Degradable polymers are used widely in tissue engineering and regenerative medicine. Maturing capabilities in additive manufacturing coupled with advances in orthogonal chemical functionalization ...methodologies have enabled a rapid evolution of defect-specific form factors and strategies for designing and creating bioactive scaffolds. However, these defect-specific scaffolds, especially when utilizing degradable polymers as the base material, present processing challenges that are distinct and unique from other classes of materials. The goal of this review is to provide a guide for the fabrication of biodegradable polymer-based scaffolds that includes the complete pathway starting from selecting materials, choosing the correct fabrication method, and considering the requirements for tissue specific applications of the scaffold.
Polyether-ether-ketone (PEEK) is one of the most common materials used for load-bearing orthopaedic devices due to its radiolucency and favorable mechanical properties. However, current ...smooth-surfaced PEEK implants can lead to fibrous encapsulation and poor osseointegration. This study compared the in vitro and in vivo bone response to two smooth PEEK alternatives: porous PEEK and plasma-sprayed titanium coatings on PEEK. MC3T3 cells were grown on smooth PEEK, porous PEEK, and Ti-coated PEEK for 14 days and assayed for calcium content, osteocalcin, VEGF and ALP activity. Osseointegration was investigated by implanting cylindrical implants into the proximal tibiae of male Sprague Dawley rats for 8 weeks. Bone-implant interfaces were evaluated using μCT, histology and pullout testing. Cells on porous PEEK surfaces produced more calcium, osteocalcin, and VEGF than smooth PEEK and Ti-coated PEEK groups. Bone ingrowth into porous PEEK surfaces was comparable to previously reported porous materials and correlated well between μCT and histology analysis. Porous PEEK implants exhibited greater pullout force, stiffness and energy-to-failure compared to smooth PEEK and Ti-coated PEEK, despite Ti-coated PEEK exhibiting a high degree of bone-implant contact. These results are attributed to increased mechanical interlocking of bone with the porous PEEK implant surface. Overall, porous PEEK was associated with improved osteogenic differentiation in vitro and greater implant fixation in vivo compared to smooth PEEK and Ti-coated PEEK. These results suggest that not all PEEK implants inherently generate a fibrous response and that topography has a central role in determining implant osseointegration.
Molecular dynamics simulations are performed to study the atomistic mechanisms governing the pseudoelasticity and shape memory in nickel–titanium (NiTi) nanostructures. For a 〈110〉 – oriented ...nanopillar subjected to compressive loading–unloading, we observe either a pseudoelastic or shape memory response, depending on the applied strain and temperature that control the reversibility of phase transformation and deformation twinning. We show that irreversible twinning arises owing to the dislocation pinning of twin boundaries, while hierarchically twinned microstructures facilitate the reversible twinning. The nanoscale size effects are manifested as the load serration, stress plateau and large hysteresis loop in stress–strain curves that result from the high stresses required to drive the nucleation-controlled phase transformation and deformation twinning in nanosized volumes. Our results underscore the importance of atomistically resolved modeling for understanding the phase and deformation reversibilities that dictate the pseudoelasticity and shape memory behavior in nanostructured shape memory alloys.
Stem cell fate has been linked to the mechanical properties of their underlying substrate, affecting mechanoreceptors and ultimately leading to downstream biological response. Studies have used ...polymers to mimic the stiffness of extracellular matrix as well as of individual tissues and shown mesenchymal stem cells (MSCs) could be directed along specific lineages. In this study, we examined the role of stiffness in MSC differentiation to two closely related cell phenotypes: osteoblast and chondrocyte. We prepared four methyl acrylate/methyl methacrylate (MA/MMA) polymer surfaces with elastic moduli ranging from 0.1 MPa to 310 MPa by altering monomer concentration. MSCs were cultured in media without exogenous growth factors and their biological responses were compared to committed chondrocytes and osteoblasts. Both chondrogenic and osteogenic markers were elevated when MSCs were grown on substrates with stiffness <10 MPa. Like chondrocytes, MSCs on lower stiffness substrates showed elevated expression of ACAN, SOX9, and COL2 and proteoglycan content; COMP was elevated in MSCs but reduced in chondrocytes. Substrate stiffness altered levels of RUNX2 mRNA, alkaline phosphatase specific activity, osteocalcin, and osteoprotegerin in osteoblasts, decreasing levels on the least stiff substrate. Expression of integrin subunits α1, α2, α5, αv, β1, and β3 changed in a stiffness- and cell type-dependent manner. Silencing of integrin subunit beta 1 (ITGB1) in MSCs abolished both osteoblastic and chondrogenic differentiation in response to substrate stiffness. Our results suggest that substrate stiffness is an important mediator of osteoblastic and chondrogenic differentiation, and integrin β1 plays a pivotal role in this process.
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•The ability of a simple machine learning model to predict mechanical properties of 3D printed lattices is demonstrated.•The effect of printing defects on photopolymer lattice sample ...mechanical and geometric properties is highlighted.•A framework is presented for including both structure and material info into property predictions of 3D printed lattices.•Kernel ridge regression is used to make accurate mechanical property predictions using a small amount of training data.
Advancements in additive manufacturing (AM) technology and three-dimensional (3D) modeling software have enabled the fabrication of parts with combinations of properties that were impossible to achieve with traditional manufacturing techniques. Porous designs such as truss-based and sheet-based lattices have gained much attention in recent years due to their versatility. The multitude of lattice design possibilities, coupled with a growing list of available 3D printing materials, has provided a vast range of 3D printable structures that can be used to achieve desired performance. However, the process of computationally or experimentally evaluating many combinations of base material and lattice design for a given application is impractical. This research proposes a framework for quickly predicting key mechanical properties of 3D printed gyroid lattices using information about the base material and porosity of the structure. Experimental data was gathered to train a simple, interpretable, and accurate kernel ridge regression machine learning model. The performance of the model was then compared to numerical simulation data and demonstrated similar accuracy at a fraction of the computation time. Ultimately, the model development serves as an advancement in ML-driven mechanical property prediction that can be used to guide extension of current and future models.
Shape‐memory polymers are a class of smart materials that have recently been used in intelligent biomedical devices and industrial applications for their ability to change shape under a predetermined ...stimulus. In this study, photopolymerized thermoset shape‐memory networks with tailored thermomechanics are evaluated to link polymer structure to recovery behavior. Methyl methacrylate (MMA) and poly(ethylene glycol) dimethacrylate (PEGDMA) are copolymerized to create networks with independently adjusted glass transition temperatures (Tg) and rubbery modulus values ranging from 56 to 92 °C and 9.3 to 23.0 MPa, respectively. Free‐strain recovery under isothermal and transient temperature conditions is highly influenced by the Tg of the networks, while the rubbery moduli of the networks has a negligible effect on this response. The magnitude of stress generation of fixed‐strain recovery correlates with network rubbery moduli, while fixed‐strain recovery under isothermal conditions shows a complex evolution for varying Tg. The results are intended to help aid in future shape‐memory device design and the MMA‐co‐PEGDMA network is presented as a possible high strength shape‐memory biomaterial.
Shape‐memory polymers have been proposed for a variety of biomedical applications. The figure shows a shape‐memory polymer expanding to secure a soft tissue. This paper investigates the fundamental relationships of shape‐recovery to a polymer network's structure. The glass transition temperature and rubbery modulus values are systematically varied and tested under free‐ and fixed‐strain recovery.
Shape memory polymers (SMPs) can retain a temporary shape after pre-deformation at an elevated temperature and subsequent cooling to a lower temperature. When reheated, the original shape can be ...recovered. Relatively little work in the literature has addressed the constitutive modeling of the unique thermomechanical coupling in SMPs. Constitutive models are critical for predicting the deformation and recovery of SMPs under a range of different constraints. In this study, the thermomechanics of shape storage and recovery of an epoxy resin is systematically investigated for small strains (within ±10%) in uniaxial tension and uniaxial compression. After initial pre-deformation at a high temperature, the strain is held constant for shape storage while the stress evolution is monitored. Three cases of heated recovery are selected: unconstrained free strain recovery, stress recovery under full constraint at the pre-deformation strain level (no low temperature unloading), and stress recovery under full constraint at a strain level fixed at a low temperature (low temperature unloading). The free strain recovery results indicate that the polymer can fully recover the original shape when reheated above its glass transition temperature (
T
g). Due to the high stiffness in the glassy state (
T
<
T
g), the evolution of the stress under strain constraint is strongly influenced by thermal expansion of the polymer. The relationship between the final recoverable stress and strain is governed by the stress–strain response of the polymer above
T
g. Based on the experimental results and the molecular mechanism of shape memory, a three-dimensional small-strain internal state variable constitutive model is developed. The model quantifies the storage and release of the entropic deformation during thermomechanical processes. The fraction of the material freezing a temporary entropy state is a function of temperature, which can be determined by fitting the free strain recovery response. A free energy function for the model is formulated and thermodynamic consistency is ensured. The model can predict the stress evolution of the uniaxial experimental results. The model captures differences in the tensile and compressive recovery responses caused by thermal expansion. The model is used to explore strain and stress recovery responses under various flexible external constraints that would be encountered in applications of SMPs.
Previous atomistic simulations and experiments have attributed size effects in the elastic modulus of Ag nanowires to surface energy effects inherent to metallic surfaces. However, differences in ...experimental and computational trends analyzed here imply that other factors are controlling experimentally observed modulus changes. This study utilizes atomistic simulations to determine how strongly nanowire geometry and surface structure influence nanowire elastic modulus. The results demonstrate that although these factors do influence the elastic modulus of Ag nanowires to some extent, they alone are insufficient to explain current experimental trends in nanowire modulus with decreasing dimensional scale. Future work needs to be done to determine whether other factors, such as surface contaminants or oxide layers, contribute to the experimentally observed elastic modulus increase.
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