BIOMED Seminar

Title:
Imaging-based Experiments and Modeling for Bone-implant Biomechanics
 
Speaker:
Jing Du, PhD
Assistant Professor
Department of Mechanical Engineering
College of Engineering
Penn State University

Details:
Bone is a complex anisotropic hierarchical composite that consists of inorganic and organic components. Bone is also a living material that adapts to mechanical stimulations through continuous modeling and remodeling activities. The morphology and mechanical properties of bone change as a result of diseases and treatment. This study presents the results of image-based experiments and simulations of the mechanical behaviors and microstructures of bone.

Mechanical testing coupled micro X-ray computed tomography (micro-CT) enabled concurrent non-invasive characterization of 3D full-field bone microstructures and bone mechanical properties. Atomic force microscopy (AFM) was used to map the surface morphology and elastic properties of bone from sub-millimeter to sub-micron scale. The experimental results are integrated with computational models to provide mechanical insights for the potential improvement of the implant treatment.

Biosketch:
Jing Du, PhD, is an assistant professor of Mechanical Engineering at Penn State University. Dr. Du received her BS and MS degrees in Mechanical Engineering and Materials Science and Engineering, respectively, from Tsinghua University, and her PhD
degree in Mechanical and Aerospace Engineering from Princeton University.

Before joining Penn State, Dr. Du was a postdoctoral scholar in the School of Dentistry at the University of California, San Francisco (UCSF). Her current areas of research interests include mechanical behaviors of biological tissues and biomaterials, biomedical devices, and bio-inspired design.

BIOMED PhD Thesis Defense
 
Title:
Investigating the Interfacial Bonding Strength of Additively Manufactured Polyetheretherketone (PEEK) Intervertebral Devices
    
Speaker:
Cemile Basgul, PhD Candidate
School of Biomedical Engineering, Science and Health Systems
Drexel University

Advisors:
Steven M. Kurtz, PhD
Research Professor
School of Biomedical Engineering, Science and Health Systems
Drexel University

Kenneth Barbee, PhD
Professor
Senior Associate Dean and Associate Dean for Research
School of Biomedical Engineering, Science and Health Systems
Drexel University

Details:
Interlayer delamination in Additively Manufactured (AM) PEEK implants has been shown to have detrimental mechanical consequences, and recent clinical observations have suggested that it may compromise the integrity of patient-specific Fused Filament Fabricated (FFF) PEEK implants. This dissertation describes thermally driven healing mechanisms in FFF PEEK by developing a model to quantitively assess the healing to evaluate the interlayer adhesion phenomena. Furthermore, it provides an overview of the AM technologies, materials, parameters, design variables, and clinical applications that have been previously studied to understand their impact on the performance of AM PEEK implants.

Firstly, FFF parameters that indirectly controlled the thermal mechanisms were evaluated for PEEK spinal cages printed using the first two generations of FFF machines. Layer delamination as a failure mechanism was identified in both generations of FFF PEEK cages. Altering the cooling time of a layer was not able to change the failure mechanism of FFF cages; however, it improved the mechanical strength of the cages. Although the main temperature settings used to 3D print cages in two generations of FFF machines were different, the mechanical strength did not differ between the two generations of cages. Printing a single cage per build, which decreased the layer cooldown time, was associated with a higher ultimate load than printing multiple cages per build. Regardless of the cage number printed per build, cages printed with a bigger nozzle demonstrated a higher ultimate load than cages printed with a smaller nozzle, in which the layers cooled down twice as fast.

Considering the thermal mechanisms that affect the layer adhesion, a 1D heat transfer model (HTM) was developed to assess the interlayer and layer temperatures in a FFF PEEK build. The temperature evolutions calculated from HTM were then employed in the non-isothermal degree of healing model. The healing was higher between the upper layers with reference to the print bed when compared to the lower layers. Among the three key FFF temperatures, the nozzle temperature was the most crucial in layer healing. Once it was below a specific value, none of the layers healed properly. The degree of healing increased with the improved build plate temperature allowing more layers to heal 100%. Despite the environment temperature being less influential on the healing of lower layers, more layers healed completely with the chamber temperature increment.

Finally, the heat transfer constituent of the established model to examine the FFF PEEK layer temperatures was validated individually with industrial (2nd) and medical (3rd) generation FFF machines. As observed in theoretical temperature evolutions, the experimental results were in agreement that the temperatures of upper FFF PEEK layers would stay higher. The comparison of the model and the experiments for layer temperatures during FFF processes in both machines overlapped particularly closer to the mid-layers. During the first quarter of the print period, where the healing calculations would be affected, model approximations were converged to the experimental temperatures earlier (beginning at the 20th layers) in both machines and were aligned with the upper layer temperatures until the top of the FFF PEEK builds. The detailed validation method presented here for heat transfer models on determining the layer temperatures of FFF builds will promote further model developments as well as HTM implementation in healing models. The framework introduced in this thesis will enable the parameter optimization to achieve sufficiently healed layers through FFF builds, thus enhancing the macro mechanical properties of FFF PEEK implants for AM at point-of-care.