Influence of foam thickness on the control of EMG activity during a step-down task in females.

Compliant foams can be used to mitigate ground reaction forces. However, it is unknown how foam surfaces influence the modulation of leg muscle activity. Thus, the current study aimed to investigate how the neuromuscular system managed changes in expected loading due to various thickness of foam placed on the landing surface during a step down task. The surface electromyographic signal (sEMG) pre-activation duration and the root mean square (RMS) amplitude of tibialis anterior (TA), lateral gastrocnemius (LG), and vastus medialis (VM) of 10 active females were measured as they stepped-down with a single leg onto polyurethane foam slabs of varying thickness (0-50 mm). Pre-activation duration was not affected by the thickness of the foam padding. LG RMS amplitude was less in the foam conditions than the control (no- foam) condition, with the greatest reduction observed for the 50 mm foam condition. In some trials, the muscles remained active throughout the step-down task. In such instances, a sEMG onset time and thus a pre-activation duration could not be determined. All foam conditions significantly increased the odds of continuous muscle activity above that of the no-foam condition. The results indicate that foam surfaces may alter the modulation of muscle activity during step-down tasks.

Measurable and Influential Parameters That Influence Corrosion Performance Differences between Multiwall Carbon Nanotube Coating Material Combinations and Model Parent Material Combinations Derived from Epoxy-Amine Matrix Materials.

Protective coatings are often erroneously thought of as perfect environmental barriers for metal substrates; however, a host of corrosion inducing environmental contaminants permeate through defect-free coatings. Carbon nanotubes are high aspect ratio nanofillers with unique mechanical, electrical, and polymer interaction properties with well-established yet, for practical reasons, often unrealized potential. The research objective was to quantify and understand the influential effects and relationships between low concentration levels of multiwall carbon nanotubes (MWCNT) dispersed into epoxy-amine matrix materials and the different water hydrogen bonding interactions on corrosion rates of steel substrates. We hypothesize that when water directly hydrogen bonds with polymer, substrate and/or MWCNTS, the localized water's capacity to transfer environmental contaminants through the coating, i.e., to and from the substrate, diminishes due to a reduced potential to contribute to the formation of water hydration shells and therefore aid in diminishing the corrosion rate. We measured the absolute pre-exposure water content, and monitored to delineate between the ratio and shifting ratio of in situ free versus bound water hydrogen bonding interactions at the coating/air interface using ATR-FTIR spectroscopy in a 5% NaCl fog environment in an attempt to correlate these differences with experimental corrosion rates. Free water content was reduced from ∼20% to <1% of the total water concentration when 1.0 wt % MWCNTs was dispersed into the parent polymer network. Concurrently, the bound water content was measured to shift from ∼2% to >80% with the same MWCNT concentration. The MWCNT bound water resulted in 25% less corrosion for the same steel substrates albeit the measured water vapor diffusivity was the same for each material combination evaluated. Interestingly, the measured pre-exposure bound water content was predictive of which material would corrode slowest and fastest, i.e., the ratio of starting water states seems to be mechanistically related to the corrosion process and the values have potential to predict corrosion rates for a variety of samples evaluated.

Ecofriendly Fabrication of Modified Graphene Oxide Latex Nanocomposites with High Oxygen Barrier Performance.

Large-scale industrial applications of barrier films and coatings that prevent permeation of degradative gases and moisture call for the development of cost-efficient and ecofriendly polymer nanocomposites. Herein, we report the facile fabrication of latex nanocomposites (LNCs) by incorporating surface-modified graphene oxide (mGO) at various loadings (0.025-1.2 wt %) into a styrene-acrylic latex using water as the processing solvent. LNCs fabricated with mGO exhibited significant reductions (up to 67%) in water vapor sorption, resulting in greater environmental stability when compared to LNCs fabricated with equivalent loading of hydrophilic, unmodified GO. The assembly and coalescence of the exfoliated latex/mGO dispersions during the film formation process produced highly dispersed and well-ordered mGO domains with high aspect ratios, where alignment and overlap of the mGO domains improved with increasing mGO content. The addition of only 0.7 vol % (1.2 wt %) mGO led to an 84% decrease (relative to the neat polymer latex film) in oxygen permeability of the LNC films, an excellent barrier performance attributed to the observed LNC film morphologies. This work enables ecofriendly development of mechanically flexible mGO/LNC films with superior barrier properties for many industrial applications including protective coatings, food packaging, and biomedical products.

Impact properties of thiol-ene networks.

In this study, a series of thiol-ene networks having glass transition temperatures ranging from -30 to 60 °C were synthesized utilizing several multifunctional thiols and two trifunctional alkenes. Thermomechanical properties were determined using dynamic mechanical analysis, and impact properties were determined using pendulum impact and drop impact testing protocols. The impact behavior was found to directly correlate to the glass transition temperature, except when the temperature at which the impact event occurs overlaps with the range of temperatures corresponding to the viscoelastic dissipation regime of the polymer. Additionally, we discuss insight into the spatial limitations of energy dissipation for thiol-ene network polymers and establish a platform for predictability in similar systems.