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At least 541 records · Page 30

Advances in Electrospun Poly(ε-caprolactone)-Based Nanofibrous Scaffolds for Tissue Engineering

Tissue engineering has great potential for the restoration of damaged tissue due to injury or disease. During tissue development, scaffolds provide structural support for cell growth. To grow healthy tissue, the principal components of such scaffolds must be biocompatible and nontoxic. Poly(ε-caprolactone) (PCL) is a biopolymer that has been used as a key component of composite scaffolds for tissue engineering applications due to its mechanical strength and biodegradability. However, PCL alone can have low cell adherence and wettability. Blends of biomaterials can be incorporated to achieve synergistic scaffold properties for tissue engineering. Electrospun PCL-based scaffolds consist of single or blended-composition nanofibers and nanofibers with multi-layered internal architectures (i.e., core-shell nanofibers or multi-layered nanofibers). Nanofiber diameter, composition, and mechanical properties, biocompatibility, and drug-loading capacity are among the tunable properties of electrospun PCL-based scaffolds. Scaffold properties including wettability, mechanical strength, and biocompatibility have been further enhanced with scaffold layering, surface modification, and coating techniques. In this article, we review nanofibrous electrospun PCL-based scaffold fabrication and the applications of PCL-based scaffolds in tissue engineering as reported in the recent literature.

Polymer Science↗

Tensile Modeling PVC Gels for Electrohydraulic Actuators

Polyvinyl chloride (PVC)-dibutyl adipate (DBA) gels are a fascinating dielectric elastomer actuator showing promise in soft robotics. When actuated with high voltages, the gel deforms towards the anode. A recent application of PVC gels in electrohydraulic actuators motivates elastic and hyperelastic constitutive relationships for tensile loading modes. PVC gels with plasticizer-to-polymer weight ratios of 2:1, 4:1, 6:1, and 8:1 w/w were evaluated. PVC gels exhibit a linear elastic region up to 25% strain. The elastic modulus decreased with increasing plasticizer content from 288.8 kPa, 56.1 kPa, 24.7 kPa, to 11 kPa. Poisson’s ratio also decreased with increasing plasticizer content from 0.42, 0.43, 0.39, to 0.35. We suggest that the decrease in polymer concentration facilitates a weakly interconnected polymer network susceptible to chain slippage that hinders the network response, thus lowering Poisson’s ratio. Our work suggests that PVC gels can be treated as isotropic and incompressible for large strains and hyperelastic modeling; however, highly plasticized gels tend to act less incompressible at small strains. The power scaling law between the elastic modulus and plasticizer weight ratio showed high agreement, making the elastic modulus deterministic for any plasticizer content. The Neo–Hookean, Mooney–Rivlin, Yeoh, Gent, Ogden, and extended tube hyperelastic constitutive models are investigated. The Yeoh model shows the highest feasibility when evaluated up to 3.5 stretch, showing a maximum normalized root-mean-square-error of 6.85%. Together, these findings establish a constitutive basis for PVC-DBA gels, incorporating small strain elasticity, large strain non-linear behavior, and network analysis while providing suggestive insight into the network structure required for accurately modeling the EPIC.

Polymer Science↗

Deep learning potential of mean force between polymer grafted nanoparticles

Grafting polymer chains on the surfaces of nanoparticles is a well-known route to control their self-assembly and distribution in a polymer matrix. A wide variety of self-assembled structures are achieved by changing the grafting patterns on the surface of an individual nanoparticle. However, an accurate estimation of the effective potential of mean force between a pair of grafted nanoparticles that determines their assembly and distribution in a polymer matrix is an outstanding challenge in nanoscience. We address this problem via deep learning. As a proof of concept, here we report a deep learning framework that learns the interaction between a pair of single-chain grafted spherical nanoparticles from their molecular dynamics trajectory. Subsequently, we carry out the deep learning potential of mean force-based molecular simulation that predicts the self-assembly of a large number of single-chain grafted nanoparticles into various anisotropic superstructures, including percolating networks and bilayers depending on the nanoparticle concentration in three-dimensions. The deep learning potential of mean force-predicted self-assembled superstructures are consistent with the actual superstructures of single-chain polymer grafted spherical nanoparticles. This deep learning framework is very generic and extensible to more complex systems including multiple-chain grafted nanoparticles. Finally, we expect that this deep learning approach will accelerate the characterization and prediction of the self-assembly and phase behaviour of polymer-grafted and unfunctionalized nanoparticles in free space or a polymer matrix.

36 MATERIALS SCIENCE↗

Electronic materials high-T(sub c) superconductivity polymers and composites structural materials surface science and catalysts industry participation

The fifth year of the Center for Advanced Materials was marked primarily by the significant scientific accomplishments of the research programs. The Electronics Materials program continued its work on the growth and characterization of gallium arsenide crystals, and the development of theories to understand the nature and distribution of defects in the crystals. The High Tc Superconductivity Program continued to make significant contributions to the field in theoretical and experimental work on both bulk materials and thin films and devices. The Ceramic Processing group developed a new technique for cladding YBCO superconductors for high current applications in work with the Electric Power Research Institute. The Polymers and Composites program published a number of important studies involving atomistic simulations of polymer surfaces with excellent correlations to experimental results. The new Enzymatic Synthesis of Materials project produced its first fluorinated polymers and successfully began engineering enzymes designed for materials synthesis. The structural Materials Program continued work on novel alloys, development of processing methods for advanced ceramics, and characterization of mechanical properties of these materials, including the newly documented characterization of cyclic fatigue crack propagation behavior in toughened ceramics. Finally, the Surface Science and Catalysis program made significant contributions to the understanding of microporous catalysts and the nature of surface structures and interface compounds.

Source record↗

Polymer informatics: Current status and critical next steps

Artificial intelligence (AI) based approaches are beginning to impact several domains of human life, science and technology. Polymer informatics is one such domain where AI and machine learning (ML) tools are being used in the efficient development, design and discovery of polymers. Surrogate models are trained on available polymer data for instant property prediction, allowing screening of promising polymer candidates with specific target property requirements. Questions regarding synthesizability, and potential (retro)synthesis steps to create a target polymer, are being explored using statistical means. Data-driven strategies to tackle unique challenges resulting from the extraordinary chemical and physical diversity of polymers at small and large scales are being explored. Other major hurdles for polymer informatics are the lack of widespread availability of curated and organized data, and approaches to create machine-readable representations that capture not just the structure of complex polymeric situations but also synthesis and processing conditions. Methods to solve inverse problems, wherein polymer recommendations are made using advanced AI algorithms that meet application targets, are being investigated. As various parts of the burgeoning polymer informatics ecosystem mature and become integrated, efficiency improvements, accelerated discoveries and increased productivity can result. Here in this paper, we review emergent components of this polymer informatics ecosystem and discuss imminent challenges and opportunities.

36 MATERIALS SCIENCE↗

Effect of processing on Polymer/Composite structure and properties

Advances in the vitality and economic health of the field of polymer forecasting are discussed. A consistent and rational point of view which considers processing as a participant in the underlying triad of relationships which comprise materials science and engineering is outlined. This triad includes processing as it influences material structure, and ultimately properties. Methods in processing structure properties, polymer science and engineering, polymer chemistry and synthesis, structure and modification and optimization through processing, and methods of melt flow modeling in processing structure property relations of polymer were developed. Mechanical properties of composites are considered, and biomedical materials research to include polymer processing effects are studied. An analysis of the design technology of advances graphite/epoxy composites is also reported.

Source record↗

Dynamic behavior of chemically tunable mechano-responsive hydrogels

Here, using theory and simulation, we model the mechanical behavior of gels that encompass loops and dangling chain ends. If the loops remain folded and dangling ends are chemically inert, then these topological features just serve as defects. If, however, the loops unfold to expose the hidden (“cryptic”) binding sites and the ends of the dangling chains are reactive, these moieties can form bonds that improve the gel's mechanical properties. For gels with a lower critical solubility temperature (LCST), we systematically switch on the possible unfolding and binding events. To quantify the resulting effects, we derive equations for the gel's equilibrium and dynamic elastic moduli. We also use a finite element approach to simulate the gel's response to deformation and validate the analytic calculations. Herein, we show that the equilibrium moduli are highly sensitive to the presence of unfolding and binding transitions. The dynamical moduli are sensitive not only to these structural changes, but also to the frequency of deformation. For example, when reactive ends bind to exposed cryptic sites at T = 29 °C and relatively high frequency, the storage shear modulus is 119% greater than the corresponding equilibrium value, while the storage Young's modulus is 109% greater than at equilibrium. These findings provide guidelines for tuning the chemical reactivity of loops and dangling ends and the frequency of deformation to tailor the mechano-responsive behavior of polymer networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A microfluidic platform for the synthesis of polymer and polymer-protein-based protocells

In this study, we demonstrate the fabrication of polymersomes, protein-blended polymersomes, and polymeric microcapsules using droplet microfluidics. Polymersomes with uniform, single bilayers and controlled diameters are assembled from water-in-oil-in-water double-emulsion droplets. This technique relies on adjusting the interfacial energies of the droplet to completely separate the polymer-stabilized inner core from the oil shell. Protein-blended polymersomes are prepared by dissolving protein in the inner and outer phases of polymer-stabilized droplets. Cell-sized polymeric microcapsules are assembled by size reduction in the inner core through osmosis followed by evaporation of the middle phase. All methods are developed and validated using the same glass-capillary microfluidic apparatus. This integrative approach not only demonstrates the versatility of our setup, but also holds significant promise for standardizing and customizing the production of polymer-based artificial cells.

36 MATERIALS SCIENCE↗

Engineering stability, longevity, and miscibility of microtubule-based active fluids

Microtubule-based active matter provides insight into the self-organization of motile interacting constituents. In this work, we describe several formulations of microtubule-based 3D active isotropic fluids. Dynamics of these fluids is powered by three types of kinesin motors: a processive motor, a non-processive motor, and a motor which is permanently linked to a microtubule backbone. Another modification uses a specific microtubule crosslinker to induce bundle formation instead of a non-specific polymer depletant. In comparison to the already established system, each formulation exhibits distinct properties. These developments reveal the temporal stability of microtubule-based active fluids while extending their reach and the applicability.

36 MATERIALS SCIENCE↗

Sodium dodecyl sulfate modulates the structure and rheological properties of Pluronic F108–poly(acrylic acid) coacervates)

Micelles formed within coacervate phases can impart functional properties, but it is unclear if this micellization provides mechanical reinforcement of the coacervate whereby the micelles act as high functionality crosslinkers. Here, we examine how sodium dodecyl sulfate (SDS) influences the structure and properties of Pluronic F108–polyacrylic acid (PAA) coacervates as SDS is known to decrease the aggregation number of Pluronic micelles. Increasing the SDS concentration leads to larger water content in the coacervate and an increase in the relative concentration of PAA to the other solids. Rheological characterization with small angle oscillatory shear (SAOS) demonstrates that these coacervates are viscoelastic liquids with the moduli decreasing with the addition of the SDS. The loss factor (tan δ) initially increases linearly with the addition of SDS, but a step function increase in the loss factor occurs near the reported CMC of SDS. However, this change in rheological properties does not appear to be correlated with any large scale structural differences in the coacervate as determined by small angle X-ray scattering (SAXS) with no signature of Pluronic micelles in the coacervate when SDS concentration is >4 mM during formation of the coacervate, which is less than that observed (6 mM SDS) in initial Pluronic F108 solution despite the higher polymer concentration in the coacervate. Finally, these results suggest that the mechanical properties of polyelectrolyte-non-ionic surfactant coacervates are driven by the efficicacy of binding between the complexing species driving the coacervate, which can be disrupted by competitive binding of the SDS to the Pluronic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Harnessing biomimetic cryptic bonds to form self-reinforcing gels

Cryptic sites, which lay hidden in folded biomolecules, become exposed by applied force and form new bonds that reinforce the biomaterial. While these binding interactions effectively inhibit mechanical deformation, there are few synthetic materials that harness mechano-responsive cryptic sites to forestall damage. Here, we develop a computational model to design polymer gels encompassing cryptic sites and a lower critical solution temperature (LCST). LCST gels swell with a decrease in temperature, thereby generating internal stresses within the sample. The gels also encompass loops held together by the cryptic sites, as well as dangling chains with chemically reactive ends. A decrease in temperature or an applied force causes the loops to unfold and expose the cryptic sites, which then bind to the dangling chains. We show that these binding interactions act as “struts” that reinforce the network, as indicated by a significant decrease in the volume of the gel (from 44% to 80%) and shifts in the volume phase transition temperature. Once the temperature is increased or the deformation is removed, the latter “cryptic bonds” are broken, allowing the loops to refold and the gel to return to its original state. These findings provide guidelines for designing polymer networks with reversible, mechano-responsive bonds, which allow gels to undergo a self-stiffening behavior in response to a temperature-induced internal stress or external force. When applied as a coating, these gels can prevent the underlying materials from undergoing damage and thus, extend the lifetime of the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗