Growth factor-eluting polymer systems have been widely reported to improve cell and tissue outcomes; however, measurements of actual growth factor concentration in cell culture conditions are ...limited. The problem is compounded by a lack of knowledge of growth factor half-lives, which impedes efforts to determine real-time growth factor concentrations. In this work, the half-life of basic fibroblast growth factor (FGF2) was determined using enzyme linked immunosorbent assay (ELISA). FGF2 release from polyelectrolyte multilayers (PEMs) was measured and the data was fit to a simple degradation model, allowing for the determination of FGF2 concentrations between 2 and 4 days of culture time. After the first hour, the FGF2 concentration for PEMs assembled at pH = 4 ranged from 2.67 ng/mL to 5.76 ng/mL, while for PEMs assembled at pH = 5, the concentration ranged from 0.62 ng/mL to 2.12 ng/mL. CRL-2352 fibroblasts were cultured on PEMs assembled at pH = 4 and pH = 5. After 2 days, the FGF2-eluting PEM conditions showed improved cell count and spreading. After 4 days, only the pH = 4 assembly condition had higher cells counts, while the PEM assembled at pH = 5 and PEM with no FGF2 showed increased spreading. Overall, the half-life model and cell culture study provide optimal concentration ranges for fibroblast proliferation and a framework for understanding how temporal FGF2 concentration may affect other cell types.
Bonding in additive manufacturing (AM) remains a key challenge in improving part properties. For thermally driven AM methods, such as material extrusion AM (MatEx), temperature governs bonding. ...Experimental measurements of temperature are limited in their ability to probe many points in space and time during a process without disturbing the temperature profiles being measured. These limitations may be overcome with computational methods; however, computing power considerations confined simulations to one or two dimensions until recently. Additionally, most existing models have had only limited ability to modify geometry or process parameters. In this work, an adaptable FEA model capable of simulating heat transfer in 3D and at sufficiently small time scales to capture the rapid cooling in AM is presented. Cooling trends from simulation are shown to be in agreement with experimental data. Temperature profiles are collapsed to equivalent time at a reference temperature and predict little variation in bonding along the z-axis of a part or with changes in print speed. A previously unreported peak in cooling rates for print speeds between 10 and 30 mm/s is shown. Uniformity in equivalent time at Tg suggests weld strength will not vary with print speed; however, high cooling rates for common print speeds may lead to greater residual stresses and reduced mechanical properties.
This study investigated the novel fabrication of polymer-metal composites using fused deposition modeling (FDM), and evaluated the mechanical and physical properties of the new materials. ...Specifically, an acrylonitrile butadiene styrene (ABS) – 420 stainless steel (SS) composite system was used, with 10, 15, and 23 wt% SS powder additions, and the resulting properties were compared to those of base ABS prepared using the same printing conditions. A new methodology to fabricate the composites was developed. The resulting materials were extruded into composite filaments, which were used to print test specimens. Tensile testing, modulated differential scanning calorimetry, and scanning electron microscopy were employed to characterize the composite materials and evaluate the effects of different print conditions. The results demonstrate, for the first time, the feasibility of using FDM to prepare ABS-SS composites that maintain or enhance mechanical properties as compared to the base polymer, while adding increased functionality.
Economic and environmental costs are assessed for four different plastics manufacturing processes, including cold and hot runner molding as well as stock and upgraded material extrusion three ...dimensional (3D) printers. A larger stock 3D printer was found to provide a melting capacity of 14.4 ml/h, while a smaller printer with an upgraded extruder had a melting capacity of 36 ml/h. 3D printing at these maximum melting capacities resulted in specific energy consumption (SEC) of 16.5 and 5.28 kWh/kg, respectively, with the latter value being less than 50% of the lowest values reported in the literature. Even so, analysis of these respective processes found them to be only 2.9% and 3.8% efficient relative to their theoretical minimum energy requirements. By comparison, cold and hot runner molding with an all‐electric machine had SEC of 1.28 and 0.929 kWh/kg, respectively, with efficiencies of 9.9% and 13.6% relative to the theoretical minima. Breakeven analysis considering the cost and carbon footprint of mold tooling found injection molding was preferable at a production quantity of around 70,000 units. Parametric analysis of model inputs indicates that the breakeven quantities are robust with respect to carbon tax incentives but highly dependent on mold costs, labor costs, and part size. Dimensional and mechanical properties of the molded and 3D printed specimens are also characterized and discussed.
Strategic cost and sustainability analysis compares efficient molding and 3D printing processes. Even with a record low specific energy consumption of 5.28 kWh/kg, 3D printing is only 3.5% efficient compared to theoretical minima. All‐electric injection molding was found to be 9.9% efficient for a cold runner mold and 13.6% efficient for a hot runner mold but requires 70,000 units to warrant upfront equipment investments.
Abstract
Mechanical properties of additively manufactured structures fabricated using material extrusion additive manufacturing are predicted through combining thermal modeling with entanglement ...theory and molecular dynamics approaches. A one-dimensional model of heat transfer in a single road width wall is created and validated against both thermography and mechanical testing results. Various model modifications are investigated to determine which heat transfer considerations are important to predicting properties. This approach was able to predict tear energies on reasonable scales with minimal information about the polymer. Such an approach is likely to be applicable to a wide range of amorphous and low crystallinity thermoplastics.
A self-healing epoxy-amine thermoset based on the compatible functionalization of the thermoset and encapsulated healing agent has been successfully developed. Healing of the thermoset resulted from ...the reaction of furans in the thermoset and multimaleimides (MMIs) in the healing agent solution. The healing agent, MMI dissolved in phenyl acetate, was encapsulated using a urea-formaldehyde encapsulation method. Autonomic healing of the thermoset was achieved by incorporating microcapsules filled with the healing agent solution within a furan-functionalized epoxy-amine thermoset. The resulting self-healing thermoset recovered 71% of its initial load after fracture.
Machine learning techniques were used to predict tensile properties of material extrusion-based additively manufactured parts made with Technomelt PA 6910, a hot melt adhesive. An adaptive data ...generation technique, specifically an active learning process based on the Gaussian process regression algorithm, was employed to enable prediction with limited training data. After three rounds of data collection, machine learning models based on linear regression, ridge regression, Gaussian process regression, and K-nearest neighbors were tasked with predicting properties for the test dataset, which consisted of parts fabricated with five processing parameters chosen using a random number generator. Overall, linear regression and ridge regression successfully predicted output parameters, with < 10% error for 56% of predictions. K-nearest neighbors performed worse than linear regression and ridge regression, with < 10% error for 32% of predictions and 10-20% error for 60% of predictions. While Gaussian process regression performed with the lowest accuracy (< 10% error for 32% of prediction cases and 10-20% error for 40% of predictions), it benefited most from the adaptive data generation technique. This work demonstrates that machine learning models using adaptive data generation techniques can efficiently predict properties of additively manufactured structures with limited training data.
Water plays an important role in the structure and properties of polyelectrolyte-based materials. In this study, the effect of humidity history on the structure and properties of dried ...polyelectrolyte complexes (PECs) was explored. PECs were assembled from poly(diallyldimethylammonium chloride) and poly(sodium 4-styrenesulfonate) solutions and then dried under controlled humidity conditions. After exposure to higher humidities (humidity tempering), both room temperature storage modulus and flexural modulus of the resulting PEC increased. Water from the humid air plasticized the PEC, increasing mobility and facilitating chain reorganization during humidity tempering, which resulted in a structure with more intrinsic electrostatic bonds (cross-links) and higher moduli. Humidity tempering can achieve a 35% increase in PEC stiffness during room temperature processing with water as the only solvent. Based on these results, humidity tempering is presented as a novel approach to tailoring the structure and mechanical properties of polyelectrolyte-based materials under mild conditions, which makes this approach very appealing to biomaterials and controlled release.
Self-healing materials are particularly desirable for load-bearing applications because they offer the potential for increased safety and material lifetimes. A furan-functionalized polymer network ...was designed that can heal via covalent bonding across the crack surface with the use of a healing agent consisting of a bismaleimide in solution. Average healing efficiencies of approximately 70% were observed. The healing ability of fiber-reinforced composite specimens was investigated with flexural, short beam shear, and double cantilever beam specimens. It was found that solvent amount and maleimide concentration play key roles in determining healing efficiency.
The change from wet and soft to dry and hard is a viscoelastic to solid material transition widely displayed in nature, in particular in materials rich in metal-coordinate cross-linking. How ...metal-coordinate cross-link dynamics contribute to macromolecular material mechanics upon solidification by dehydration remains an open question. Using mussel-inspired Fe-catechol cross-linked polymer hydrogels, we address this question. In addition to a nearly 2-fold increase in stiffness, we find that the presence of Fe-catechol coordination bonds in a dehydrated polymer gel also provides the bulk network with a significantly increased energy dissipation with over three times higher loss factor. We present evidence to suggest that small amounts (∼4 wt %) of locally bound water maintain the dynamic nature of Fe-catechol coordinate cross-links in a dehydrated polymer network. The dehydration-induced polymer material mechanics presented here may provide deeper insights on the biological utilization of metal-coordinate cross-link dynamics as well as inspire new ideas on sustainable materials engineering.
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