Transient Networks Research Articles

Energy-Dissipating Polymeric Silicone Surfactants.

Materials that are able to withstand impact loadings by dissipating energy are crucial for a broad range of different applications, including personal protective applications. Shear-thickening fluids (STFs) are often used for this purpose, but their preparation is still limited, in part, to high production costs. It is demonstrated that polymeric surfactants comprised of linear telechelic sugar-modified silicones-with neither additives nor particles-generate transient polymer networks (TPNs) that represent a promising alternative to STFs. The reported polymers have distinct viscoelastic properties and can turn from a liquid into a rubbery network when force is applied. Saccharide-modified silicones with short chains (degree of polymerization (DP) ≈ 34, 68) are solids, but become energy-absorbing viscoelastic fluids when diluted in low-viscosity silicone oils; longer silicones (DP ≈ 338, 675) with low saccharide contents are viscoelastic fluids at room temperature. Excellent damping properties are found for the reported silicone surfactants, even those containing only 0.1% saccharides. The degree of energy absorption can be tailored simply by controlling the sugar/silicone ratio.

Transient brain networks underlying interpersonal strategies during synchronized action.

Interpersonal coordination is a core part of human interaction, and its underlying mechanisms have been extensively studied using social paradigms such as joint finger-tapping. Here, individual and dyadic differences have been found to yield a range of dyadic synchronization strategies, such as mutual adaptation, leading–leading, and leading–following behaviour, but the brain mechanisms that underlie these strategies remain poorly understood. To identify individual brain mechanisms underlying emergence of these minimal social interaction strategies, we contrasted EEG-recorded brain activity in two groups of musicians exhibiting the mutual adaptation and leading–leading strategies. We found that the individuals coordinating via mutual adaptation exhibited a more frequent occurrence of phase-locked activity within a transient action–perception-related brain network in the alpha range, as compared to the leading–leading group. Furthermore, we identified parietal and temporal brain regions that changed significantly in the directionality of their within-network information flow. Our results suggest that the stronger weight on extrinsic coupling observed in computational models of mutual adaptation as compared to leading–leading might be facilitated by a higher degree of action–perception network coupling in the brain.

Mechanical Strength Management of Polymer Composites through Tuning Transient Networks.

The addition of transient networks to polymer composites marks a new direction toward the design of novel materials, with numerous biomedical and industrial applications. The network structure connected by transient cross-links (CLs) relaxes as time evolves, which results in the stretching release of polymer strands between transient CLs during strain. Using molecular dynamics simulations, we measure directly the stress-strain curves of double polymer networks (DPNs), containing both transient and permanent components, at different strain rates. Lifetime and density of transient CLs control the relaxation spectrum of transient networks and determine the mechanical properties of DPNs. A Rouse mode analysis reveals that at high strain rates the mechanical strength of DPNs is defined jointly by the cross-linking structures of permanent and transient networks. At low strain rates, the cross-linking structure of transient network relaxes, leaving the permanent component of the network as a sole contributor to the mechanical strength of DPNs. The transient network is shown to facilitate a dissipation of energy at higher strain rates and prevents a rupture of the network, while the permanent network preserves the structural integrity of the composite at low strain rates. This study provides computational and theoretical foundations for designing polymer composites with desirable mechanical strength and toughness by means of tuning transient networks.

Dynamically tuning transient silicone polymer networks with hydrogen bonding

Supramolecular polymers are composed of non-covalently connected chains and characterized by high chain dynamics. The viscoelastic behavior of supramolecular telechelic sugar-siloxanes - ranging from solids to viscous fluids able to form transient polymer networks - is readily tuned by the fraction of internal HO groups that can intermolecularly form hydrogen bonds.

Dynamic functioning of transient resting-state coactivation networks in the Human Connectome Project.

Resting‐state analyses evaluating large‐scale brain networks have largely focused on static correlations in brain activity over extended time periods, however emerging approaches capture time‐varying or dynamic patterns of transient functional networks. In light of these new approaches, there is a need to classify common transient network states (TNS) in terms of their spatial and dynamic properties. To fill this gap, two independent resting state scans collected in 462 healthy adults from the Human Connectome Project were evaluated using coactivation pattern analysis to identify (eight) TNS that recurred across participants and over time. These TNS spatially overlapped with prototypical resting state networks, but also diverged in notable ways. In particular, analyses revealed three TNS that shared cortical midline overlap with the default mode network (DMN), but these “complex” DMN states also encompassed distinct regions that fall beyond the prototypical DMN, suggesting that the DMN defined using static methods may represent the average of distinct complex‐DMN states. Of note, dwell time was higher in “complex” DMN states, challenging the idea that the prototypical DMN, as a single unit, is the dominant resting‐state network as typically defined by static resting state methods. In comparing the two resting state scans, we also found high reliability in the spatial organization and dynamic activities of network states involving DMN or sensorimotor regions. Future work will determine whether these TNS defined by coactivation patterns are in other samples, and are linked to fundamental cognitive properties.

Deciphering How the Viscoelastic Properties of Mussel-Inspired Metal-Coordinate Transiently Cross-Linked Gels Dictate Their Tack Behavior.

In recent years, researchers have incorporated mussel-inspired metal-coordinate cross-links into various types of gels to improve their mechanical properties, particularly toughness and self-healing. However, not much is understood about how the linear mechanical properties of these gels dictate their tack properties. In this study, we use shear rheology and tack tests to explore correlations between linear viscoelastic properties (i.e., plateau modulus, Gp, and characteristic relaxation time, τc) and tack behavior (i.e., peak stress, σmax, and energy dissipation per volume, EDV) of transiently cross-linked hydrogels comprised of histidine-functionalized 4-arm PEG coordinated with Ni2+. By using the Ni2+-histidine ratio and polymer wt % of the transient networks to control their viscoelastic properties, we demonstrate a strong dependence of σmax on Gp and τc. The observed correlation between network dynamics and mechanics under tensile load is in good quantitative agreement with a theoretical framework for σmax, which includes the linear viscoelastic properties as parameters. EDV is also influenced by Gp and τc, and the EDV after reaching σmax is additionally dependent on the polymer wt %. These findings are consistent with previously proposed molecular mechanics of reversible HisxNi2+ cross-links and provide us with new insights into the correlations between bulk mechanics and adhesive dynamics of gels with transient metal-coordinate cross-links.

Modeling lipid-encapsulated microbubbles using transient network theory

Encapsulated microbubbles (EMBs) are widely used to enhance contrast in ultrasound sonography and are finding increasing use in biomedical therapies such as drug/gene delivery and tissue ablation. EMBs consist of a gas core surrounded by a stabilizing shell made of various materials, including polymers, lipids, and proteins. Lipid-coated EMBs present a unique challenge for modeling due to their relatively large oscillations and nonlinear, viscoelastic properties. We propose a novel model for a lipid-coated, spherical EMB that utilizes a statistically based continuum theory based on transient networks to simulate the encapsulating material. The use of transient network theory permits the viscoelastic properties of the encapsulation—such as stress, elastic energy and entropy—to be calculated locally based on the configuration of lipid molecules. The model requires a minimum number of parameters that include the lipid concentration, and the rates of attachment and detachment of lipids to and from the network. The model closely reproduces the experimentally measured radial response of an ultrasonically driven, lipid-coated microbubble. The model also reproduces experimentally observed nonlinear behavior, such as compression and expansion-dominated oscillations. Furthermore, the model can be readily extended to large nonspherical EMB deformations, which are important in many biomedical applications.

Lewis Pairs as Highly Tunable Dynamic Cross-Links in Transient Polymer Networks.

Classical Lewis pairs (LPs) between unhindered electron-poor Lewis acids (LAs) and electron-rich Lewis bases (LBs) present an overlooked motif with tremendous potential as dynamic cross-links in transient polymer networks (TPNs) for self-healing and stimuli-responsive applications. We demonstrate that simple and intuitive matching of weak/strong organoborane LA and amine LB pairs offers access to a large set of binding equilibrium constants, Keq, that span ∼6 orders and dissociation rate constants, kdiss, that span ∼7 orders of magnitude. The implementation in polystyrene (PS)/polydimethylsiloxane (PDMS) blends results in dynamically cross-linked networks with bulk thermomechanical properties that are directly correlated with the strength and kinetic parameters for the LP interactions. The LP dynamic cross-link design is highly versatile and broadly applicable to different polymer architectures as demonstrated in the formation of reprocessable elastomers from Lewis base-decorated high molecular weight PDMS in combination with Lewis acid-decorated PS when reinforced with fumed silica as a filler.

A memristor-based transient chaotic neural network model and its application

Transient chaotic neural networks (TCNNs) have shown promise in solving optimization problems but still suffer from slow convergence and being difficult to implement in hardware. In this paper, the HP memristor is introduced to a TCNN to develop a memristor-based transient chaotic neural network (MTCNN) model that is highly efficient, converges quickly, and has significant prospects for physical implementation. The proposed MTCNN makes full use of the nonlinearity and memory-related characteristics of memristors, and their conductance values are used as self-feedback connection weights that can be adjusted dynamically according to the annealing algorithm. The MTCNN model was applied to solve combinatorial optimization problems, including the channel assignment problem (CAP) of four cells and the traveling salesman problem (TSP) of 10 cities. In 500 runs, the MTCNN algorithm delivered a 5% higher optimal solution rate than the TCNN algorithm while using only 70% of its number of iterations in the CAP, and achieved a shorter average distance and a 40% higher convergence speed than the TCNN algorithm in the TSP.

The Permeability Evolution of Tuffisites and Implications for Outgassing Through Dense Rhyolitic Magma

AbstractThere is growing evidence that outgassing through transient fracture networks exerts an important control on conduit processes and explosive‐effusive activity during silicic eruptions. Indeed, the first modern observations of rhyolitic eruptions have revealed that degassed lava effusion may depend upon outgassing during simultaneous pyroclastic venting. The outgassing is thought to occur as gas and pyroclastic debris are discharged through shallow fracture networks within otherwise low‐permeability, conduit‐plugging lava domes. However, this discharge is only transient, as these fractures become clogged and eventually blocked by the accumulation and sintering of hot, melt‐rich pyroclastic debris, drastically reducing their permeability and creating particle‐filled tuffisites. In this study we present the first published permeability measurements for rhyolitic tuffisites, using samples from the recent rhyolitic eruptions at Chaitén (2008–2009) and Cordón Caulle (2011–2012) in Chile. To place constraints on tuffisite permeability evolution, we combine (1) laboratory measurements of the porosity and permeability of tuffisites that preserve different degrees of sintering, (2) theoretical estimates on grainsize‐ and temperature‐dependent sintering timescales, and (3) H2O diffusion constraints on pressure‐time paths. The inferred timescales of sintering‐driven tuffisite compaction and permeability loss, spanning seconds (in the case of compaction‐driven sintering) to hours (surface tension‐driven sintering), coincide with timescales of diffusive degassing into tuffisites, observed vent pulsations during hybrid rhyolitic activity (extrusive behavior coincident with intermittent explosions), and more broadly, timescales of pressurization accompanying silicic lava dome extrusion. We discuss herein the complex feedbacks between fracture opening, closing, and sintering and their role in outgassing rhyolite lavas and mediating hybrid explosive‐effusive activity.

PH-Assisted Gelation of Lactose-Modified Chitosan.

We report on a controlled process allowing for the gelation of a diol-rich chitosan-derivative named CTL (lactose-modified chitosan) in the presence of boric acid as the cross-linker. A two-step approach is described, namely (i) the mixing of CTL and boric acid at pH = 5, a condition where the inorganic component is mildly reactive; (ii) the addition of sodium bicarbonate (NaHCO3) as a trigger, allowing for the gradual and slow pH increase. The goal was to convert gradually the almost inert neutral boric acid into the much more reactive borate anion, the latter promoting the formation of borate esters with CTL diols. Gelling kinetics as well as mechanical behavior at small and large deformations was investigated by rheometry. CTL-boric acid gels behaved essentially as transient networks, hence continuously assembling and dissociating in a highly dynamic fashion. The present gelling mechanism preserves the strain-hardening behavior in the nonlinear region of stress-strain response, corroborating the already suggested potential applications of such gels as mimics of biological soft tissues.

Geochemical constraints on the role of tuffisite veins in degassing at the 2008–09 Chaitén and 2011–12 Cordón Caulle rhyolite eruptions

Hybrid activity during the rhyolitic eruptions of Chaitén (2008–09) and Cordón Caulle (2011–2012) in Chile has offered unprecedented insights into the enigmatic and complex degassing processes occurring during eruptions of silicic magma. Highly permeable, transient fracture networks within the conduit can act as outgassing channels. Their interaction with deeper volatile-rich melt can account for both punctuated explosive activity and large-scale degassing of the system, leading towards predominantly effusive behaviour. In this study we characterise trace element concentrations and 210Pb226Ra systematics within pyroclastic material from the recent eruptions at Chaitén and Cordón Caulle volcanoes. Results reveal how gas fluxing from deep, volatile-rich reservoirs to the surface, within magmatic conduits, can be recorded by trace elements and 210Pb226Ra disequilibria in tuffisite veins.Tuffisite veins (particle-filled fracture networks) are present in volcanic bombs from both eruptions. Trace element heterogeneity associated with tuffisites preserves evidence for degassing. At Chaitén, enrichments (e.g. Cu) and depletions (e.g. Mo, Li and Bi) are identified in vein material and clasts transported within veins, and record multiple degassing events. At Cordón Caulle, enrichments of volatiles in an early vein (e.g. Tl and Bi) and depletions in a later vein (e.g. Cd, In, Pb and Tl) reflect interactions between glassy clasts and the carrier gas phase that transported them. In contrast, 210Pb and 226Ra, which can be fractionated during degassing, are mostly in secular equilibrium. Modelling suggests that the disparity between the signals preserved in these two types of chemical signatures reflects the brevity of degassing events and the relative volumes of tuffisite veins and the bodies of degassing magma that they source gas from. The lack of preserved 210Pb enrichments in tuffisite veins at both volcanoes places an upper limit on the mass of deeper, bubble-rich magma outgassed via tuffisites during their lifetime.This study shows that both the presence, and absence, of sample-scale geochemical heterogeneity can be used to place constraints on syn-eruptive physical processes and underlines the value of analysing a wide suite of trace element species.

Microstate functional connectivity in EEG cognitive tasks revealed by a multivariate Gaussian hidden Markov model with phase locking value

Objective. Tracking the spatiotemporal fast (~100 ms) transient networks remains challenging due to a limited understanding of neural activity dynamics as well as a lack of relevant sophisticated methodologies. In this study, we introduce a novel approach to identify simultaneously distinct EEG microstates and their corresponding microstate functional connectivity (µFC) networks in which each µFC network is associated with a distinguished connectivity pattern of recurrent neuronal activity. Approach. The introduced approach is based on a multivariate Gaussian hidden Markov model (MGHMM) to decompose the sensor-space stochastic multi-subject event-related potential (ERP) into quasi-stable EEG microstates. Raw trial segments whose time windows belong to a corresponding segmented EEG microstate are then concatenated for measuring their µFC using the time-averaged phase-locking value. Illustration of this method is evaluated with synthetic data for which ground-truth microstate dynamics are known. Furthermore, we apply the method to identify EEG microstates and corresponding µFC networks in publicly available EEG data measured from visual cognitive tasks. Finally, we compare the MGHMM method with conventional dynamic FC (dFC) approaches using clustering-based K-means and time sliding windows, which conversely segregate the macrostate FC matrices across times into ‘FC-states’. Main results. By using the MGHMM approach, we reveal: (1) EEG microstates, (2) µFC networks, (3) the associations of EEG microstate networks and their corresponding µFC networks dynamically modulated in publicly available EEG cognitive tasks, and (4) compared dFC performances between our proposed µFC approaches and ‘FC-states’ segmented by clustering-based K-means and time sliding windows. Significance. Evidence of significant improvements of microstate correlations (p -value < 0.05) and improved tendency of FC distinction (p -value = 0.064) over reported methods with simulated and realistic data will make this approach a preferred methodology to study dynamic brain networks and guarantee its use for further clinical applications.

Rheological Tuning of Entangled Polymer Networks by Transient Cross-links.

The remarkable functionalities of transiently cross-linked, biopolymer networks are increasingly becoming translated into synthetic materials for biomedical and materials science applications. Various computational and theoretical models, representing different transient cross-linking mechanisms, have been proposed to mimic biological and synthetic polymer networks, and to interpret experimental measurements of rheological, transport, and self-repair properties. Herein, we employ molecular dynamics simulations of a baseline entangled polymer melt coupled with parametrized affinities for binding and unbinding of transient cross-links (CLs). From these assumptions alone, we determine the emergent CL mean density and fluctuations, and the induced rheology, across the 2-parameter space of binding and unbinding affinities for a moderately long chain, entangled the polymer melt. For sufficiently weak (short-lived) CLs, nonmonotonicity emerges with respect to the affinity to form CLs: the stress relaxation, viscous, and elastic moduli all shift above the baseline if CLs form rapidly, reverse below the baseline as CLs form slowly, and reverse again, recovering the baseline as CLs form very slowly. For sufficiently strong (long-lived) CLs and sufficiently fast CL formation, a dramatic rise emerges in the viscous and elastic moduli at all frequencies, more prominently in the elastic moduli at medium to high frequencies, inducing a sol-gel transition. These results are placed in context with the experimental and theoretical literature on transient polymer networks.

Stress fluctuations in transient active networks.

Inspired by experiments on dynamic extensile gels of biofilaments and motors, we propose a model of a network of linear springs with kinetics consisting of growth at a prescribed rate, death after a lifetime drawn from a distribution, and birth at a randomly chosen node. The model captures features such as the build-up of self-stress, that are not easily incorporated into hydrodynamic theories. We study the model numerically and show that our observations can largely be understood through a stochastic effective-medium model. The resulting dynamically extending force-dipole network displays many features of yielded plastic solids, and offers a way to incorporate strongly non-affine effects into theories of active solids. A rather distinctive form for the stress distribution, and a Herschel-Bulkley dependence of stress on activity, are our major predictions.

Local dynamics in supramolecular polymer networks probed by magnetic particle nanorheology.

Transient supramolecular polymer networks are promising candidates as soft self-healing or stimuli-sensitive materials. In this paper, we employ a novel nanorheological approach, magnetic particle nanorheology (MPN), in order to better understand the local dynamic properties of model supramolecular networks from a molecular point of view. Hence, the bond strength between four-arm star-shaped polyethylene glycol (PEG) functionalized at the four extremities with terpyridine ligands is tuned by implementing different metal ions with variable complexation affinities for the ligand. We show that MNP allows for the evaluation of the strength and connectivity of the polymer networks by the estimation of relaxation times, mesh size, and also the viscoelastic properties of these materials. These results are compared and complemented to former outcomes on these systems that were obtained by macroscopic analytical methods. A clear dependence between the strength of the metal-ligand complex and the local dynamics of the polymeric network is observed by the nanorheological approach, which is in good agreement with previous predictions related to the complex formation constants.

Crosslinker mobility weakens transient polymer networks

Transient networks comprised of polymers connected by short-lived bonds are a common design theme for both biological and synthetic materials. Transient bonds can provide mechanical rigidity, while still allowing for visco-elastic flows on timescales longer than the bond lifetime. In many biological polymer networks such as the actin cytoskeleton, the short-lived bonds are formed by accessory proteins that diffuse away after unbinding. By contrast, bonds in synthetic networks, such as the pendant groups of telechelic polymers, can only rebind in the same location. Using a recently developed theoretical model of the fracturing of visco-elastic materials, we here investigate the effect of linker mobility on the bond dynamics of a network under stress. We find that although mean field properties such as the average bond linker lifetime are barely affected by bond mobility, networks cross linked by mobile bonds fracture more readily due to 'leaking' of linkers from crack areas to less stressed regions within the network. We propose a theoretical model to describe the redistribution of mobile linkers, which we validate by simulations. Our work offers insight into a potential trade-off that cells face, between fracture strength versus the modularity and tight dynamic control offered by mobile linkers.

Transient Topographical Dynamics of the Electroencephalogram Predict Brain Connectivity and Behavioural Responsiveness During Drowsiness

As we fall sleep, our brain traverses a series of gradual changes at physiological, behavioural and cognitive levels, which are not yet fully understood. The loss of responsiveness is a critical event in the transition from wakefulness to sleep. Here we seek to understand the electrophysiological signatures that reflect the loss of capacity to respond to external stimuli during drowsiness using two complementary methods: spectral connectivity and EEG microstates. Furthermore, we integrate these two methods for the first time by investigating the connectivity patterns captured during individual microstate lifetimes. While participants performed an auditory semantic classification task, we allowed them to become drowsy and unresponsive. As they stopped responding to the stimuli, we report the breakdown of alpha networks and the emergence of theta connectivity. Further, we show that the temporal dynamics of all canonical EEG microstates slow down during unresponsiveness. We identify a specific microstate (D) whose occurrence and duration are prominently increased during this period. Employing machine learning, we show that the temporal properties of microstate D, particularly its prolonged duration, predicts the response likelihood to individual stimuli. Finally, we find a novel relationship between microstates and brain networks as we show that microstate D uniquely indexes significantly stronger theta connectivity during unresponsiveness. Our findings demonstrate that the transition to unconsciousness is not linear, but rather consists of an interplay between transient brain networks reflecting different degrees of sleep depth.

Molecular factors governing the viscosity peak of giant micelles in the presence of salt and fragrances

HypothesisThe formation of transient networks of giant micelles leads to a viscosity peak when salt is added to aqueous solutions of charged surfactants. It is the consequence of an increase of the packing parameter due to charge screening of the surfactant headgroups, leading to a continuous transformation of the aggregates from spherical to wormlike micelles, and finally to branched networks. It should therefore be possible to predict the macroscopic viscosity of entangled giant micelles by modelling the packing parameter at nanoscale. ExperimentsA thermodynamic model is presented with a minimum of adjustable parameters, where branched networks are considered to be built from three coexisting microphases: cylinders, endcaps, and junctions. We use spontaneous packing parameters, in which the whole molecular length instead of the commonly used hydrocarbon chain length is considered. Standard reference chemical potentials and subsequently the occurrence of each microphase can be explicitly derived at specific electrolyte concentrations. Effective micellar length of giant micelles can be obtained from the microphase composition and is subsequently used to calculate the viscosity. FindingsThe model successfully predicts position and intensity of the viscosity maximum observed in experimental salt curves of sodium laureth sulfate (SLES). The robustness of the model was further investigated for various types of added salts or fragrance oils that affect differently spontaneous packing parameters or interfacial bending energy. An excellent agreement of the simulated salt curves with experimental data was achieved.

Basalt, Unveiling Fluid-filled Fractures, Inducing Sediment Intra-void Transport, Ephemerally: Examples from Katla 1918

This article documents textures within basaltic Katla 1918 pyroclasts, where particle-filled fractures and bubbles have been observed. These features are analogous to tuffisite veins; particle-filled fractures which represent the preserved remains of transient degassing pathways in shallow conduits.Such fractures have long been considered restricted to high viscosity silicic melts. However, through BSE images and compositional maps, we have identified similar tuffisite-like features in crystal-poor basalt pyroclasts from the 1918 CE subglacial eruption of Katla, Iceland (K1918). Clast textures record transient mobility of juvenile/lithic particles, melt droplets and gas through magmatic fractures and connected vesicles. Key evidence includes (1) the presence of variably sintered fine-ash particles within variably healed fractures and vesicles (present in >80% of clasts analysed), (2) compositional maps that reveal the presence of foreign particles within preserved and healed permeable pathways, and (3) lower vesicularities immediately surrounding ‘fracture’ walls, suggestive of diffusive volatile loss into a permeable network.The 1918 CE eruption of Katla occurred under a thick glacier, however the ice was quickly breached, owing partly to the explosive nature of the eruption. We propose that the formation and preservation of these transient permeable networks have been facilitated by rapid decompression of a relatively volatile-rich magma, in a confined subglacial environment, with combined magmatic and phreatomagmatic fragmentation, followed by rapid quenching by meltwater.Tuffisite veins in rhyolite demonstrate repeated fracture-healing cycles, which drive incremental release of overpressured gas and help to defuse explosive eruptions. Interestingly, the permeable network at Katla failed to defuse the 1918 CE eruption, which involved a particularly violent subglacial eruptive phase. It is unclear whether this demonstrates an inability of mafic tuffisite-like features to efficiently degas magma (perhaps owing to the especially transient nature of permeable pathways in low viscosity magmas) or an ability to enhance fragmentation by providing infiltration pathways for external water. The latter scenario may explain the rapid melting of the overlying glacier as the large surface area-to-volume ratio of fractured magma would allow rapid heat transfer.Nevertheless, we document a previously unrecognised texture in basaltic magmas. It is intriguing why it has not, to the best of our knowledge, been documented elsewhere. Have these permeable pathways been overlooked in the past (e.g. mistaken for bad sample preparation or not noticed without high magnification BSE images) and are in fact a widespread phenomenon in subglacial (and other?) basalts; or do our samples in fact represent a rarely preserved texture? Either way, they offer a new insight into the degassing and fragmentation of subglacial basalt.