Thawed matrix method for computing local mechanical properties of amorphous solids.

We present a method for computing locally varying nonlinear mechanical properties in particle simulations of amorphous solids. Plastic rearrangements outside a probed region are suppressed by introducing an external field that directly penalizes large nonaffine displacements. With increasing strength of the field, plastic deformation can be localized. We characterize the distribution of local plastic yield stresses (residual local stresses to instability) with our approach and assess the correlation of their spatial maps with plastic activity in a model two-dimensional amorphous solid. Our approach reduces artifacts inherent in a previous method known as the "frozen matrix" approach that enforces fully affine deformation and improves the prediction of plastic rearrangements from structural information.

Stress overshoot, hysteresis, and the Bauschinger effect in sheared dense colloidal suspensions.

The mechanical nonlinear response of dense Brownian suspensions of polymer gel particles is studied experimentally and by means of numerical simulations. It is shown that the response to the application of a constant shear rate depends on the previous history of the suspension. When the flow starts from a suspension at rest, it exhibits an elastic response followed by a stress overshoot and then a plastic flow regime. Conversely, after flow reversal, the stress overshoot does not occur, and the apparent elastic modulus is reduced while numerical simulations reveal that the anisotropy of the local microstructure is delayed relative to the macroscopic stress.

Computational indentation in highly cross-linked polymer networks.

Indentation is a common experimental technique to study the mechanics of polymeric materials. The main advantage of using indentation is this provides a direct correlation between the microstructure and the small-scale mechanical response, which is otherwise difficult within the standard tensile testing. The majority of studies have investigated hydrogels, microgels, elastomers, and even soft biomaterials. However, a less investigated system is the indentation in highly cross-linked polymer (HCP) networks, where the complex network structure plays a key role in dictating their physical properties. In this work, we investigate the structure-property relationship in HCP networks using the computational indentation of a generic model. We establish a correlation between the local bond breaking, network rearrangement, and small-scale mechanics. The results are compared with the elastic-plastic deformation model. HCPs harden upon indentation.

Signatures of the spatial extent of plastic events in the yielding transition in amorphous solids.

Amorphous solids are yield stress materials that flow when a sufficient load is applied. Their flow consists of periods of elastic loading interrupted by rapid stress drops, or avalanches, coming from microscopic rearrangements known as shear transformations (STs). Here we show that the spatial extent of avalanches in a steadily sheared amorphous solid has a profound effect on the distribution of local residual stresses that in turn determines the stress drop statistics. As reported earlier, the most unstable sites are located in a flat "plateau" region that decreases with system size. While the entrance into the plateau is set by the lower cutoff of the mechanical noise produced by individual STs, the departure from the usually assumed power-law (pseudogap) form of the residual stress distribution comes from far field effects related to spatially extended rearrangements. Interestingly, we observe that the average residual stress of the weakest sites is located in an intermediate power-law regime between the pseudogap and the plateau regimes, whose exponent decreases with system size. Our findings imply a new scaling relation linking the exponents characterizing the avalanche size and residual stress distributions.

Ripple-like instability in the simulated gel phase of finite size phosphocholine bilayers.

Atomistic molecular dynamics simulations have reached a degree of maturity that makes it possible to investigate the lipid polymorphism of model bilayers over a wide range of temperatures. However if both the fluid Lα and tilted gel [Formula: see text] states are routinely obtained, the [Formula: see text] ripple phase of phosphatidylcholine lipid bilayers is still unsatifactorily described. Performing simulations of lipid bilayers made of different numbers of DPPC (1,2-dipalmitoylphosphatidylcholine) molecules ranging from 32 to 512, we demonstrate that the tilted gel phase [Formula: see text] expected below the pretransition cannot be obtained for large systems (equal or larger than 94 DPPC molecules) through common simulations settings or temperature treatments. Large systems are instead found in a disordered gel phase which display configurations, topography and energies reminiscent from the ripple phase [Formula: see text] observed between the pretransition and the main melting transition. We show how the state of the bilayers below the melting transition can be controlled and depends on thermal history and conditions of preparations. A mechanism for the observed topographic instability is suggested.

MLLPA: A Machine Learning-assisted Python module to study phase-specific events in lipid membranes.

Machine Learning-assisted Lipid Phase Analysis (MLLPA) is a new Python 3 module developed to analyze phase domains in a lipid membrane based on lipid molecular states. Reading standard simulation coordinate and trajectory files, the software first analyze the phase composition of the lipid membrane by using machine learning tools to label each individual molecules with respect to their state, and then decompose the simulation box using Voronoi tessellations to analyze the local environment of all the molecules of interest. MLLPA is versatile as it can read from multiple format (e.g., GROMACS, LAMMPS) and from either all-atom (e.g., CHARMM36) or coarse-grain models (e.g., Martini). It can also analyze multiple geometries of membranes (e.g., bilayers, vesicles). Finally, the software allows for training with more than two phases, allowing for multiple phase coexistence analysis.

Residual stress distributions in amorphous solids from atomistic simulations.

The distribution of local residual stresses (threshold to instability) that controls the statistical properties of plastic flow in athermal amorphous solids is examined with an atomistic simulation technique. For quiescent configurations, the distribution has a pseudogap (power-law) form with an exponent that agrees well with global yielding statistics. As soon as deformation sets in, the pseudogap region gives way to a system size dependent plateau at small residual stresses that can be understood from the statistics of local residual stress differences between plastic events. Results further suggest that the local yield stress in amorphous solids changes even if the given region does not participate in plastic activity.

A machine learning study of the two states model for lipid bilayer phase transitions.

We have adapted a set of classification algorithms, also known as machine learning, to the identification of fluid and gel domains close to the main transition of dipalmitoyl-phosphatidylcholine (DPPC) bilayers. Using atomistic molecular dynamics conformations in the low and high temperature phases as learning sets, the algorithm was trained to categorise individual lipid configurations as fluid or gel, in relation with the usual two-states phenomenological description of the lipid melting transition. We demonstrate that our machine can learn and sort lipids according to their most likely state without prior assumption regarding the nature of the order parameter of the transition. Results from our machine learning study provide strong support in favour of a two-states model approach of membrane fluidity.

Controlling Marangoni-induced instabilities in spin-cast polymer films: How to prepare uniform films.

In both research and industrial settings spincoating is extensively used to prepare highly uniform thin polymer films. However, under certain conditions, spincoating results in films with non-uniform surface morphologies. Although the spincoating process has been extensively studied, the origin of these morphologies is not fully understood and the formation of non-uniform spin-cast films remains a practical problem. Here we report on experiments demonstrating that the formation of surface instabilities during spincoating is dependent on temperature. Our results suggest that non-uniform spin-cast films form as a result of the Marangoni effect, which describes flow due to surface tension gradients. We find that both the wavelength and amplitude of the pattern increase with temperature. Finally, and most important from a practical viewpoint, the non-uniformities in the film thickness can be entirely avoided simply by lowering the spin coating temperature.