Michael Barbella, Managing Editor06.07.24
The relationship between stress modulation and their structures has long remained elusive. But researchers are gaining insight into the intelligent approach to physical stress distriibution found in natural materials like wood and bone.
By integrating machine learning, optimization, 3D printing, and stress experiments, engineers at the University of Illinois Urbana-Champaign have developed a material that replicates human bone. This substance could provide orthopedic surgeons with a new fracture healing solution.
Fractures to the femur (the long bone in the upper leg), are a common injury and particularly prevalent among the elderly. The broken edges cause stress to concentrate at the crack tip, increasing the chances the fracture will lengthen. Conventional repair methods typically involve surgical procedures to attach a metal plate around the fracture with screws, which may cause loosening, chronic pain, and further injury.
A study led by University of Illinois Urbana-Champaign civil and environmental engineering professor Shelly Zhang and graduate student Yingqi Jia in collaboration with professor Ke Liu from Peking University introduces a new approach to orthopedic repair that uses a fully controllable computational framework to produce a material that mimics bone. The study findings are published in Nature Communications.
“We started with materials database and used a virtual growth stimulator and machine learning algorithms to generate a virtual material, then learn the relationship between its structure and physical properties,” Zhang said. “What separates this work from past studies is that we took things a step further by developing a computational optimization algorithm to maximize both the architecture and stress distribution we can control.”
In the lab, Zhang’s team used 3D printing to create a full-scale resin prototype of the new bio-inspired material and attached it to a synthetic model of a fractured human femur.
“Having a tangible model allowed us to run real-world measurements, test its efficacy and confirm that it is possible to grow a synthetic material in a way analogous to how biological systems are built,” Zhang said. “We envision this work helping to build materials that will stimulate bone repair by providing optimized support and protection from external forces.”
According to Zhang, this technique can be applied to various biological implants anywhere stress manipulation is needed. “The method itself is quite general and can be applied to different types of materials such like metals, polymers—virtually any type of material,” she noted. “The key is the geometry, local architecture and the corresponding mechanical properties, making applications almost endless.”
The David C. Crawford Faculty Scholar Award from the University of Illinois supported this research.
Zhang also is affiliated with mechanical science and engineering and the National Center for Supercomputing Applications at Illinois.
By integrating machine learning, optimization, 3D printing, and stress experiments, engineers at the University of Illinois Urbana-Champaign have developed a material that replicates human bone. This substance could provide orthopedic surgeons with a new fracture healing solution.
Fractures to the femur (the long bone in the upper leg), are a common injury and particularly prevalent among the elderly. The broken edges cause stress to concentrate at the crack tip, increasing the chances the fracture will lengthen. Conventional repair methods typically involve surgical procedures to attach a metal plate around the fracture with screws, which may cause loosening, chronic pain, and further injury.
A study led by University of Illinois Urbana-Champaign civil and environmental engineering professor Shelly Zhang and graduate student Yingqi Jia in collaboration with professor Ke Liu from Peking University introduces a new approach to orthopedic repair that uses a fully controllable computational framework to produce a material that mimics bone. The study findings are published in Nature Communications.
“We started with materials database and used a virtual growth stimulator and machine learning algorithms to generate a virtual material, then learn the relationship between its structure and physical properties,” Zhang said. “What separates this work from past studies is that we took things a step further by developing a computational optimization algorithm to maximize both the architecture and stress distribution we can control.”
In the lab, Zhang’s team used 3D printing to create a full-scale resin prototype of the new bio-inspired material and attached it to a synthetic model of a fractured human femur.
“Having a tangible model allowed us to run real-world measurements, test its efficacy and confirm that it is possible to grow a synthetic material in a way analogous to how biological systems are built,” Zhang said. “We envision this work helping to build materials that will stimulate bone repair by providing optimized support and protection from external forces.”
According to Zhang, this technique can be applied to various biological implants anywhere stress manipulation is needed. “The method itself is quite general and can be applied to different types of materials such like metals, polymers—virtually any type of material,” she noted. “The key is the geometry, local architecture and the corresponding mechanical properties, making applications almost endless.”
The David C. Crawford Faculty Scholar Award from the University of Illinois supported this research.
Zhang also is affiliated with mechanical science and engineering and the National Center for Supercomputing Applications at Illinois.