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Absorber layers comprised of shear thickening fluid (STF) intercalated Kevlar® (STF-ArmorTM) are integrated within the standard extra-vehicular activity (EVA) suit and tested for efficacy against both needle puncture and hypervelocity impact (HVI) tests characteristic of micrometeoroids and orbital debris (MMOD). An improvement in puncture resistance against hypodermic needle threats is achieved by substituting STF-ArmorTM in place of neoprene-coated nylon as the absorber layer in the standard EVA suit. The prototype lay-ups containing STF-ArmorTM have the benefit of being 17% thinner and 13% lighter than the standard EVA suit and the ballistic limit is identified in HVI testing. The results here demonstrate that EVA suit lay-ups containing STF-ArmorTM as absorber layers offer meaningful resistance to MMOD threats.

A microfluidic process for producing crystals of controlled size by confining the crystallization within drops is demonstrated. The process consists of a drop producing stage which segments the mother liquor into monodisperse drops followed by crystallization in a temperature controlled tubular crystallizer. The process is implemented to produce lactose crystals with significantly narrower crystal size distribution (CSD) as compared with crystals produced in a stirred bulk crystallizer. By controlling the drop size and initial supersaturation the mean crystal size can be controlled. The distribution of the number of crystals per drop and the CSD are measured as a function of supersaturation at temperatures between 20 and View the MathML source for 150 and View the MathML source drops. In the case where drops contain only one crystal, a very narrow CSD is obtained with a coefficient of variation of crystal size as low as 7%. The crystallization of lactose in a microfluidic tubular crystallizer is modeled by treating nucleation in drops as a Poisson process with a nucleation rate based on classical nucleation theory. Experimental results are in good agreement with predictions from a Poisson process model over the range of temperatures, supersaturations and drop sizes tested.

Drop-based crystallization techniques are used to achieve a high degree of control over crystallization conditions in order to grow high-quality protein crystals for X-ray diffraction or to produce organic crystals with well-controlled size distributions. Simultaneous crystal growth and stochastic nucleation makes it difficult to predict the number and size of crystals that will be produced in a drop-based crystallization process. A mathematical model of crystallization in drops is developed using a Monte Carlo method. The model incorporates key phenomena in drop-based crystallization, including stochastic primary nucleation and growth rate dispersion (GRD) and can predict distributions of the number of crystals per drop and full crystal size distributions (CSD). Key dimensionless parameters are identified to quickly screen for crystallization conditions that are expected to yield a high fraction of drops containing one crystal and a narrow CSD. Using literature correlations for the solubilities, growth, and nucleation rates of lactose and lysozyme, the model is able to predict the experimentally observed crystallization behavior over a wide range of conditions. Model-based strategies for use in the design and optimization of a drop-based crystallization process for producing crystals of well-controlled CSD are identified.