Softening and Yielding of Soft Glassy Materials

Solids deform and fluids flow, but soft glassy materials, such as emulsions, foams, suspensions, and pastes, exhibit an intricate mix of solid and liquid-like behavior. While much progress has been made to understand their elastic (small strain) and flow (infinite strain) properties, such understanding is lacking for the softening and yielding phenomena that connect these asymptotic regimes. Here we present a comprehensive framework for softening and yielding of soft glassy materials, based on extensive numerical simulations of oscillatory rheological tests, and show that two distinct scenarios unfold depending on the material's packing density. For dense systems, there is a single, pressure-independent strain where the elastic modulus drops and the particle motion becomes diffusive. In contrast, for weakly jammed systems, a two-step process arises: at an intermediate softening strain, the elastic and loss moduli both drop down and then reach a new plateau value, whereas the particle motion becomes diffusive at the distinctly larger yield strain. We show that softening is associated with an extensive number of microscopic contact changes leading to a non-analytic rheological signature. Moreover, the scaling of the softening strain with pressure suggest the existence of a novel pressure scale above which softening and yielding coincide, and we verify the existence of this crossover scale numerically. Our findings thus evidence the existence of two distinct classes of soft glassy materials -- jamming dominated and dense -- and show how these can be distinguished by their rheological fingerprint.Comment: 9 pages, 11 figures, to appear in Soft Matte

Finite-Size Scaling at the Jamming Transition

We present an analysis of finite-size effects in jammed packings of N soft, frictionless spheres at zero temperature. There is a 1/N correction to the discrete jump in the contact number at the transition so that jammed packings exist only above isostaticity. As a result, the canonical power-law scalings of the contact number and elastic moduli break down at low pressure. These quantities exhibit scaling collapse with a non-trivial scaling function, demonstrating that the jamming transition can be considered a phase transition. Scaling is achieved as a function of N in both 2 and 3 dimensions, indicating an upper critical dimension of 2.Comment: 5 pages, 3 figure

Soft Sphere Packings at Finite Pressure but Unstable to Shear

When are athermal soft sphere packings jammed ? Any experimentally relevant definition must at the very least require a jammed packing to resist shear. We demonstrate that widely used (numerical) protocols in which particles are compressed together, can and do produce packings which are unstable to shear - and that the probability of generating such packings reaches one near jamming. We introduce a new protocol that, by allowing the system to explore different box shapes as it equilibrates, generates truly jammed packings with strictly positive shear moduli G. For these packings, the scaling of the average of G is consistent with earlier results, while the probability distribution P(G) exhibits novel and rich scalingComment: 5 pages, 6 figures. Resubmitted to Physical Review Letters after a few change

Contact Changes near Jamming

We probe the onset and effect of contact changes in soft harmonic particle packings which are sheared quasistatically. We find that the first contact changes are the creation or breaking of contacts on a single particle. We characterize the critical strain, statistics of breaking versus making a contact, and ratio of shear modulus before and after such events, and explain their finite size scaling relations. For large systems at finite pressure, the critical strain vanishes but the ratio of shear modulus before and after a contact change approaches one: linear response remains relevant in large systems. For finite systems close to jamming the critical strain also vanishes, but here linear response already breaks down after a single contact change.Comment: 5 pages, 4 figure

Transfer learning for a multimodal hybrid EEG-FTCD Brain-Computer Interface

Transfer learning has been used to overcome the limitations of machine learning in Brain-Computer Interface (BCI) applications. Transfer learning aims to provide higher performance than no-transfer machine learning when only a limited number of training data is available and can consequently reduce training and calibration requirements. BCI systems are designed to provide communication and control tools for individuals with limited speech and physical abilities (LSPA). Most noninvasive BCI systems are based on Electroencephalogram (EEG) because of EEG \textquotesingle s cost effectiveness and portability. However, EEG signals present low signal-to-noise ratio and nonstationarity due to background brain activity. Such a behavior may decrease the global performance of the system. To overcome the disadvantages of EEG signals, in our previous work, we developed two different multi-modal BCI systems based on EEG and functional transcranial Doppler (fTCD), a cerebral flood velocity measure. These two multi-modal systems that combine EEG and fTCD signals aim to reduce performance degradation obtained when EEG was the only BCI modality. One of the systems is based on steady state evoked potentials and the other one is designed using motor imagery paradigms. Our results have shown that such a hybrid system outperforms EEG only BCIs. However, both systems require significant amount of training data for personalized design which could be tiresome for the target population. In this study, we extend these systems by performing a new transfer learning algorithm and we demonstrate the corresponding algorithm on the three different binary classification tasks for both BCIs in order to reduce the calibration requirements. Performing experiments with healthy participants, we collected EEG and fTCD data using both BCI systems. In order to apply transfer learning and to reduce the calibration requirements for BCIs, for each participant, we identify the most informative datasets from the rest of the participants based on probabilistic similarities between the class conditional distributions and increase the training set from this data. We demonstrate that transfer learning reduces the calibration requirements up to \%87.5 for BCI systems. Also, through comparison between different classifiers LDA, QDA, and SVM, we observe that QDA achieves the higher difference between transfer learning and no transfer accuracy

Mesoscopic structure of dry-pressed clay samples from small-angle X-ray scattering measurements . In : Proceedings of the XIIIth International Conference on Small-Angle Scattering

Weakly hydrated samples of platelet-shaped nano-particles obtained by dry-pressing suspensions of the synthetic Na fluorohectorite clay are studied. The particles consist of stacks of several tens of 1 nm-thick nanosilicate platelets. They form a compound of quasi-two-dimensional particles whose average director is aligned with the direction of the uniaxial stress applied at dehydration. Small-angle X-ray scattering images from these samples are either isotropic or anisotropic, depending on the sample orientation with respect to the X-ray beam. From anisotropic images, changes in the scattering objects' orientation distribution probability (ODP) function are investigated as the temperature is lowered, thus triggering swelling of the individual particles by water intercalation. This is done, on the one hand, by inferring the width of the ODP function from the eccentricity of quasi-elliptic iso-intensity cuts of the small-angle scattering images, and, on the other hand, by obtaining the ODP function from azimuthal profiles of the images. The decays of the scattering intensity as a function of momentum transfer along the two principal directions of the images exhibit power law behaviors. A crossover scale between two power law regimes is observed on the profiles recorded along the horizontal axis; it corresponds to the typical pore size along the direction of the initially applied load. These results are compared with a previous study of similar systems

Jamming in finite systems: stability, anisotropy, fluctuations and scaling

Athermal packings of soft repulsive spheres exhibit a sharp jamming transition in the thermodynamic limit. Upon further compression, various structural and mechanical properties display clean power-law behavior over many decades in pressure. As with any phase transition, the rounding of such behavior in finite systems close to the transition plays an important role in understanding the nature of the transition itself. The situation for jamming is surprisingly rich: the assumption that jammed packings are isotropic is only strictly true in the large-size limit, and finite-size has a profound effect on the very meaning of jamming. Here, we provide a comprehensive numerical study of finite-size effects in sphere packings above the jamming transition, focusing on stability as well as the scaling of the contact number and the elastic response.Comment: 20 pages, 12 figure

Rheology of Dense Suspensions of Non-Colloidal Particles in Yield-Stress Fluids

Pressure-imposed rheometry is used to study the rheological properties of suspensions of non-colloidal spheres in yield stress fluids. Accurate measurements for both the shear stress and particle normal stress are obtained in the dense regime. The rheological measurements are favourably compared to a model based on scaling arguments and homogenisation methods