element. Based on the atomic size, the most ideal metallic bonding character, and selected atomistic studies,[52,53] it is most reasonable that Cu is the fasted diffusor. With this assumption the second step consists of interrogating a composition with respect to how easy changes in local bonding environments are. This is determined by the binding energies between species and also the size of the central atom, since a large atom has a larger coordination number. Therefore, Cu is surrounded by fewer atoms in Figure 4 than Zr. Chemistryspecific coordination numbers can be estimated via the efficientclusterpacking model,[54,55] and this analysis reveals that the compositional effect on the bonding around Cu to its nearest neighbors changes according to the change of nominal composition in the ZrCuAl system. With increasing Zrcontent, this leads to a shifting bond character from a Cu–Culike to a more Cu–Zrlike environment.
Using the mixing enthalpies and the heats of formation, one finds that Cu–Zr bonds are stronger than Cu–Cu bonds, which allows to conclude that Cu will experience a shallower migration barrier in the Zrlean alloy. Even though the assessed shearband dynamics is a competition between athermal sheardisordering and thermallyactivated relaxation, \( E_{\text{eff}} \) naturally characterizes the latter. It thus follows that Zrrich alloys in Zr_{x}Cu_{90−x}Al_{10} are expected to relax faster than Zrlean compositions, thereby increasing the resistance to continued shear. This is in good agreement with the data contained in Figure 3, providing a first atomistic pathway to understand and connect \( E_{\text{eff}} \) to structural details of a metallic glass.
The mathematical details of the above structural analysis and its link to \( E_{\text{eff}} \) have been described by Thurnheer et al.,[38] but suffer currently from two shortcomings: (1) It does not take into account the dilated structure in the shearband core, and (2) it further does not include any bias of stress. Comparing between different alloys, the former can be ignored if one assumes a homogenous volume expansion and the absence of chemical shearband segregation.[56] The latter can be considered by the most basic relation \( Q = H  \varOmega \tau \), where \( H \) is the zerostress barrier, \( \varOmega \) the activation volume, \( \tau \) the shear stress, and \( \varOmega \) a barrier energy. The three unknowns, \( H \), \( \varOmega \) and \( \tau \) can be determined independently from either experiments, or the efficientpackingcluster model, which allows a refined structural model including a stressbias that is currently underway.
As part of the experimentalists view, we add that the yield stress is connected to the shear modulus \( G \),[57] that itself obeys the theory of elastic modulus inheritance,[58] which in the ternary case means that Zrrich alloys have a lower shear modulus. One therefore finds lower \( G \) values linked to a more sluggish sheardynamics. Since low shear moduli often scale with the ductility of metallic glasses,[59,60] the here sketched thoughtprocess may suggest that an atomicscale understanding for ductility and the design of ductile metallic glasses is within reach, where \( E_{\text{eff}} \) plays a central role. Based on almost 20 different compositions, we will demonstrate this opportunity in detail in the future.[49]
2.3 Length Scales of the Underlying Shear Defect
Serrated flow in metallic glasses has for a long time revolved around the mechanics and the detailed appearance of the stress–strain signature, whereas the underlying structure, and in particular the mediating shear defect, received experimentally less attention. One obvious reason for this is the difficulty in revealing and characterizing a nanoscale sheared region in a disordered material. In the context of structural heterogeneities of metallic glasses, this has been summarized in detail in a recent review article,[61] and we will here only highlight a few aspects regarding the fluctuations of both length scales and structural measures of shear bands.
At the smallest scale of the shearband core, detailed scanningtransmission electron microscopy (STEM) work has revealed that the simple measure of the shearband thickness \( t_{w} \) can vary more than 40 pct over a distance of 600 nm, and become a tenfold of the commonly cited shearband thickness of 10 or 20 nm.[62] One may argue that deviations away from 10 to 20 nm can be caused by projection errors during STEM imaging, but tilting the TEM sample allows the determination of an edgeon view with the electron beam, as discussed in Reference 63. This variation of the width of the shearband core is schematically depicted in Figure 5, to which we will add two additional length scales of substantially larger values.
With the nanoindentation work by Pan et al.[64] and Maass et al.[65] it became clear that there is some longrange signature around the nanoscopic shearband core, extending over tens to hundred micrometers. These initial reports had different interpretations, but captured the same feature. Our own conclusion was that the longrange signature measured via nanoindentation hardness maps originated from positiondependent residual stresses, of which the inplane component is known to cause changes in the measured hardness.[66] These residual stresses were proposed to emerge when shear occurs over a nonplanar shearband plane,[27] locally giving rise to either tensile or compressive stress states. That means, no structural change was ascribed to the longrange softening (or hardening). A longrange strain field around a shear band was also reported via Xray strain mapping[67] and magnetic force microscopy.[68] Xray correlation spectroscopy suggests that these longrange stress (or strain) fields can significantly enhance the local relaxation response of the matrix material around the shear band itself.[69] A critical aspect in the quantification of these still unsatisfactorily understood and characterized longrange signatures is that they depend on location, meaning that they may not even be observed in a single experiment. Similar to the later discussed shearband structure, strongly positiondependent properties increase the complexity of the shear defect. A sensible contribution to the question if the longrange signatures are caused by only residual internal stresses or also structural changes was recently provided via fluctuation microscopy.[70] These measurement indicated a micronwide damage zone around the shearband core that indeed revealed structural changes. We emphasize that this is a distinctly different observation than the signature of a longrange residual stress field.
These developments do not only motivate the distinction between a nanometer shearband core, a surrounding micrometer structural damage zone, and an even larger zone of residual stresses, as schematically summarized in Figure 5, but also that the lengthscales of these are positiondependent properties. In particular, the latter insight makes the experimental characterization of this shear defect very challenging, since results will depend on where they are measured along the shearpath. As we will see in the following section, the emerging locality of the shearband is also a dominant factor in the structural change.
2.4 Local ShearBand Structure
Focusing on the underlying shear defect instead of the stress–strain signature naturally leads to interrogating the structure of a formed shear band. One experimentally unexplored aspect of shearband structure is the question if any possible damage accumulation occurs during shear. In other words, is the structure of the shear band evidencing any systematic change with locally admitted shear strain \( \gamma \)? Our work on shearband dynamics repeatedly revealed indications for that this may be the case, as for example seen in Figure. 3 of Reference 20 where \( v_{\text{SB}} \) increases with strain towards failure. Selected atomistic simulations have interrogated regions of strain localization as a function of local shear strain,[71,72] but to our knowledge, no experimental data set has been reported. One of the few methods that allows quantitative tracking of shearband structure is highangle annular darkfield (HAADF) STEM that can return changes in density \( \left( {\Delta \rho } \right) \) between the shearband core and the surrounding matrix material.[73] This approach has revealed both significant reductions in density with amounts exceeding ~ 10 pct,[62,73] but also regions of increased density (~ 6 pct).[74] Traced along the shearband, \( \Delta \rho \) is like the shearband thickness a locally varying property.[62] Using HAADFSTEM on shearbands that have admitted different amounts of shear strain, we pursued a statistical assessment of both local \( \Delta \rho \) and \( t_{w} \) values in a Zrbased BMG (Zr_{52.5}Cu_{17.9}Ni_{14.6}Al_{10}Ti_{5}, Vit105). One key aspect of this effort was to sample a large range of \( \gamma \), which initially was attempted by varying the amount of axial engineering strain of compression samples.[75] In cases where only one single shear band accumulated all plastic strain, it is straight forward to calculate a local \( \gamma \) of the shear band using the locally measured shearband thickness. Figure 6 shows this data set as a cluster at shear strains larger than 1000. This approach involves the complication of finding a shear band in a crosssectional cut of a bulk sample, the procedure of which is outlined in Reference 62.
A different approach using 3point bending was subsequently pursued to assess smaller shearstrains, which has the advantage that a TEM lamella can be extracted directly at the surface step. That means, the magnitude of the shearband surfacesteps resulting from plastic bending can be determined and sampled in order to probe different \( \gamma \). A TEM sample liftout is done including the surface step, from which a shearband segment can be traced inwards into the sample. In this way, \( \gamma \)values below 100 were probed. The corresponding data is displayed in the upper left corner in Figure 6. In addition to the much smaller shearstrain values, it is also clear that the associated local density changes are much smaller, mostly yielding values that are between the resolution limit and ~ 1 pct density decrease. It is finally interesting to note that no compaction (positive \( \Delta \rho \)) was measured as part of this data set, but has been seen in our work on a ternary Zrbased alloy.[63]
Each data set alone in Figure 6 does not reveal any particular trend, and also data sets from individual TEM foils do not allow any systematic conclusion. A selection of three different shearbands is highlighted in the inset in Figure 6, demonstrating no change of \( \Delta \rho \) with increasing \( \gamma \), no change of \( \gamma \) with decreasing \( \Delta \rho \), or a mildly decreasing \( \Delta \rho \) with increasing \( \gamma \). However, the two strongly scattered data sets together hint towards some overall trend. What structural mechanisms may drive this scatter remains experimentally inaccessible, and clearly more efforts are needed to investigate possible dependencies between structure and shear strain. However, a direct conclusion from this data is that single measurement may reveal any result, and that generalized conclusions based on small data sets cannot be made. The large scatter in Figure 6 is therefore another manifestation of the locality of shear deformation that was discussed in the previous section.
Whilst the here presented data is in qualitative agreement with recent computer simulations that highlight the positiondependent complexity of strainlocalization in BMGs,[76,77,78] we are far away from understanding the local mechanisms that cause these fluctuations across much larger lengthscales than of short and mediumrange structural order. To overcome this hurdle with experiments does currently not seem feasible, and substantial efforts/developments in atomistic simulations are needed in view of the length scales, time scales, and the prominence of thermal activation in shear banding. In fact, one has to conclude that current atomistic simulations never capture the same damage mechanism as characterized with experiments. With our continued effort in probing true thermallyactivated structural activity in metallic glasses via microsecond timescale molecular dynamics simulations,[79,80,81] we are currently exploring sufficiently low strain rates that can produce a serrated flow response that is not simply a manifestation of driven and athermal plasticity.
3 Concluding Remarks and Outlook
This manuscript discusses four research directions that go beyond the stress–strain signature of serrated flow in BMGs.
We began with the statistical characteristics of plastic fluctuations in serrated flow. The current status of this approach suggests some scalefree response of ductile BMGs, but also reveals as of now not well understood structural influences on the serration statistics. This itself warrants further studies, as an apparent contradiction between microstructurally insensitive theoretical statistical models and structural effects on the statistics emerge. It remains also unclear what alloyspecific microstructural mechanisms dictate longrange interactions and correlated plastic activity that scaleinvariance entails.
As a second direction, we articulated the possibility of using the effective barrier energy derived from temperature dependent shearband velocities as a descriptor for shear stability. If we are successful with proving the validity of this approach, a model would be within reach that connects experimentally derived quantities with the atomistic details of the alloy. One may further speculate if such a model could guide the design of malleable BMG compositions.
The third and fourth research directions are related, as they address length scales and the structure of shear bands that underlie serrated flow. Here it becomes clear that a shear band is much more complex than a simple plane with a finite thickness and uniform properties. All experimentally so far revealed properties are depending on position, and the origins of the various signatures beyond the nanoscale shearband core are yet to be unraveled. We end with posing the question if structural damage accumulates with strain inside a shear band. Given evidence of structural changes outside the shearband core, this question may be also be considered at the larger lengthscales of an extended damage zone.
We would argue that serrated flow and the dynamics of shear bands is a very well understood topic. However, many fundamental questions relating to the strainlocalization process remain elusive or are essentially unexplored. Metallic glasses fall, in this regard, well behind their crystalline counterparts, for which textbooks have been filled with detailed defect mechanisms. If the international research community wants to live up to the originally articulated vision of developing ductile glassy alloys, continued efforts are needed to fill this gap. We hope that this contribution can spark new efforts in understanding plastic flow of metallic glasses.
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Acknowledgments
This research was carried out in part in the Frederick Seitz Materials Research Laboratory Central Research Facilities at UIUC. RM gratefully acknowledges startup funds provided by the Department of Materials Science and Engineering at UIUC. RM acknowledges the excellent coworkers that have contributed to the here discussed topic, including J.F. Löffler, D. Klaumünzer, P. Thurnheer, K. Laws, P.M. Derlet, C. Liu, S. Küchemann, A. Das, C. Volkert, V. Roddatis, K. Samwer, and many more.
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Maaß, R. Beyond Serrated Flow in Bulk Metallic Glasses: What Comes Next?. Metall Mater Trans A 51, 5597–5605 (2020). https://doi.org/10.1007/s1166102005985w
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DOI: https://doi.org/10.1007/s1166102005985w