3D printed cellular solid outperforms traditional stochastic foam in long-term mechanical response.

3D printing of polymeric foams by direct-ink-write is a recent technological breakthrough that enables the creation of versatile compressible solids with programmable microstructure, customizable shapes, and tunable mechanical response including negative elastic modulus. However, in many applications the success of these 3D printed materials as a viable replacement for traditional stochastic foams critically depends on their mechanical performance and micro-architectural stability while deployed under long-term mechanical strain. To predict the long-term performance of the two types of foams we employed multi-year-long accelerated aging studies under compressive strain followed by a time-temperature-superposition analysis using a minimum-arc-length-based algorithm. The resulting master curves predict superior long-term performance of the 3D printed foam in terms of two different metrics, i.e., compression set and load retention. To gain deeper understanding, we imaged the microstructure of both foams using X-ray computed tomography, and performed finite-element analysis of the mechanical response within these microstructures. This indicates a wider stress variation in the stochastic foam with points of more extreme local stress as compared to the 3D printed material, which might explain the latter's improved long-term stability and mechanical performance.

Mullins effect in a filled elastomer under uniaxial tension.

Modulus softening and permanent set in filled polymeric materials due to cyclic loading and unloading, commonly known as the Mullins effect, can have a significant impact on their use as support cushions. A quantitative analysis of such behavior is essential to ensure the effectiveness of such materials in long-term deployment. In this work we combine existing ideas of filler-induced modulus enhancement, strain amplification, and irreversible deformation within a simple non-Gaussian constitutive model to quantitatively interpret recent measurements on a relevant PDMS-based elastomeric cushion. We find that the experimental stress-strain data is consistent with the picture that during stretching (loading) two effects take place simultaneously: (1) the physical constraints (entanglements) initially present in the polymer network get disentangled, thus leading to a gradual decrease in the effective cross-link density, and (2) the effective filler volume fraction gradually decreases with increasing strain due to the irreversible pulling out of an initially occluded volume of the soft polymer domain.

Radiation-induced mechanical property changes in filled rubber.

In a recent paper we exposed a filled elastomer to controlled radiation dosages and explored changes in its cross-link density and molecular weight distribution between network junctions [A. Maiti et al., Phys. Rev. E 83, 031802 (2011)]. Here we report mechanical response measurements when the material is exposed to radiation while being under finite nonzero strain. We observe interesting hysteretic behavior and material softening representative of the Mullins effect, and materials hardening due to radiation. The net magnitude of the elastic modulus depends upon the radiation dosage, strain level, and strain-cycling history of the material. Using the framework of Tobolsky's two-stage independent network theory we develop a model that can quantitatively interpret the observed elastic modulus and its radiation and strain dependence.

Convectively driven polymerase chain reaction thermal cycler.

We have fabricated a low-cost disposable polymerase chain reaction thermal chamber that uses buoyancy forces to move the sample solution between the different temperatures necessary for amplification. Three-dimensional, unsteady finite element modeling and a simpler 1-D steady-state model are used together with digital particle image velocimetry data to characterize the flow within the device. Biological samples have been amplified using this novel thermal chamber. Time for amplification is less than 30 min. More importantly, an analysis of the energy consumption shows significant improvements over current technology.