Smart soft materials, because of their mechanical flexibility and quick response to multi-physics stimuli, have drawn considerable attention over the past few years. Here, we present controllable wrinkling patterns of a liquid crystal polymer film attached on a soft substrate, controlled by laser illumination that holds unique optical characteristics of high coherence and irradiance.

The mechanical behavior of athermal random fiber networks embedding particulate inclusions is studied in this work. Composites in which the filler size is comparable with the mean segment length of the network are considered. Inclusions are randomly distributed in the network at various volume fractions, and cases in which fibers are rigidly bonded to fillers and in which no such bonding is imposed are studied separately. In the presence of inclusions, the small strain modulus increases, while the ability of the network to strain stiffen decreases relative to the unfilled network case.

Amit Acharya          Shankar Venkataramani

 (In Materials Theory)

Growth processes in many living organisms create thin, soft materials with an intrinsically hyperbolic
geometry. These objects support novel types of mesoscopic defects - discontinuity lines
for the second derivative and branch points - terminating defects for these line discontinuities.
These higher-order defects move "easily", and thus confer a great degree of
flexibility to thin hyperbolic elastic sheets. We develop a general, higher-order, continuum mechanical framework
from which we can derive the dynamics of higher order defects in a thermodynamically consistent
manner. We illustrate our framework by obtaining the explicit equations for the dynamics
of branch points in an elastic body.

https://www.researchgate.net/publication/333877242_Continuum_mechanics_of_moving_defects_in_growing_bodies

The group on “Mechanics of soft and living interfaces” (https://www.lacan.upc.edu/mechanics-of-soft-and-living-interfaces/) lead by Marino Arroyo (https://www.lacan.upc.edu/arroyo/) is looking for a highly motivated and creative postdoctoral researcher to study the mechanical organization of epithelial cells and tissues, and how this understanding can lead to a precise control of tissue structure, mechanical properties, and dynamics.

We've recently published our new study about Uncertainty Quantification in Molecular Dynamics (MD) Simulations. Due to the selection of functional forms of interatomic potentials or the numerical approximation, MD simulations may predict different material behavior from experiments or other high-fidelity results. In this study, we used Stochastic Reduced Order Modeling (SROM) to achieve

(1) mechanical behavior of graphene predicted by MD simulations in good agreement with the continuum model which has been calibrated by experiments;

Composite materials are increasingly used in industry due to the possibility of tailoring their properties based on the applications. Their greatest advantage is strength and stiffness combined with lightness. However, their optimal design and performance is still limited by the lack of knowledge of physical mechanisms that control their fracture behavior. Machine learning and big data driven approaches have not been extensively studied for fracture behavior predictions.

The focus of this symposium is to discuss current research and key developments in theory, computational and experimental methods to study and predict the mechanical properties of materials in application-orientated environments. These environments may include, but are not limited to high temperature, cryogenic temperature, electrical and magnetic field, gas, radiation, chemical, pressure extremes, and humidity.